Preface - iasri.icar.gov.in · • Signing of MOU with IARI, New Delhi to start new courses for M.Sc. and Ph.D. degree in Agricultural Statistics 1970 • Status of a full fledged

Preface

It gives me immense pleasure inbringing out the Annual Report 2009-10 of the Indian Agricultural StatisticsResearch Institute (IASRI). Thepresent report highlights some ofthe glimpses of the researchachievements made, newmethodologies developed, significant

advisory and consultancy services provided,dissemination of knowledge acquired and developmentof human resource. The scientists, technical personnel,administrative, finance and other staff of the Institutehave put in their best efforts in fulfilling the mandate ofthe Institute.

To fulfill objectives and mandate of the Institute, theresearch was carried out under 50 research projects inthe Institute (01 National Professor Scheme, 30 Institutefunded, 05 NAIP funded, 01 AP Cess funded, 04 fundedby other outside agencies and 09 in collaboration withother Institutions). 12 projects have been completedand 06 new studies/projects have been initiated withone as ad-hoc study. One of the new initiativeundertaken this year is initiation of NAIP ConsortiumStrengthening Statistical Computing for NARS forcreation of sound and healthy statistical/computingenvironment for the benefit of scientists.

It gives me great satisfaction that the Institute hascelebrated its Golden Jubilee year, completing 50years on 02 July 2009. As part of Golden JubileeCelebrations, five Golden Jubilee Workshops wereorganised. A publication “IASRI ... an era of Exellence”has also been published.

Eleven training programmes (One under Center ofAdvanced Faculty Training; one Winter School; one forISS Probationers; four for CSO officials; threeInternational Training programmes one for CAC staffat Tashkent, one at ICARDA, Syria and one sponsoredby AARDO; one special training programme onfinancial matters for officials of ICAR Hqrs.) wereorganized. In all 182 participants were trained in thesetraining programmes. Ten other Symposium/Workshops, one Workshop in Hindi and twoBrainstorming sessions on Establishment of Centre ofAgricultural Bioinformatics were also organised.

An important breakthrough in the capacity building andsensitization of the scientists of NARS was the initiationof a new concept of organizing “Travel TrainingProgrammes” at different locations in various areas ofstatistics and computer applications. Three such traveltraining programmes on Advances in Design ofExperiments were organized for the scientists ofANGRAU, Hyderabad and its centres and 245researchers were sensitized.

Scientists of the Institute published 61 research papersin National and International refereed Journals alongwith 24 popular articles, 06 book chapters, 24 projects/technical reports/reference manuals, 03 pamphlets and04 workshops proceedings.

I am happy to note that some of our colleagues receivedacademic distinctions during the year.

The scientists of the Institute were deputed forpresentation of their papers in various national/international conferences. This year two scientists weredeputed to present their papers to Washington DC andSouth Africa. Four scientists visited Malaysia, Tunisia,Uzbekistan, Spain, South Africa, USA and Syria ondifferent assignments.

To promote Hindi, a poster presentation of researchpapers in Hindi was organized.

This report has been compiled through collective effortsrendered by Heads of Divisions, scientists and otherstaff of the Institute. I wish to express my sincereappreciation to all of them for their devotion, whole-hearted support and cooperation in carrying out variousfunctions and activities of the Institute.

I wish to express my sincere thanks to all my colleaguesin Research Coordination and Management Unit forcoordinating various activities and Hindi Section forHindi Translation of the required material.

It is expected that the scientists in NARS will beimmensely benefitted from the information containedin this publication. I look forward to any suggestionsand comments for its improvements.

(VK Bhatia)Director

Milestones1930 • Statistical Section created under ICAR

1940 • Activities of the Section increased with appointment of Dr. PV Sukhatme

1945 • Re-organisation of statistical section into statistical branch as a centrefor research and training in the field of Agricultural Statistics

1949 • Re-named as Statistical Wing of ICAR

1952 • Activities of Statistical Wing further expanded and diversified with therecommendations of FAO experts, Dr. Frank Yates and Dr. DJ Finney

1955 • Statistical Wing moved to its present campus

1956 • Collaboration with AICRP initiated

1959 • Re-designated as Institute of Agricultural Research Statistics (IARS)

1964 • Installation of IBM 1620 Model-II Electronic Computer

• Signing of MOU with IARI, New Delhi to start new courses for M.Sc. andPh.D. degree in Agricultural Statistics

1970 • Status of a full fledged Institute in the ICAR system, headed by Director

1977 • Three storeyed Computer Centre Building inaugurated

• Installation of third generation computer system, Burroughs B-4700

1978 • Re-named as Indian Agricultural Statistics Research Institute (IASRI)

1983 • Identified as Centre of Advanced Studies in Agricultural Statistics andComputer Applications under the aegis of the United NationsDevelopment Programme (UNDP)

1985–86 • New Course leading to M.Sc. degree in Computer Application inAgriculture, initiated

1989 • Commercialization of SPAR 1

1991 • Burroughs B-4700 system replaced by a Super Mini COSMOS LANServer

1992 • Administration-cum-Training Block of the Institute was inaugurated

1993–94 • M.Sc. degree in Computer Application in Agriculture changed to M.Sc. inComputer Application

1995 • Center of Advanced Studies in Agricultural Statistics & ComputerApplication established by Education Division, ICAR

1996 • Establishment of Remote Sensing & GIS lab with latest software facilities

• Outside funded projects initiated

1997 • Senior Certificate Course in ‘Agricultural Statistics and Computing’ revived

• Establishment of modern computer laboratories

• First software in India for generation of design along with its randomisedlayout SPBD release 1.0

1998 • Four Divisions of the Institute re-named as Sample Survey, Design ofExperiments, Biometrics and Computer Applications

• Revolving Fund Scheme on Short Term Training Programs in InformationTechnology initiated

• Training programmes in statistics for non-statisticians in NationalAgricultural Research System initiated

1999 • Strengthening of LAN & Intranet with Fibre optics & UTP cabling

• Substantial growth in outside funded projects and training programmes

2000 • Two Divisions re-named as Division of Forecasting Techniques andDivision of Econometrics

2001 • Data Warehousing activities (INARIS project under NATP) initiated

2002 • Establishment of National Information System on Animal ExperimentsLaboratory

• Development of PIMSNET(Project Information Management System onInternet) for NATP

2003 • Establishment of National Information System on Long-term FertilizerExperiments funded by AP Cess Fund

• Development of PERMISnet (A software for Online Information onPersonnel Management in ICAR System)

• First indigenously developed software on windows platform releasedStatistical Package for Factorial Experiments (SPFE) 1.0

2004 • National Information System on Agricultural Education (NISAGENET)Project launched

• Training Programme for private sector initiated and conducted trainingprogramme for E.I. DuPont India Private Limited

• E-Library Services initiated

2005 • Statistical Package for Augmented Designs (SPAD) and StatisticalPackage for Agricultural Research (SPAR) 2.0 released

• Design Resources Server with an aim to provide E-advisory in NARSinitiated

2006 • Organisation of International Conference on Statistics and Informaticsin Agricultural Research

2007 • Establishment of Agricultural Bioinformatics Laboratory(ABL)

2008 • Software for Survey Data Analysis (SSDA) 1.0 released

2009 • Golden Jubilee Celebration Year of the Institute

• Strengthening Statistical Computing for NARS initiated

• International Training Hostel inaugurated

● To undertake basic, applied adaptive, strategic and anticipatoryresearch in Agricultural Statistics and related fields and use theseresearches in meeting challenges and improving quality of agriculturalresearch.

● To conduct post-graduate teaching and in-service, customized andsponsored training courses in Agricultural Statistics and ComputerApplications at National and International level so as to be a leadcentre of excellence in Human Resource Development.

● To provide methodological support in strengthening NationalAgricultural Statistics System by establishing linkages with Statedepartments of agriculture and allied fields, other research institutions,industry, etc.

● To lead in development of Agricultural Knowledge Management andInformation System for National Agricultural Research System.

● To provide advisory and consultancy services for strengthening theNational Agricultural Research System and undertaking sponsoredresearch and consultancy for National and Internationalorganizations.

Vision

Statistics and ICT for enriching the quality of Agricultural Research

Undertake research, education and training in Agricultural Statistics andComputer Applications for Agricultural Research

Mission

Mandate

● lkekU; CykWd vfHkdYiuk }kjk vk¡dMksa ds vkWu ykbu fo'ys"k.kds fy, ,d ekWM;wy fodflr fd;k x;k ftls laLFkku dhosclkbV ds eq[k i`"B ij viyksM fd;k x;k A

● VªhVesUV~l dh nh gqbZ la[;k v] CykWd vkdkj k ds fy,cgqHkqth; vfHkdYiuk,a izkIr djus ds fy, ,d jSf[kd iw.kkZadb.Vhtj izksxzkfeax i¼fr fodflr dh x;h ftlesa mu VªhVesUV~ltks m+1 ;k mlls vf/d gksa] ds dkaØsl λ rFkk vU; VªhVesUV

;qXeksa ds dkWUØsUl 'kwU; gks A ;gk¡ ⎥⎦

⎤⎢⎣

⎡≤2

vm ekuk x;k ,oa [.]

mPpre iw.kkZad iQyu dks n'kkZrk gS A ;s vfHkdYiuk,¡ larqfyrçfrp;u ;kstuk,a çkIr djus ds fy, mi;ksxh gSa A

● vkWu&iQkeZ ijh{k.kksa ds vk¡dM+ksa dk ç;ksx djrs gq, ,u-,-vkj-ih- tksu Lrj] jkT; Lrj ,oa vf[ky Hkkjrh; Lrj ij 14iQ+lyksa (05 vukt] 04 nkysa vkSj 05 frygu) ds moZjdiks"kd ds çfr fdyksxzke mi;ksx }kjk ,d fdyksxzke iQ+lymit esa vkSlr o`f¼] moZjd vuqfØ;k vuqikr (,iQ-,iQ-vkj)çkIr fd;s x;s A vukt] frygu ,oa nkyksa ds lewg ds fy,fu;a=k.k ds çfr N moZjd vuqfØ;k vuqikr Øe'k% 9-20]7-73 ,oa 1-5 fd-xzk-@fd-xzk- gaS tcfd fu;a=k.k ds çfr NPK

ds ;s eku Øe'k% 10-80] 5-60 ,oa 6-70 fd-xzk-@fd-xzk- gaS Ajk"Vªh; Lrj ij leLr [kk|kUu iQ+lyksa dk iwYM vuqfØ;kvuqikr 8-79 fd-xzk-@fd-xzk- (fu;a=k.k ds çfr NP) ,oa 10-98fd-xzk-@fd-xzk- ds eè; esa gS A lHkh [kk|kUu iQ+lyksa ds fy,fu;a=k.k ds çfr NPK dk moZjd vuqfØ;k vuqikr 9-27fd-xzk-@fd-xzk- ik;k x;k tks fd vuq'kalk ds vuqlkj N, NP,

NK ds fy, ik;s x;s vuqfØ;k ls vf/d Fkk A

● eYVh ys;j ijlsIVªksu (,e-,y-ih-) ,oa jsfMvy vk/kfjriQyu (vkj-ch-,iQ-) vk/kfjr ,d ;k nks fgMu ys;jl lfgrU;wjy usVoDlZ dk iz;ksx djds ,oa pkoy] xsgw¡ o xUuk mitdks jsliksUl pj rFkk ekSle pjksa dks bUiqV pj ysrs gq, mitiwokZuqeku ekWMy fodflr fd, x,A

● ,e-,y-ih- ,oa vkj-ch-,iQ- vk/kfjr usVoDlZ dk iz;ksx djrsgq, rFkk buiqV pjksa ds :i esa ekSle pjksa dk iz;ksx djdsljlksa dh iQ+ly esa vYVjusfjvk CykbV ,oa ikmMªh feYM~;w dsfy, jksx iwoZ&psrkouh ekWMYl fodflr fd;s x;s A

● o"kZ 1971&2002 dh vof/ ds nkSjku vf/dre ,oa U;wurerkieku rFkk çkr% ,oa lka; dh lkis{k vknzZrk ds ekSlelEcU/h vk¡dM+ksa dk ç;ksx djrs gq, mRrj çns'k esa vkyw dhmit dks iwokZuqeku ds fy, ekSle vk/kfjr ekWMy fodflrfd;s x;s A

● vizkpfyd iQyu vkWVksfjxsjsflo ekWMy yxkus ds fy, xq.kkadiQyuksa dk vkdyu fd;k x;k ftlesa Hkkfjr U;wure oxZ fof/}kjk Vsyjl lhfjt ,Dlisa'ku dk iz;ksx fd;k x;k tcfd

djusy MsaflVh iQyu dks Hkkj ds :i esa fy;k x;kALo ,sDlkbfVax Fkjs'kksYM vkWVksfjxzsflo (,l-bZ-Vh-,-vkj-),d ls vf/d Fkjs'kksYM lfgr vjSf[kd le; J`a[kykekWMYl dh iQSfeyh dh Ñf"k esa iz;ksxkRedrk dks n'kkZ;kx;kA ;s le; Ja[kyk,a o`rh; :i esa vk¡dM+ksa dk izn'kZudjrh gSaA

● eYVhekWMy o"kkZ lEcU/h vk¡dM+ksa ds fy, lkaf[;dh; yfuZaxF;ksjh ds mi;ksx }kjk ^ckWMh* ,oa ^Vsy* esa feJ.k ds forj.kds la;kstu dh i¼fr dk çn'kZu fd;k x;k A o"kkZ lEcU/hvk¡dM+ksa esa lS¼kafrd ^Vsy* forj.k ds la;kstu gsrq pje ekulwpdkad ds rhu vkdydksa dh lax.kuk dh x;hA

● egRoiw.kZ vuktksa (pkoy] xsgw¡] Tokj] cktjk] eDdk)] fryguksa(ew¡xiQyh] ljlksa)] [kk|&rsyksa (ukfj;y dk rsy] ew¡xiQyh dkrsy] ljlksa dk rsy) ,oa nyguksa (puk] ew¡x] vjgj] mM+nbR;kfn) dh Fkksd dher ij dky Js.kh vk¡dM+ksa dk ç;ksxdjrs gq, dky Jsf.k;ksa dh fLFkjrk dh VsfLVax ds fy,laof/Zr fMDdh iQ~;wyj rduhd] dksb.VhxszfVax osDVlZ dk irkyxkus ds fy, tksgUlu dh dks&b.Vhxsz'ku fof/ rFkk larqyuds çfr dky Jsf.k;ksa ds lek;kstu dh xfr dk irk yxkus dsfy, lfn'k =kqfV djsD'ku edSuhte uked mUur vFkZferh;lk/uksa dk ç;ksx djrs gq, Lisf'k;y ekdsZV bUVhxzs'ku vè;;ufd;k x;k A fo'ys"k.k ls Kkr gqvk fd gky ds o"kksZa esa cktkjksads chp ,ddhdj.k esa lq/kkj gqvk gS A Ñf"k&oLrqvksa dhdherksa esa Hkkjr ds dqN pqus gq, jkT; Lrj ds Fkksd ds ckt+kjksads chp vxzlfjr gksus dh ço`fr gS A

● Hkkoh O;kikj ds {ks=k esa egRoiw.kZ iQ+lyksa ds fy, dherokWfYVfyfV] dher fMldojh ,oa tksf[ke çcU/u dkvè;;u fd;k x;k rFkk Hkkjrh; xsgw¡ ,oa eDds dh iQ+ly dsdkWUVªsDV fMtkbuksa dh vesfjdk ds dkWUVªsDVksa ls rqyuk dh x;hAHkkoh ;wpj ekfdZV dh okWfYVfyfV] LikWV ekfdZV okWfYVfyfV lsvf/d cM+h gksrh gSA Hkkoh dherksa dh rqyuk esa LikWV dherksadk forj.k vf/d fo"ke gksrk gS A

● ¶ikni vkuqoafa'kdh ,oa çtuu¸ ls lEcfU/kr Ñ"kh; mRikndrkdks c<+kus esa lgk;d dkjdksa dh igpku djus ds fy,eYVhMkbesaU'kuy Ldsfyax (,e-Mh-,l-) fof/ dk ç;ksx fd;ktkrk gS A ;g ik;k x;k fd Hkkjr u dsoy ,cks;ksfVd ,oack;ksfVd LVªslsl dh vksj vf/d è;ku ns jgk gS cfYd ,sls{ks=kksa tSls & ck;ksbUiQkWjesfVDl] eksyhD;wyj vflfLVax flysD'ku]VªkaLtSfuDl bR;kfn ds fodkl dh vksj Hkh è;ku ns jgk gS A

● f}pj.kh; çfrp;u ds vUrxZr ,d en ds fy, Mksesu rFkklef"V ;ksx] nksuksa ds vkdyd fodflr fd;s x;s tgk¡ Mksesudh fof'k"Vrk vuqHko dh x;h] ijUrq pj.k 1 dh çfrn'kZ bdkbZls vkbZVe fjLik¡l vko';d :i ls miyC/ ugha Fkk A

● f}pj.kh; çfrp;u ds vUrxZr vuqikr vkdyd ds çlj.k dsvuqekfur vufHkUkr vkdyd fodflr fd;s x;s A

● ¶'kwU;&LiQhr vk¡dM+ksa ds fy, y?kq {ks=k vkdyu¸ ukedvè;;u esa feDpj ekWMy dk mi;ksx djrs gq, ,l-,-bZ dsfy, ,d fof/ fodflr dh x;h tks vk¡dM+ksa esa vfrfjDr 'kwU;mifLFkfr dh x.kuk djrh gS A bl mn~ns'; ds fy, feDpjekWMy dks yhfu;j feDpj ekWMy ,oa tuZykbTM yhfu;jfeDLM ekWMy ds la;kstu ds :i esa ifjHkkf"kr fd;k x;k gS A,l-,-bZ- dh çLrkfor vçksp rhu pj.kksa esa dk;Zjr gSA çFke]pj ds /ukRed ekuksa ds fy, ,d yhfu;j feDLM ekWMyla;ksftr fd;k tkrk gS] nwljs pj.k esa] /ukRed ekuksa dhlEHkkO;rk ds fy, tuZykbTM yhfu;j feDLM ekWMy la;ksftrfd;k tkrk gS A vUr esa] vkdyu ds pj.k esa nksuksaa ekWMyksa dksla;ksftr fd;k tkrk gS A

● ,slh ifjfLFkfr;ksa esa ftuesa vè;;u/hu pj rFkk bdkb;ksa dsvkdkjksa dk udkjkRed lg&lEcU/ gksrk gS muesa vkdkjçfrp;u ;kstuk ds O;qRØekuqikrh lEHkkO;rk (vkbZ-ih-vkbZ-ih-,l- ;kstuk) dks 'kkfey djus dh vo/kj.kk 'kkfey dh x;hAvkbZ-ih-vkbZ-ih-,l- ;kstuk lqfuf'pr djrh gS fd bdkb;ksa dhiQLVZ vkMZj lEHkkO;rk bdkb;ksa ds vkdkj ds ekiksa dsO;qRØekuqikrh gks A

● pkoy thukse esa U;wfDy;ksVkbM ikWyhekWjfiQ+TEk (SNPs) dslax.kukRed fo'ys"k.k ds fy, pkoy thukse ds iQyu&vo;oksaij ,d osCk vk/kfjr lwpuk&ra=k fodflr fd;k x;k AiQyu&vo;oksa ij flaxy SNPs ij lwpuk çkIr djus ds fy,vkWu&ykbu lqfo/k,¡ miyC/ djk;h x;h A pkoy iQyu&vo;oksaij osc vk/kfjr lwpuk ç.kkyh esa ç;ksDrkvksa dks çeksVj jhtu]vuVªk¡LysVsM jhtUl] Vªk¡Ulys'ku LVkVZ lkbV~l] LIykbl lkbV~l],Dlk¡l] bUVªk¡l] Vªk¡Lkys'ku LVkWi lkbV~~l bR;kfn ij flDosUllEcU/h lwpuk çkIr djus dh lqfo/k miyC/ gS A LIykblLVksj esa LIykbl lkbV~l] iksth'ku OgsV] eSfVªlsl] iQkbykstsfufVdlEcU/h bR;kfn ds oxhZdj.k ij Hkh lwpuk miyC/ gS A

● xsgw¡ iQ+ly çcU/u ij fodflr fo'ks"kK ra=k dk oSjk;VhflysD'ku ekWM~;wy ,oa jksx uSnkfud ekWM~;wy dk fgUnh otZuvkjEHk fd;k x;k A fo'ks"kK ra=k ds fgUnh ekWM~;wy ds fy,MkVkcsl SQL loZj dh lgk;rk ls rS;kj fd;k x;k gS tksfgUnh Hkk"kk ds liksVZ ds fy, UNICODE Lohdkj djrk gSSA

● vkuqoaf'kdh lg&lEcU/ ds vkdyu ds fy,] vkmVyk;lZ dhmifLFkfr esa] vkuqoaf'kdh lg&lEcU/ ds vkdyd cgqr ghvovkdfyr gSa ftlds ifj.kkeLo:Ik vfHkufr esa cgqr o`f¼gksrh gSA vkmVyk;lZ dh mifLFkfr esa ekud =qkfV esa cgqr o`f¼gksrh gS A

● i'kq çtuu gsrq lkaf[;dh; iSdst (,l-ih-,-ch- 2-1) dk ,dβ&otZu fodflr fd;k x;k A i'kqvksa ds vkuqoaf'kd çkpyksa ds

vkdyu ,oa mudh çtuu LVªSfVtht ,oa flysD'ku çkslslrS;kj djus ds fy, ;g iSdst i'kq çtudksa ds fy, cgqrmi;ksxh gS A

● Ñf"k vuqla/ku esa lesfdr MkVk ekVZ ds fy, ukWyst MkVkos;jgkml esa lesfdr MkVk ekVZ ds fy, eYVhMkbesU'kuyekWMy rS;kj fd;k x;k A fofHkUu MkVk ekVZ~l dks le; Ja[kykvk¡dM+ks a ij vk/kfjr djds vkWu&ykbu fo'ys"k.k ,oaçkxqDrk@iwokZuqeku ds fy, ;s ekWMy fodflr ,oa fØ;kfUorfd;s x;s A bl vkWu&ykbu çkxqDrk ds fy, rhu çdkj dsekWMy vFkkZr~ Vªs.M] fodkl ,oa Lo lekJ;.k 'kkfey fd;sx;s A

● Hkk-Ñ-lka-v-la- ds loZj ls http://permisnet.iasri.res.in/

;w-vkj-,y- ij Hkk-Ñ-v-i- es a ekuo 'kfDr fu;kstu(PERMISnet-II) ds fy, fMflt+u LkiksVZ flLVe fØ;kfUorfd;k x;k A

● ih-th- Ldwy] Hkk-Ñ-v-la-] ubZ fnYyh ds fy, ,d vkWu&ykbuizCkU/u&ra=k fodflr fd;k x;k A blesa ikB~~~;Øeksa ds izcU/u]Nk=kksa] ladk;] ç'kklu ,oa bZ&yfuZax ds fy, ik¡p ekM~;wYk gSa Abl ra=k esa 267 Nk=k rFkk 412 ladk; lnL; iathÑr gks pqdsgSa A bl ra=k esa 23 fo"k;ksa esa 536 ikB~;Øe lwph gSa A lHkhNk=kksa dks çFke ,oa f}rh; VªkbesLVj ds fy, vkWu&ykbujftLVj fd;k x;k A

● bZ&yfuZax lksY;w'ku iQ+kWj ,fxzdYpjy ,T;wds'ku ;wftax ewMy(eksM~;wyj vkWctsDV vksfj,UVsM Mk;usfed yfuZaax ,uok;ZuesUV)esa Ñf"k lkaf[;dh ds vUrxZr ¶,yhesUVªh LVSfVfLVdy esFkM~l¸rFkk lax.kd vuqç;ksx ds vUrxZr ¶iQ.MkesaVYl vkWiQ+ dEI;wVlZ,s.M izksxzkfeax¸ ikB~;Øe rS;kj fd;s x;s A

laLFkku ds oSKkfudksas }kjk jk"Vªh; ,oa vUrjjk"Vªh; Lrj ds tuZyksa esadqy 61 'kks/ i=k] 04 yksdfç; ys[k] 06 iqLrd vè;k;] 24ifj;kstuk@rduhdh fjiksVsZa@lanHkZ eSuqvYl] 03 iSE+IkQysV vkSj 04dk;Z'kkykvksa ds dk;Zo`Rr çdkf'kr fd;s x;sA Ñf"k vuqla/ku MkVkiqfLrdk 2009 çdkf'kr dh x;h tks Ja[kyk dh 13oha dM+h gS A

MkW- gqdqe pUnz dks bUVjus'kuy ,slksfl,'ku vkWiQ+ losZ LVsfVf'k;Ul}kjk dksdjku gulsu iqjLdkj 2009 iznku fd;k x;k A

MkW- ,-ds- of'k"B dks 11&12 flrEcj 2009 ds nkSjku ikf.Mpsjh]fo'ofo|ky;] iqMqpsjh esa vk;ksftr jk"Vªh; Lrjh; dk;Z'kkyk ,oalsfeukj ds nkSjku Js"B 'kks/ i=k iqjLdkj çnku fd;k x;k A

MkW- fgeknzh ?kks"k dks 30 fnlEcj 2009 ls 02 tuojh 2010 dsnkSjku gSnjkckn fo'ofo|ky;] gSnjkckn esa vk;ksftr iQjfUV;j vkWIkQbUVjIkQsl fcVohu LVsV~fVLdl ,s.M lkbfUlt vUrjjk"Vªh; lEesyuesa Js"B iksLVj çLrqfr ds fy, Jherh HkkxZoh ,oa çks- lh-vkj- jkoiqjLdkj çnku fd;k x;kA

MkW- ,-ds- xqIrk dks 20 ekpZ 2010 dks MkW- okbZ-,l- ijekj ckxokuh,oa Ñf"k okfudh fo'ofo|ky;] ukSuh] lksyu (fg-ç) esa vk;ksftrus'kuy flEiksft;e vkWu ykbiQLVkby ÝyksjhdYpj& pSysatsl ,s.MviksjP;qfuVht esa ekSf[kd çLrqfr ds fy, r`rh; iqjLdkj çnkufd;k x;k A

xsgw¡ iQly çcU/u fo'ks"kK ra=k dks Js"B bZ&dkWUVsUV ,oa Js"BbZ&yfuZax lksY;w'ku ds fy, esUFku iqjLdkj nf{k.k ,f'k;k & 2009çnku fd;k x;k A

laLFkku ds oSKkfudksa dks vusd jk"Vªh;@vUrjjk"Vªh; lEesyuksa esa'kks/&i=k çLrqr djus ds fy, çfrfu;qDr fd;k x;k A

bl o"kZ fuEufyf[kr 11 çf'k{k.k dk;ZØe vk;ksftr fd;s x;sftlesa 182 çfrHkkfx;ksa dks çf'k{k.k fn;k x;k A& mPp ladk; çf'k{k.k dsUnz ds vUrxZr Ñf"k esa lwpuk

izcU/u gsrq osc izkS|ksfxfd;ksa esa uohure mUufr ij ,d 21f}olh; izf'k{k.k dk;ZØe A

& tSolwpuk ,oa lkaf[;dh; thuksfeDl ij ,d 'khrdkyhuLdwy A

& rhu vUrjjk"Vªh; çf'k{k.k dk;ZØe&(i) rk'kdan esa lh-,-lh-deZpkfj;ksa ds fy, ijh{k.kkRed vfHkdYiuk,¡ ,oa vk¡dM+ksa dkfo'ys"k.k (ii) vkbZ-lh-,-vkj-Mh-,-] ,fyIiks] flfj;k esavfHkdYiuk ijh{k.kksa ds fo'ys"k.k ds fodkl ,oa (iii) ,izQks,f'k;u :jy fMosYiesUV vkWxZukbts+'ku }kjk izk;ksftr &Ñf"k&losZ{k.kksa esa lqnwj laosnu ,oa th-vkbZ-,l- dk vuqiz;ksxA

& Hkkjrh; lkaf[;dh lsok (vkbZ-,l-,l-) ds XXIX cSp dsifjoh{kk/hu vf/dkfj;ksa ds fy, dsUnzh; lkaf[;dh; laxBu}kjk çk;ksftr ^MkVk ,ukfyfll fon LVSfVfLVdy VwYl* fo"k;ij ,d 26 fnolh; çf'k{k.k dk;ZØeA

& pkj iqu'p;kZ ikB~;Øe (i) lsokdkyhu Hkkjrh; lkaf[;dh;lsok vf/dkfj;ksa ,oa jkT; ljdkj@dsUæ 'kkflr izns'kksa dsofj"B vf/dkfj;ksa@lh-,l-vks- ds fy, lkaf[;dh; lax.kuk ,oavk¡dM+kas ds çlkj dh rduhdksa esa lwpuk izkS|ksfxdh dk vuqiz;ksx(ii) Hkkjrh; lkaf[;dh lsokvksa ,oa jkT; ds vU; ofj"B vf/dkfj;ksa ds fy, y?kq {ks=k vkdyu rduhdsa (iii) Hkkjrh;lkaf[;dh lsok ds 12 vf/dkfj;ksa ,oa lkaf[;dh; dfeZdksa dsfy, dsUnzh; lkaf[;dh; laxBu] lkaf[;dh; ,oa dk;ZØedk;kZUo;u ea=kky;] Hkkjr ljdkj }kjk çk;ksftr vkf/dkfjdvk¡dM+ksa ds fy, vuqla/ku rFkk (iv) jkT;ksa@dsUæ 'kkflrizns'kksa@lkaf[;dh ,oa dk;ZØe dk;kZUo;u ea=kky;] Hkkjr ljdkjds ih-,l-;w- ds lkaf[;dhs; dkfeZdksa ds fy, Hkkjr esa Ñf"klkaf[;dh ç.kkyh A

Hkk-Ñ-v-i- eq[;ky; ds vf/dkfj;ksa ds fy, foRr lEcU/h ekeyksaij ,d fo'ks"k çf'k{k.k dk;ZØe A

vkpk;Z ,u th- jaxk Ñf"k fo'ofo|ky;] jktsUnz uxj] gSnjkckn rFkkmlds dsUnzksa ij ijh{k.k vfHkdYiukvksa esa ,Mokaflt ij rhu ;k=kkizf'k{k.k dk;ZØe vk;ksftr fd, x, ftuesa 245 'kks/dÙkkvksa usizfrHkkfxrk dhA

laLFkku ds Lo.kZ t;Urh lekjksg ds vk;kstu ds nkSjku 05 çlkjdk;Z'kkyk,¡ vk;ksftr dh x;ha%

& ijh{k.k vfHkdYiuk

& y?kq {ks=k vkdyu rduhdksa dk ç;ksx

& Ñf"k esa fo'ks"kK ra=k

& Ñf"k esa fMlhtu liksVZ ds fy, lqnwj laosnu ,oa HkkSxksfydlwpuk i¼fr

& thuksfeDl esa lkaf[;dh; ,oa lax.kukRed eqn~ns

nl vU; laxksf"B;k¡] dk;Z'kkyk,¡@O;k[;ku l=k] vUrjjkZ"Vªh; lEesyuksads nkSjku fo'ks"k vkeaf=kr okrkZ,¡ vk;ksftr dh x;haA

Ñ"kh; tSo&lwpuk dsUnz dh LFkkiuk ij nks cszuLVkfeZax l=k vk;ksftrfd, x,A

laLFkku dh f'k{k.k ,oa çf'k{k.k lEcU/h xfrfof/;k¡] ftuesa leLrLukrdksRrj vè;kiu dk;ZØeksa dk fu;kstu] vk;kstu ,oa leUo;u'kkfey gS] Hkkjrh; Ñf"k vuqla/kku laLFkku ds LukrdksRrj Ldwy dslg;ksx ls pyk;h x;ha A bl o"kZ dqy 16 Nk=kksa 03 ih,p-Mh-(Ñf"k lkaf[;dh)] 05 ,e-,llh- (Ñf"k lkaf[;dh) ,oa 08,e-,llh- (lax.kd vuqç;ksx) us viuk fMxzh ikB~;Øe iwjkfd;k A 23 u;s Nk=kksa 07 ih,p-Mh- (Ñf"k lkaf[;dh)] 08,e-,llh- (Ñf"k lkaf[;dh) ,oa 08 ,e-,llh- (lax.kd vuqç;ksx)dks ços'k fn;k x;k A

Hkkjr ,oa n{ksl ns'kk s a lfgr vU; fons'kk s a ds vuqla/kkulaLFkkuksa@fo'ofo|ky;ksa esa lkaf[;dh; vk¡dM+ksa ds ladyu] fo'ys"k.k,oa foospu ds dk;ksZa esa yxs 'kks/drkZvksa ds ykHkkFkZ ¶Ñf"k lkaf[;dh,oa lax.kd¸ esa ,d mPp çek.k&i=k ikB~;Øe vk;ksftr fd;kx;k A bl çek.k&i=k ikB~;Øe esa lkr vf/dkfj;ksa us lgHkkfxrkdh A

fgUnh dks çksRlkgu nsus ds fy, laLFkku esa ,d 'kks/&i=k&iksLVj&çn'kZuçfr;ksfxrk vk;ksftr dh x;h ftlesa fgUnh iksLVj rS;kj djus esamYys[kuh; ;ksxnku nsus okys dfeZ;ksa dks iqjLÑr fd;k x;k A

laLFkku dk iqLrdky; jk"Vªh; Ñf"k vuqla/kku ç.kkyh (NARS)ds vUrxZr ns'k dk ,d {ks=kh; iqLrdky; gS tks laLFkku dsç;ksDrkvksa ds lkFk&lkFk vU; vuqla/ku laxBuksa ds ç;ksDrkvksa dhlwpuk lEcU/h vko';drkvksa dks iwjk djus esa egRoiw.kZ HkwfedkfuHkk jgk gS A

Executive Summary

Indian Agricultural Statistics Research Institute (IASRI)established in 1959 as an Institute of AgriculturalResearch Statistics is mainly responsible for conductingresearch and education/training in Agricultural Statistics.With the advances in information technology, the Institutehas adapted itself to the current needs of agriculturalresearch. In the changed scenario, the mandate of theInstitute is to undertake basic, applied and adaptiveresearch in Agricultural Statistics, to conduct postgraduate and in-service training courses in AgriculturalStatistics and Computer Applications, to provideconsultancy services, to act as a repository of informationon Agricultural Statistics for research, to develop theInstitute as an Advanced Centre of Excellence ineducation and training in Agricultural Statistics andComputer Applications and to liaise with other ICARInstitutes and SAUs, State Agricultural/AnimalHusbandry Departments, to assist in the developmentand strengthening of National Agricultural StatisticsSystem and to undertake sponsored research and

training of national and international organisations inthese disciplines.

A number of research projects were undertaken during theyear in different Divisions of the Institute namely SampleSurvey, Design of Experiments, Biometrics, ForecastingTechniques, Econometrics and Computer Applications.Research was carried out under 50 research projects inthe Institute, of which 01 National Professor Scheme, 30Institute funded, 05 NAIP funded, 01 AP Cess funded,04 funded by other outside agencies and 09 incollaboration with other Institutes in various thrust areas.This year 12 projects were completed, 06 new projects wereinitiated and one project of ad-hoc nature was initiated andcompleted as well.

Some of the salient research achievements are:

● For the experimental situations in which the numberof experimental units is less than the number ofparameters to be estimated, efficient mixed-level

2

Executive Summary

supersaturated designs (SSDs) have beengenerated by juxtaposing a uniform design with aHadamard matrix. E(s2)-optimal two-level SSDshave been extended by adding more runs to thedesign. The extended design is also E(s2)-optimalaccording to the new lower bound obtained.

● The Design Resources Server has beenstrengthened by adding SAS and SPSS steps andsyntax for (i) fitting of non-linear models and(ii) performing cluster analysis. A link on StatisticalGenomics, essentially as an e-learning platform forthe researchers particularly the geneticists, thebiologists, the statisticians and the computationalbiology experts has been created. Another link forblock designs with factorial structure has also beenadded. During the year, google analytics gave 5392page views and usage of the server through 448cities across 78 countries.

● For detecting t outlier observation vectors in multi-response experiments, general expression of Cookstatistic has been obtained.

● Two methods of construction of designs for mixtureexperiments with process variables have beendeveloped using orthogonally blocked responsesurface designs and projection matrices. Thedesigns for mixture experiments with processvariables obtainable from these methods ofconstruction have been catalogued for both Linearand Quadratic models for 2-5 mixture componentsand one process variable with 2-levels.

● A series of designs involving sequences of treatmentsfor comparing two disjoint sets of treatments has beenobtained and variance of contrasts pertaining to directas well as residual effects of test versus test, testversus control and control versus control treatmentshas also been obtained.

● For the experimental situations whereinexperimental units are used for a series of tasksone after another in the experimental conditionswhose levels are difficult to change, two classes ofnested designs involving sequences of treatmentswith same number of experimental periods andunits have been obtained.

● A method of construction of second order rotatableresponse surface designs in the presence ofneighbour effects has been developed.

● The concept of Neighbour Balanced Block (NBB)designs has been defined for the experimental

situation where the treatments are the combinationsof levels of two factors and only one of the factorexhibits neighbour effect. Some methods ofconstructing complete NBB designs for two factorsin a plot strongly neighbour balanced for one factorhas been obtained.

● Two three-class association schemes calledtetrahedral association scheme and cubicalassociation scheme have been defined along withmethods of constructing partially balanced incompleteblock designs.

● A module for online analysis of data generatedthrough a general block design has been developedand uploaded on the home page of the Institute.

● A linear integer programming approach has beendeveloped for obtaining polygonal designs for givennumber of treatments v, block size k, concurrenceof treatments separated by a distance of m + 1 ormore as λ and all other concurrences as zero,

⎥⎦⎤

⎢⎣⎡≤2

vm , here [.] denotes the greatest integer

function. These designs are useful for obtainingbalanced sampling plans.

● Fertilizer Response Ratio (FRR), average increaseof grain yield in kilogram of a crop due to perkilogram use of fertilizer nutrient of 14 crops (5cereals, 4 pulses, 5 oilseeds) at NARP zone level,state level and all India level have been obtainedusing the data from On-farm trials. The fertilizerresponse ratios of N over control are 9.20, 7.73and 8.51 kg/kg for cereals, oilseeds and pulse groupwhereas these value of NPK over control are 10.80,5.60 and 6.70 kg/kg respectively. The fertilizerresponse ratio for all foodgrain crops for NPK overcontrol is observed as 9.27 kg/kg which is morethan response observed for N, NP, NK over control.

● Crop yield forecast models have been developedusing rice, wheat and sugarcane yields as responsevariable and weather variables as input variablesusing multi-layer perceptron (MLP) and radial basisfunction (RBF) based neural networks with one ortwo hidden layers.

● Disease forewarning models using MLP and RBFbased neural networks are developed for AlternariaBlight and Powdery Mildew in mustard crop usingweather variables as input variables.

● Weather based models for forecasting potato yieldin Uttar Pradesh have been developed by using

3

Executive Summary

weather data on maximum and minimumtemperature and morning and evening relativehumidity during the period 1971-2002.

● For fitting of non-parametric functionalautoregressive models, the coefficient functionshave been estimated using Taylor ’s seriesexpansion in which unknown coefficients areestimated by the method of weighted least squares,weights being the kernel density function.The applicability of self-exciting thresholdautoregressive (SETAR) family of non-linear timeseries models with more than one threshold isdemonstrated in the field of agriculture, having timeseries data that depicts cyclical patterns.

● For multimodal rainfall data, methodology of fittingmixture of distributions to ‘body’ and ‘tail’ usingstatistical learning theory is demonstrated. Threeestimators of extreme value index are computed to fitthe theoretical tail distribution to the rainfall data.

● Spatial market integration has been studied usingadvanced econometric tools namely AugumentedDickey Fuller technique for testing stationarity oftime series, Johansen’s Co-integration method forfinding the co-integrating vectors and Vector ErrorCorrection mechanism for finding out the speed ofadjustment of price series to equilibrium for wholesale market of important cereals (rice, wheat, jowar,bajra, maize), oilseeds (ground nut, mustard),edible oils (coconut oil, ground nut oil, mustard oil)and pulses (gram, moong, arhar, urd, etc.) usingtime series data on wholesale prices. The analysisrevealed that the integration among the marketshas improved over the recent years. The prices ofagricultural commodities tend to converge amonga few selected state-level wholesale markets in India.

● In the area of futures trading, price volatility, pricediscovery and risk management are studied forimportant crops, and the contract designs of Indianwheat and maize crops are compared with UScontracts. The volatility of futures market is greaterthan the spot market volatility.

● Multidimensional scaling (MDS) approach is usedfor identifying the factors contributing towardsenhancing agricultural productivity pertaining to thesubdomain “Plant Genetics and Breeding”. It isfound that India is focusing not only on abiotic andbiotic stresses but also on evolving areas such asbioinformatics, molecular assisted selection,transgenics, etc.

● Estimators of both domain and population totals foran item of interest are developed under two-phasesampling where the domain identity is realized, butthe item response is not necessarily available froma phase I sampled unit.

● An approximately unbiased estimator of thevariance of ratio estimator under the two-phasesampling has been developed.

● Small Area Estimation (SAE) that accounts forpresence of excess zeros in the data has beendeveloped using the mixture model (a combinationof linear mixed model and generalized linear mixedmodel). This proposed approach works in threesteps. Firstly, a linear mixed model is fitted forpositive values of the variable and then at thesecond step, a generalized linear mixed model isfitted for probability of positive values. Finally, thetwo models are combined at estimation stage.

● For situations in which the variable of interest isnegatively correlated with sizes of units, the conceptof inclusion probability inversely proportional to sizesampling (IPIPS) scheme is introduced. IPIPSscheme ensures that the first order inclusionprobabilities of units are inversely proportional tosize measures of the units.

● For computational analysis of SNPs in ricegenome, a web based information system onfunctional elements of rice genome has beendeveloped. Online facilities have been created toaccess the information on Single NucleotidePolymorphisms (SNPs) at functional elements.Web information system on rice functional elementshelp facilitate users to extract sequence informationon promoter regions, untranslated regions,translation start sites, splice sites, exons, introns,translation stop sites, etc. Information onclassification of splice sites, position weightmatrices, phylogenetic relationships etc. is alsoprovided in the Splice Store.

● The variety selection and disease diagnosticmodules of the expert system on wheat cropmanagement have been developed in Hindi usingSQL server that accepts UNICODE for the supportof Hindi language.

● In presence of outliers, it is seen that the estimatesof genetic correlation are highly under estimatedwith the result that the bias increases considerably.The standard error in the presence of outliers alsoincreases considerably.

4

Executive Summary

● A β−version of Statistical Package for AnimalBreeding (SPAB 2.1) has been developed. Thepackage is quite useful for animal breeders forestimation of genetic parameters and forformulating sound breeding strategies and selectionprocesses.

● In knowledge data warehouse for agriculturalresearch, multidimensional model for the IntegratedData Mart has been designed. Models have beendeveloped and implemented for on-line analysisand prediction/forecasting based on time seriesdata to different data marts. Three types of modelsi.e. trend, growth, and auto regression areincorporated for this on-line prediction.

● Decision support system for manpowerplanning (PERMISnet-II) has been implementedin ICAR from IASRI server at the URLhttp://permisnet.iasri.res.in.

● Developed an online management system for PGSchool, IARI, New Delhi. It has five modules formanagement of courses, students, faculty,administration and e-learning. At present the systemhas 267 registered students and 412 facultymembers. The system has 536 courses listed in 23disciplines. All the students have been registeredonline for I, II trimesters of academic year 2009-10.

● In the e-Learning solution for agricultural educationusing MOODLE (Modular Object Oriented DynamicLearning Environment), the courses “ElementaryStatistical Methods” under the discipline ofAgricultural Statistics and “Fundamentals ofComputers and Programming” under the disciplineof Computer Applications have been prepared.

Scientists of the Institute published 61 research papersin National and International refereed Journals alongwith 24 popular articles, 06 book chapters, 24 projects/technical reports/reference manuals, 03 pamphlets and04 workshops proceedings. The Agricultural ResearchData Book 2009 which is thirteenth in the series hasbeen published.

Dr. Hukum Chandra received Cochran-Hansen Prize 2009from International Association of Survey Statisticians.

Dr. AK Vasisht received the Best Research PaperAward during national level Workshop-cum-Seminarheld at Pondicherry University, Puducherry during11-12 September 2009.

Dr. Himadri Ghosh received Mrs. Bhargavi andProfessor CR Rao Award for Best Poster Presentationduring International Conference on Frontiers ofInterface between Statistics and Sciences held atUniversity of Hyderabad, Hyderabad during 30December 2009 to 02 January 2010.

Dr. AK Gupta received III prize for oral presentationduring the National Symposium on Lifestyle Floriculture:Challenges and Opportunities held at Dr.YS ParmarUniversity of Horticulture and Forestry, Nauni, Solan(HP) on 20 March 2010.

Expert System on Wheat Crop Mangement receivedManthan Award South Asia 2009 for best e-content andbest e-learning solution.

Scientists of the Institute were deputed for presentationof their papers in several National/Internationalconferences.

This year following eleven training programmes wereorganized in which 182 participants were impartedtraining

– A twenty one days training programme underCentre of Advanced Faculty Training on RecentAdvances in Web Technologies for InformationManagement in Agriculture.

– Winter School on Bioinformatics and StatisticalGenomics.

– Three International training programme on(i) Experimental Designs and Data Analysis forthe CAC Staff at Tashkent, (ii) Advances inDesign and Analysis of Experiments at ICARDAAleppo, Syria and (iii) Applications of RemoteSensing and GIS in Agricultural Surveyssponsored by Afro Asian Rural DevelopmentOrganization at the Institute.

– CSO Sponsored 26 days training programme onData Analysis with Statistical Tools for IndianStatistical Service (ISS) Probationers of XXIXbatch.

– Four refresher training programmes on(i) Applications of Information Technology inStatistical Computing and Data DisseminationTechniques for in-service ISS officers and seniorofficers of State Governments/UT (ii) Small AreaEstimation for the Indian Statistical Services andother senior officers of States/Union Territories

,

5

Executive Summary

(iii) Research Methodology for Official Statisticsfor twelve ISS officers and statistical personneland (iv) Agricultural Statistical System in India forstatistical personnel of States/UTs/PSUs of CSO.

– One special training programme on financialmatters for the officials of ICAR Hqrs.

● Three Travel Training programmes on Advances inDesign of Experiments were organized for thescientists of Acharya NG Ranga AgriculturalUniversity, Rajendra Nagar, Hyderabad and itscentres and 245 researchers were sensitized.

● 05 Dissemination workshops as part of GoldenJubilee celebrations of the Institute were organized

– Design of Experiments

– Applications of Small Area EstimationTechniques

– Expert Systems in Agriculture

– Remote Sensing and GIS for Decision Supportin Agriculture

– Statistical and Computational Issues inGenomics

● Ten other Symposium/Workshop/lecture sessions/special invited talks during International Conferencewere organised.

● Two Brainstorming Sessions on Establishment ofCentre of Agricultutal Bioinformatics were organised.

The activities relating to education and trainingwhich include planning, organization and coordinationof the entire Post-graduate teaching programmes ofthe Institute were undertaken in collaboration with PGSchool, IARI. During the year, a total of 16 students,03 Ph.D. (Agricultural Statistics), 05 M.Sc. (AgriculturalStatistics) and 08 M.Sc. (Computer Application)completed their degrees. 23 new students 07 Ph.D.(Agricultural Statistics), 08 M.Sc. (AgriculturalStatistics) and 08 M.Sc. (Computer Application) wereadmitted.

A Senior Certificate Course in Agricultural Statistics andComputing was organised. Seven officials participatedin this Certificate Course.

To promote Hindi, a poster presentation was organizedat the Institute and awards were distributed for theoutstanding performances.

The Library of the Institute with a status of RegionalLibrary under NARS, played a vital role in meeting theinformation needs of the in-house users as well as usersfrom other research organisations.

Indian Agricultural Statistics Research Institute (IASRI)has been and continues to be a premier Institute of theIndian Council of Agricultural Research (ICAR) withglorious tradition of carrying out research, teaching andtraining in the areas of Agricultural Statistics andComputer Application. Recognizing the importance ofresearch and education in Agricultural Statistics wayback in 1930, the then Imperial Council of AgriculturalResearch established a small Statistical Section toassist the State Departments of Agriculture and AnimalHusbandry in planning and designing their experiments,analysis of experimental data, interpretation of results,and also rendering advice on the formulation of thetechnical programmes and examining the progressreports of the schemes funded by the Council. Theactivities of the Section increased rapidly with theappointment of Dr. PV Sukhatme as Statistician to theCouncil in 1940 and studies were initiated fordeveloping objective and reliable methods for collectingyield statistics of principal food crops. The efficiencyand practicability of these methods was demonstrated

in different States for estimating crop yield. As a result,in the course of a few years, the method was extendedpractically to the entire country to cover all principalfood and non-food crops. Research in sampling theoryand training of field staff and statistical staff were theactivities initiated in this period resulting in the re-organization of the Statistical Section into a StatisticalBranch in 1945 with appropriate expansion in itsstrength. The designation of Statistician was changedto Statistical Advisor. The Statistical Branch wasrenamed as Statistical Wing in 1949. The StatisticalWing soon acquired International recognition as acentre for research and training in the field ofAgricultural Statistics. During 1952 on therecommendations of two FAO experts, Dr. Frank Yatesand Dr. DJ Finney, who visited the Council on theinvitation of the Government of India, activities of theStatistical Wing were further expanded and diversified.Subsequently, in recognition of its important role as atraining and research institution, the Statistical Wingwas re-designated as the Institute of Agricultural

Introduction

8

Introduction

Research Statistics (IARS) on 02 July 1959. In April1970, the Institute was declared as a full-fledgedInstitute in the ICAR system and is since then headedby a Director. On 01 January 1978 the name of theInstitute was changed to Indian Agricultural StatisticsResearch Institute (IASRI) emphasizing the role of‘Agricultural Statistics’ as a full-fledged discipline byitself.

The Goal of the Institute is to conduct research,education and training in Agricultural Statistics andComputer Applications in Agriculture. The vision of theinstitute is to use the power of Statistics as a scienceblended judiciously with information communicationtechnology to enhance the quality of agriculturalresearch. To convert this vision into a reality, the Institutehas set for itself a mission to undertake research,teaching and training in Agricultural Statistics andComputer Applications so that these efforts culminateinto improved quality of agricultural research and alsomeet the challenges of agricultural research in neweremerging areas. The functions and activities of theInstitute have been re-defined from time to time in thepast. The present main thrust of the Institute is toconduct basic, applied, adaptive, strategic andanticipatory research in Agricultural Statistics, todevelop trained manpower and to disseminateknowledge and information produced so as to meetthe methodological challenges of agricultural researchin the country.

The Institute has made its presence felt in the NationalAgricultural Research System (NARS). The Institute isalso becoming progressively a repository of informationon agricultural research data and has taken a lead inthe country in developing a data warehouse onagricultural research data. The Institute also occupiesa place of pride in the National Agricultural StatisticsSystem (NASS) and has made several importantcontributions in the strengthening NASS, which has adirect impact on the national policies. Some of theresearch activities and their impact are given in thesequel:

Research Achievements and Impact

The Institute has made some outstanding and usefulcontributions to the research in Agricultural Statisticsin the fields like Design of Experiments, StatisticalGenetics, Forecasting Techniques, Statistical Modelling,

Sample Surveys, Econometrics, Computer Applicationsin Agriculture, Software Development, etc. IASRI hasconducted basic and original research on many topicsof interest and has published number of papers innational and international journals of repute. IASRI hasbeen providing and continues to provide support to theNARS by way of analyzing voluminous data usingadvanced and appropriate analytical techniques. IASRIhas also been very actively pursuing advisory servicesthat has enabled the Institute to enrich the quality ofagricultural research in the NARS. Through its advisory,IASRI has made its presence visibly felt in NARS andnow experimenters look to IASRI for designingexperiments and analysis of experimental data.

The efficient designs like balanced incomplete blockdesigns, group divisible and extended group divisibledesigns, reinforced extended group divisible designs,square and rectangular lattice designs, α-designs,reinforced α-designs, augmented designs, designs forfitting response surfaces, etc. and advanced analyticaltechniques including contrast analysis, linear modelswith nested structures, experiments with mixturesmethodology, mixed effects models, biplot, etc. havebeen adopted by the experimenters in NARS. Theapplication of α-designs and resolvable block designshas improved the precision of treatment comparison inCrop Improvement programmes of Rapeseed andMustard, Sorghum, etc. The analytical techniques forestimating/projecting the Energy Requirement in theAgricultural Sector has been exploited for the analysisof countrywide data. The analytical techniques for theanalysis of data from the experiments conducted tostudy the post harvest storage behaviour of theperishable commodities like fruits and vegetables arebeing widely used in NARS. The Institute works in closecollaboration with NARS organizations and manyprojects are being run at the Institute in collaborationwith All India Co-ordinated Research Projects and ICARInstitutes. Institute has developed linkages with theCGIAR organizations such as CIMMYT, IRRI andICARDA. The status of experimentation is nowchanging and with the support provided in terms ofsuggesting efficient designs and analyzing the datausing modern complicated statistical tools, the researchpublications of the agricultural scientists are finding aplace in high impact factor international journals.

The methodology for General Crop Estimation Surveys(GCES), cost of cultivation studies, Integrated Sample

9

Introduction

Surveys (ISS) for livestock product estimation, fruitsand vegetable survey, which are being adoptedthroughout the country are research efforts of IASRI.Methodology based on small area estimation techniquefor National Agricultural Insurance Scheme suggestedby IASRI has been pilot tested in the country. A statuspaper on chronological development and present statusof information support system for management ofagriculture was prepared as a part of State of IndianFarmer: A Millennium Study of Ministry of Agriculture.The sample survey methodology for imported fertilizerquality assessment, fish resources estimation, flowerproduction estimation, area and production ofhorticultural crops estimation, etc. have been developedand passed on to the user agencies. Integratedmethodology for estimation of multiple crop area ofdifferent crops in North Eastern Hilly Regions usingRemote Sensing data has been developed. Samplingmethodology for estimation of post harvest losses hasbeen successfully adopted in AICRP on Post HarvestTechnology for assessment of post harvest losses ofcrops/commodities

The Institute has also made very significantcontributions in developing the analytical techniquesfor the estimation of genetic parameters, models forpre-harvest forecasting of crop yields, models forforewarning of incidence of pests and diseases andeconometrics and statistical modeling of biologicalphenomena using non-linear models, non-parametricregression, structural time series, neural network andmachine learning approaches. The techniquesdeveloped have potential applications in long termprojections of food grain production, aphid population,marine fish production, etc. The methodologydeveloped for forecasting based on weather variablesand agricultural inputs was used by Space ApplicationCentre, Ahmedabad, to obtain forecast of wheat yieldat national level. Models developed for forewarning ofaphids in mustard crop were used by National ResearchCentre for Rapeseed and Mustard to provideforewarning to farmers which enabled them to optimizeplant protection measures and save resources onunnecessary sprays consecutively for three years. Themodification in the procedure of estimation of geneticparameters has been suggested for incorporating theeffect of unbalancedness, presence of outliers, aberrantobservations and non-normality of data sets.Procedures for studying genotype × environment

interactions have been developed and used for theanalysis of data generated from crop improvementprogrammes. The research work on construction ofselection indices and progeny testing and sireevaluation have been used for animal improvementprogrammes. The Institute has now initiated researchin the newer emerging area of statistical genomics.

Achievements in Information CommunicationTechnology

The Institute has the capability of development ofInformation Systems, Decision Support Systems andExpert Systems. Realizing the need of integration ofdatabases to prepare a comprehensive knowledgewarehouse that can provide desired information in timeto the planners, decision-makers and developmentalagencies, Integrated National Agricultural ResourcesInformation System (INARIS) with the active supportof 13 sister institutes as partners has been developed.The data warehouse comprises of 59 databases onagricultural technologies of different sectors ofagriculture and related agricultural statistics at districts/state/national levels, population census including villagelevel population data as well as tehsil level householdassets and livestock census. Subject-wise data martshave been designed, multi-dimensional data cubesdeveloped and published in the form of on-line decisionsupport system. The Institute has also developedinformation systems for agricultural field experiments,animal experiments and long term fertilizer experimentsconducted in NARS. Besides, a comprehensivePersonnel Management Information System Network(PERMISnet) has been implemented for the ICAR formanpower planning, administrative decision making,and monitoring. For National Agricultural TechnologyProject, a Project Information and Management SystemNetwork (PIMSnet) was developed and implementedfor concurrent monitoring and evaluation of 845projects. A National Information System on AgriculturalEducation Network in India (NISAGENET) has beendesigned, developed and implemented so as tomaintain and update the data regularly on parametersrelated to agricultural education in India. OnlineManagement System for PG School, IARI hasbeen developed. An Expert System on Wheat CropManagement has also been developed and implemented.

A milestone in the research programmes of the Institutewas created when it started developing indigenous

10

Introduction

statistical software packages mainly for analysis ofagricultural research and animal breeding data.Statistical packages for generation of experimentaldesigns for various experimental situations, bothunstructured and factorial structure of treatments,catalogues of designs, randomized layout of design andanalysis of data were also developed. Statisticalpackages developed and widely being used in NARSare:

- Statistical Package for Agricultural Research(SPAR) 2.0

- Statistical Package for Block Designs (SPBD) 1.0- Statistical Package for Factorial Experiments

(SPFE) 1.0- Statistical Package for Augmented Designs

(SPAD) 1.0- Software for Survey Data Analysis (SSDA) 1.0

- Statistical Package for Animal Breeding (SPAB)2.1

The creation of Design Resources Server, an e-learningand e-advisory resource for the experimenters, hasbeen another revolution in the growth of the Institute.The server provides a platform to popularize anddisseminate research and also to further strengthenresearch in newer emerging areas in design ofexperiments among peers over the globe in generaland among the agricultural scientists in particular soas to meet the emerging challenges of agriculturalresearch. This server is hosted at www.iasri.res.in/design.

Achievements in Human Resource Development

The one of the thrust areas of the Institute is to developtrained manpower in the country in the disciplines ofAgricultural Statistics and Computer Applications formeeting the challenges of Agricultural Research in thenewer emerging areas. A humble beginning in the areaof development of trained manpower was made in 1945with the initiation of two regular certificate courses, onecourse of six months duration, called Junior CertificateCourse (JCC) and the other course of one year durationcalled Senior Certificate Course (SCC). Besides, therewas another course of one year duration known asProfessional Statisticians’ Certificate Course (PSCC)that was introduced to train professional statisticians.Subsequently, a Diploma course involving a researchproject of one year duration, in addition to PSCCconsisting of one year course work in advanced

statistics, was also introduced. This necessitated theaugmentation of the staff and accordingly, the strengthof the branch was increased to two Professors ofStatistics and other staff. These certificate courseshelped in strengthening the linkages of the Institute withthe State Departments of Agriculture and AnimalHusbandry. The certificate courses started in 1945 werediscontinued by the Indian Council of AgriculturalResearch (ICAR) in 1985-86. However, during 1997,the Senior Certificate Course in Agricultural Statisticsand Computing was revived. This course is now of sixmonths duration and lays more emphasis on statisticalcomputing using statistical softwares. The course isdivided into two modules viz. (i) Statistical Methods andOfficial Agricultural Statistics, and (ii) Use of Computersin Agricultural Research, of three months duration each,77 participants have completed both modules, 21 havecompleted module-I and 12 have completed module-IIsince 1997.

The year 1964 witnessed tremendous changes in theactivities of the Institute when an memorandum ofunderstanding was signed with Indian AgriculturalResearch Institute (IARI), New Delhi to start new degreecourses leading to M.Sc. and Ph.D. in AgriculturalStatistics. In 1981, a two years Diploma Course inAdvanced Computer Programming was introduced. Onthe recommendations of UNDP, this course was soondiscontinued and in 1985 another new course leadingto an M.Sc. degree in Computer Applications inAgriculture was initiated in collaboration with IARI, NewDelhi. This course was re-designated as M.Sc. degreein Computer Application during 1993-94. The Institutehas so far produced 176 Ph.D. and 292 M.Sc. studentsin Agricultural Statistics and 89 M.Sc. students inComputer Application. The alumni of the Institute areat present occupying high positions in Universities andother academic research institutions of USA, Canadaand other countries.

The functioning of the Institute as a Centre of AdvancedStudies in Agricultural Statistics and ComputerApplication during October 1983 to March 1992 underthe aegis of United Nations Development Programmewas another landmark in the history of the Institute.The purpose of this programme was to develop theInstitute as a centre of excellence with adequateinfrastructure and facilities to undertake advancedtraining programmes and to carry out research invarious emerging areas of Agricultural Statistics and

11

Introduction

Computer Application. Under this programme, anumber of illustrious statisticians and computerscientists from abroad visited the Institute with a viewto interacting with the scientists, giving seminars/lectures and suggesting gaps in the researchprogrammes of the Institute. Under the programmesome scientists of the Institute received training forcapacity building from abroad. Another singulardevelopment in the growth of the Institute was theCentre of Advanced Studies programme in AgriculturalStatistics and Computer Application established duringthe VIII Five Year Plan in 1995. Under this program theinstitute organizes training programmes on varioustopics of current interest for the benefit of scientists ofNARS. These training programmes cover specializedtopics of current interest in statistics and agriculturalsciences. During the period under report the Centre ofAdvanced Studies (CAS) is renamed as Centre ofAdvanced Faculty Training (CAFT). So far 44 trainingprogrammes have been organised under the aegis ofCentre of Advanced Faculty Training. In all a total of781 participants have been benefited.

There is yet another form of training courses, whichare tailor made courses and are demand driven. Thecoverage in these courses is need based and thecourses are organized for specific organizations fromwhere the demand is received. The Institute hasconducted such programmes for Indian Council ofForestry Research, Indian Statistical Servicesprobationers and Senior officers of Central StatisticalOrganization and many other organizations. TheInstitute has also conducted several internationaltraining programmes on request from FAO, particularlyfor African, Asian and Latin American countries. TheInstitute has broadened the horizon of capacity buildingby opening its doors to the agro-based private sector.One such training programme was organized forresearch personnel of E.I. DuPont Pvt. Ltd. The Institutehas also conducted training programmes for thescientists/research personnel of CGIAR organizationssuch as ICARDA and Rice-Wheat Consortium for Indo-Gangetic plains. A number of research workers fromthe Institute have served as consultants and advisorsin Asian, African and Latin American countries. Also, anumber of statisticians and students of the Institute areat present occupying high positions in universities andother academic and research institutions of USA,Canada and other countries.

Infrastructural Developments

As the activities of the Institute started expanding in alldirections, the infrastructure facilities also startedexpanding. Two more buildings ‘Computer Centre’ and‘Training-cum-Administrative Block’ were constructedin the campus of the Institute in the years 1976 and1991, respectively. An important landmark in thedevelopment of the Institute was the installation of anIBM 1620 Model-II Electronic Computer in 1964. A thirdgeneration computer Burroughs B 4700 system wasinstalled in March 1977. The Burroughs B–4700 systemwas replaced in 1991 by a Super Mini COSMOS-486LAN Server with more than hundred nodes consistingof PC/AT’s, PC/XT’s and dumb terminals all in a LANenvironment. Later, COSMOS-486 LAN Server wasreplaced by a PENTIUM-90 LAN Server having state-of-art technology with UNIX operating system.Computer laboratories equipped with PCs, terminalsand printers, etc. had been set up in each of the sixScientific Divisions as well as in the AdministrativeWings of the Institute.

For undertaking research in the newer emerging areas,a laboratory on Remote Sensing (RS) and GeographicInformation System (GIS) was created in the Institute.The laboratory was equipped with latest state-of-arttechnologies like computer hardware and peripherals,Global Positioning System (GPS), softwares likeERMapper, PCARC/INFO, Microstation 95, GeomediaProfessional, ARC/INFO Workstation and ERDASImagine with the funds received through two AP CessFund projects. This computing facility has further beenstrengthened with the procurement of ARC-GISsoftware under NATP programme.

An Agricultural Bioinformatics Lab (ABL) fully equippedwith software and hardware has been created to studycrop and animal biology with the latest statistical andcomputation tools.

The LAN at IASRI has steadily been strengthened andthe Computer Centre, Sample Survey Block, Trainingand Administration Block and Panse Guest House havebeen connected using fiber optical cable as backboneand connectivity has been established for 462 nodes.The LAN is being managed using manageableswitches. Currently the internet services are beingprovided through Firewall and secure servers withmultiple CPU capabilities on a 8 Mbps bandwidth.

12

Introduction

Primary and Secondary DNS, Domain: iasri.res.in,Website (http://www.iasri.res.in) and E-mail services arebeing maintained in house. Live E-mail and Internetfacilities are being provided to the scientists/technical/administrative staff. Newly built, International TrainingHostel was Inaugurated by Hon’ble Dr. Mangala RaiSecretary, DARE & Director General, ICAR on, 09 July2009. Internet facilities at International Training Hostelis being provided on a 512 Kbps download speed usingMTNL Broadband WiFi Modem.

There are various labs at the Institute for dedicatedservices like ARIS lab for Training, Stat lab for Statisticalanalysis and Centre for Advance Study lab.

Keeping pace with the emerging technologies in thearea of Information Technology (IT), from the year 1998onwards the computer hardware and softwarehave been constantly upgraded/replaced with newerplatforms and versions. The computing environment inthe Institute has latest rack mount servers, PCs,notebook computers, laser mono & colour printers,inkjet printers, scanners, DVD duplicator, visualiser andvideo projectors. All the divisions, administrative andaccounts sections of the Institute have been providedwith PCs, printers and peripherals. Software packagesthat are needed for application development, statisticaldata analysis, network securities and office automationare being made available to the scientists and staff ofthe Institute. Some of the important softwares that areavailable are SAS, SPSS, SYSTAT, GENSTAT, Datawarehouse software – Cognos, SPSS clementine, MSOffice 2007, MS Visual Studio Dot net, Macro-Media,MS Project, E-views, Trend Micro Antivirus, NEURAL

NETWORKS (STATISTICA), Gauss Software, Minitab14, Maple 9.5, Matlab, Sigma Plot Web Statistica andLingo Super.

The Institute continued to provide selective informationdocumentation services to scientists in the ICARInstitutes and Agricultural Universities on referencesto documents relating to areas of their specific interest.The bibliographic databases in Biotechnology andAnimal Science Research are being maintained in theBio-Informatics Laboratory providing SelectiveDissemination of Information (SDI) services on VETCD,BEASTCD and AGRICOLA databases of the Food andAgriculture Organisation under United Nations.

Organisational Set-up

The Institute has following six Divisions, two Unitsand three Cells to undertake research, training,consultancy, documentation and dissemination ofscientific output.

Divisions● Sample Survey● Design of Experiments● Biometrics● Forecasting Techniques● Econometrics● Computer Applications

Units● Research Co-ordination and Management Unit

(RCMU)

● Institute Technology Management Unit (ITMU)

Staff Position (as on 31 March 2010)

Manpower No. of posts No. of postssanctioned filled

Director 1 1

Scientific 130 63

Technical 221 105

Administrative 109 96

Auxiliary 14 9

Skilled Supporting 80 64

Total 555 338 Staff Strength in Position as on 31 March 2010

13

Introduction

Budget Allocation vis-à-vis Utilization (2009–10)(Rupees in Lakhs)

Head of Allocation ExpenditureAccount Plan Non-Plan Plan Non-Plan

Pay & Allowances 0.00 2224.98 0.00 2224.64TA 5.33 4.63 5.32 4.63

OTA 0.00 0.31 0.00 0.30HRD/Fellowship 1.66 27.25 1.65 26.06Contingencies 75.58 157.21 75.57 157.13

Equipments 18.32 6.37 18.32 6.45Furniture 1.49 0.00 1.49 0.00Works 21.00 29.00 21.00 29.00

Library 26.62 0.00 26.62 0.00

Total 150.00 2449.75 149.97 2448.21

Cells● Training Administration Cell (TAC)● Consultancy Processing Cell (CPC)● Planning, Monitoring and Evaluation (PME) Cell

Financial StatementThe Standing Finance Committee had approved the XIPlan Budget of the Institute. The total outlay of Rs. 1200lakhs was sanctioned under the XI Plan budget of theInstitute.

Through regular monitoring, the Institute was able toensure optimal utilization of funds available in thebudget. The actual utilization of the budget both underplan and non-plan is furnished in the sequel.

The research targets set by the Institute wereimplemented by six Divisions of the Institute, viz.Sample Survey, Design of Experiments, Biometrics,Forecasting Techniques, Econometrics and ComputerApplications. The basic, applied, adaptive and strategicresearch in Agricultural Statistics and ComputerApplication is carried out under six broad programmesthat cut across the boundaries of the Divisions andencourage interdisciplinary research. The sixprogrammes are as under:

1. Development and analysis of experimental designsfor agricultural system research

2. Forecasting and remote sensing techniques andstatistical applications of GIS in agriculturalsystems

3. Development of techniques for planning andexecution of surveys and analysis of data includingeconomic problems of current interest

4. Modeling and simulation techniques in biologicalsystems

5. Development of informatics in agricultural research6. Teaching and training in Agricultural Statistics and

Computer Application

Programme 1: DEVELOPMENT AND ANALYSIS OFEXPERIMENTAL DESIGNS FOR AGRICULTURALSYSTEM RESEARCH

Supersaturated Designs for Scarce ExperimentalResourcesSupersaturated Designs (SSDs) are essentiallyfractional factorial plans employed generally inscreening experiments in which usually a large numberof factors are investigated, but only a few of them areactive having significant influence on the response. Thisfeature of SSDs is termed as effect sparsity.Identification of these few active factors correctly andeconomically is the main purpose of such experiments.The focus on the class of SSDs is for its run-sizeeconomy and mathematical novelty. The run size is notenough to estimate the main effects of all the factors inthe experiment.

Research Achievements

16


Two-level SSDs have been studied extensively becauseof their application and ease of generation. But multi-level SSDs are often required in agricultural, industrialand scientific experimentation for exploring nonlineareffects of the factors. Mixed-level SSDs are alsorequested frequently in experimentation. In anexperimental situation where in several factors havesame number of levels and one or two factors havedifferent number of levels than the rest of the factors,mixed level SSDs become useful. The few factors withdifferent levels may be called as factors of asymmetryand are important factors. Some recent references onmixed level SSDs are Fang et al. (2003; Metrika 58),Li et al. (2004; Statist. Prob. Letters 69), Koukouvinosand Mantas (2005; Statist. Prob. Letters 74), Ai et al.(2007; J. Statist. Plann. Inf. 137), Tang et al. (2007;J. Statist. Plan. Inf. 137) and Gupta et al. (2008;J. Statist. Theo. Pract. 2; 2009; Statist. Prob. Letters 79).

Some methods of constructing ( )NODfE -efficient

and ( )2χE -efficient, balanced, mixed level SSDs,derived essentially from the juxtaposition of uniformdesigns (centered L

2-discrepancy) and Hadamard

matrices have been given and criteria have been usedto investigate the efficiency of the designs constructed.One method of construction generates SSDs of the type

ns×2n-1//n. Mathematical expressions of ( )NODfE and

( )2χE have been obtained for this series of SSDs andit has been shown algebraically that all the designs are

always ( )NODfE and ( )2χE optimal. Here n ≡ 0 {mod(4)} and s (<n) is a positive integer. The case s = 1 isvery interesting as for this case for every design

( )NODfE = 1 and ( )2χE = 2 and all the designs areoptimal according to these two criteria. Another seriesof SSDs obtained are of the type (n/2)×2n-1//n. For thisseries of SSDs it is not possible to obtain neat

expressions for ( )NODfE and ( )2χE . However, for n ≤60, all the designs obtained are NODf -optimal and their

( )2χE -efficiency is also very high.

For the construction of SSDs, uniform designs andHadamard matrices have been taken respectively fromhttp://www.math.hkbu.edu.hk/UniformDesign/,maintained by Chang-Xing Ma, and from http://www.iasri.res.in/WebHadamard/WebHadamard.htm,(maintained at Design Resources Server, IASRI).

SSDs are useful for the experimental situations wherethe number of experimental units is less than thenumber of parameters to be estimated. In suchexperimental situations, it is quite common that anexperimenter begins the experimentation using anefficient design with the resources available at that timein the form of number of affordable runs, say n. Theexperimenter uses a two-level E(s2)-optimal SSD(n,m) = d. After the initiation of the experiment or after theexperiment is over, additional resources becomeavailable that permit the experimenter to include r,1≤r<m-n more runs to the design d. How does theexperimenter pick the additional runs and augment theoriginal design d so as to get an extended SSD (n+r,m) = d $, which is also E(s2)-optimal in the extendedclass. In other words, the problem is to obtain anextended E(s2)-optimal SSD(n+r, m) = d$ given thatthe original SSD(n, m) = d is E(s2)-optimal.

This situation has been handled by adding r runs tothe already used E(s2)-optimal SSD (n, m) and usingthe existing bounds given by Das et al. (2008; J. Statist.Plann. Inf. 138) and Suen and Das (2009; J. Statist.Plann. Inf. 140) depending upon (n+r) is even or oddfor evaluating the efficiency of the extended design.But this bound may be difficult to attain because thesub-design with n runs is already E(s2)-optimal.Therefore, a new lower bound to E(s2) of the extendeddesign d$, obtained by adding r new runs to d, giventhat d is E(s2)–optimal, has been obtained.

A new class of extended E(s2)-optimal two-level SSDshas been obtained by adding runs to an existing E(s2)-optimal two-level SSDs. The extended design is a unionof two optimal SSDs belonging to different classes. Newlower bound to E(s2) has been obtained for theextended SSDs. For some optimal designs generated,the value of E(s2) smaller than the lower bound givenby Das et al. (2008, J. Statist. Plann. Inf. 138). Thisclass of unbalanced SSDs needs to be studied furtherin detail.

A catalogue of 67 ( )NODfE -optimal mixed-level SSDsgenerated from uniform design and Hadamard matrix

has been prepared. The ( )2χE -efficiency of thedesigns is also given. Similarly a small catalogue ofextended two-level E(s2)-optimal SSDs has beenprepared. The extended designs are E(s2)-optimalbefore and after adding r runs to SSD(n, m).

17


Further, the layout of the designs given in the cataloguecan also be obtained. The bibliography on SSDs has alsobeen expanded by adding the latest references on SSDs.

Designs for Crop Sequence ExperimentsA factorial experiment run in a block design (blockdesigns with factorial structure) is said to have theOrthogonal Factorial Structure (OFS) if the adjustedtreatment sum of squares can be split up orthogonallyinto components due to different factorial effects likemain effects and interactions. In such a design inter-effect orthogonality holds if the best linear unbiasedestimates of the estimable treatment contrastsbelonging to different factorial effects are orthogonalor uncorrelated. Any factorial effect is said to bebalanced if all the normalized contrasts belonging tothat effect are estimated with the same variance. Thesedesigns have very interesting applications in cropsequence experiments where two crops are grown intwo cropping seasons, Kharif and Rabi. One set oftreatments is given in the Kharif crop and anotherdistinct set of treatments is given in the Rabi crop. Theobservations are recorded in both the seasons. Theinterest of the experimenter is in the direct effects ofKharif and Rabi treatments, the residual effect of theKharif treatments and the interaction of the residualeffect of Kharif treatments and direct effect of Rabitreatments. There may be more than two cropssequence. Similarly, the treatments in the individualcropping season could have a factorial structure. Theseextensions are pretty simple and straight forward. Fromexperimenter’s point of view, it is desirable that the maineffects efficiencies are very high and the interactionefficiencies are also reasonably high.

For two factor factorial experiments with v = s1�s

2,

where s1

and s2 are the number of levels of the two

factors, respectively and v is the total number oftreatment (combinations), some methods ofconstruction of factorial designs with all main effectsbalanced are available in the literature when (i) s

1 is an

integral multiple of s2; block size is a multiple of both s

1

and s2 and (ii) s

1and s

2 have a common factor, like s

1=f

1f

and s2=f

2f ; block size is a multiple of both s

1 and s

2. It

is indeed possible that s1= f

1�f

2�. . .�fp and s

2= h

1�h

2�.

. . �hq. Then it is indeed possible to obtain a design forv = f

1�f

2�. . . �fp� h

1�h

2�. . .�hp factorial experiment

having all the properties of the original design.

A unified method of construction of factorial designsfor v = s

1�s

2 has been given. The designs generated

are (i) with single replication of treatment combinationsand (ii) with replication two or more of the treatmentcombinations. The designs are balanced in the sensethat main effects can be estimated with full efficiency.Some of the interaction effects also have full efficiency.The efficiency of the other interactions is high. Usingreplacement and collapsing of levels, one can generatedesigns for v=f

1�f

2�. . . �fp� h

1�h

2�. . .�hp factorial

experiment. Most of the methods available fall as aparticular case of this unified approach.

This unified approach, however, does not allow theconstruction of designs when s

1 and s

2 are co-prime

and block size is a multiple of both s1 and s

2. This needs

to be investigated further.

Structure Resistant Designs

Extended group divisible designs are useful for cropsequence experiments. In these experiments,sometimes either the level of a factor may be lethal ormaterial pertaining to that level may becomeunavailable at the time of laying out the experiment.Therefore, it is desired to obtain extended groupdivisible designs that retain the property of orthogonalfactorial structure with balance when the observationspertaining to treatment combinations of a particular levelof a factor are missing. For such situations, structureresistant extended group divisible designs with unequalblock sizes have been obtained.

Design Resources Server

● Design Resources Server (www.iasri.res.in/design)developed to popularize and disseminate researchin design of experiments among experimenters andresearch statisticians has been strengthened. Thehome page of the server is

18


● Statistical genomics

A new link on Statistical Genomics has been initiatedessentially as an e-learning platform which can beuseful to the researchers particularly the geneticists,the biologists, the statisticians and the computationalbiology experts. It contains the information on somepublic domain softwares that can be downloadedfree of cost. A bibliography on design and analysisof microarray experiments is also given.These are hosted at http://iasri.res.in/design/Statistical_Genomics/default.htm. A screen shot ofthis link is

The following new additions have been made on DesignResources Server

● Analysis of data

The page “Analysis of Data” has been strengthenedby adding the steps and syntax for (i) fitting non-linear models using SAS and SPSS on the sub-linkNon-Linear Models, and (ii) performing clusteranalysis of data using SAS and SPSS on thesub-link Cluster Analysis. Some screens shots foranalysis of data appear like

controlling efficiency for interaction effects are alsogiven at this link. URL for this link is www.iasri.res.in/design/factorial/factorial.htm. Some screen shots forblock designs with factorial treatment structure areas given below:

● Block designs with factorial treatment structureOn the link Designs for Factorial Experiments, a sub-link has been added on Block Designs with FactorialTreatment Structure giving a bibliography with 232references on the subject. Catalogues of designshaving orthogonal factorial structure permittingestimation of main effects with full efficiency and

19


gave 10402 page views, 8444 unique pageviews and usage through 782 cities across 92countries in 6 continents. During 01 April 2009to 31 March 2010, the Server gave 5392 pageviews and usage through 448 cities across 78countries in 6 continents.

Outliers in Multi-response ExperimentsExperiments in which data on several responses aremeasured from an experimental unit corresponding tothe application of a treatment, are known as multi-response experiments. Multi-response experiments arevery common in agricultural experiments. Completemulti-response experiments are those experiments inwhich all the response variables are recorded from eachexperimental unit. Outlier(s) in multi-responseexperiments is/are likely to appear. If an experimentalplot is heavily infested with pests, disease and/or weedsthen all the responses observed from that plot may beoutlier(s). Outlier(s) may also occur because of heavyirrigation on some experimental plot(s) by mistake.Outlier(s) could very well be due to transcription errors.The data from such experiments is generally analyzedwithout giving any importance to these outlyingobservations. When outliers are present in the data,the whole setup of the experiment is disturbed whichmay result in erroneous conclusions. Therefore, itbecomes pertinent to detect outlier(s) before analyzingthe data from these experiments.

A test statistic has been developed earlier for detectionof a single outlier observation vector in multi-responseexperiments conducted in block designs. It may happenthat all the components of the observation vectorobtained from an experimental unit may not be outlier.To deal with the situations where observations from allthe responses may not be outliers, general expressionof Cook-statistic has been obtained for detecting any tobservations from each of any k responses as outliers.Then appropriate expressions for some particular casesare also obtained.

Further, outlier(s) may exist in more than oneobservation vectors. Therefore, a general expressionof Cook-statistic under mean shift model for detectingany t outlier observation vectors has been obtained.Two upper bounds of Cook-statistic have also beenobtained. These upper bounds help to reduce thecomputation of all possible sets of t outlier observation

● Dissemination of the ServerTo popularize the server among agriculturalscientists, a Bulletin on the Design ResourcesServer was published which was released byDr. MM Pandey, DDG (Engg), ICAR on 29 April2009. The presentations on the Server were madeat (i) Central Asia office of ICARDA at Tashkentduring 01-05 June 2009; (ii) ANGRAU, Hyderabadduring 16-17 June 2009; (iii) RARS, Tirupati on 05October 2009; (iv) ICARDA, Aleppo, Syria during08-19 November 2009; (v) BCKV, Kalyani on 22December 2009; (vi) RARS, Ankapalle on 06January 2010 and (vii) National Research Centrefor Agroforestry, Jhansi on 12 February 2010.

● Usage of the Server

- Warren F. Kuhfeld. Orthogonal Arrays. AnalyticsDivision SAS, Document No. 273 (http://support.sas.com/techsup/technote/ts723.html).

- Electronic text material in “New andRestructured Post-Graduate Curricula & Syllabion Statistical Sciences (Statistics/AgriculturalStatistics; Bio-Statistics, Computer Application)of Education Division, Indian Council ofAgricultural Research, New Delhi, 2008.

- Jingbo Gao, Xu Zhu, Nandi, A.K. (2009). Non-redundant precoding and PARR reduction inMIMO OFDM systems with ICA based blindequalization. IEEE transactions on WirelessCommunications, 8(6), 3038-3049.

- Design Resources Server is a copyright ofIASRI (ICAR). The server has been registeredunder Google analytics on 26 May 2008. During26 May 2008 - 31 March 2010, Google Analytics

20


vectors. If these upper bounds are not statisticallysignificant, then there is no need to compute all possibleset of vectors. Developed statistics are applied to realexperimental data.

Designs for Mixture Experiments in AgricultureMixture experiments with process variables havecommonly been used in agricultural experiments. Forexample, consider an experiment that has beenconducted with the application of 120 kg Nitrogen (N)applied in splits at different crop growth stages. Sincethe fixed quantity of nitrogen has been applied atdifferent crop growth stages, therefore, the responsedepends upon the proportion of nitrogen applied atdifferent crop growth stages. This experiment has beenconducted with two varieties of paddy viz. Saket-4(early) and Rasi (medium). The split doses of nitrogenapplied in splits constitute the experiments withmixtures. The varieties are not the part of mixtureproportions but they affect the response variable. Sothe variety is the process variable and the wholeexperiment becomes mixture experiment with processvariable. These experiments in NARS are generallyconducted and analyzed using a randomized completeblock design. This provides the inference on the besttreatment tried during the experiment and does notprovide any information on the relationship of theproportions with the response variable. Further, theexperimenter may be interested in obtaining optimumsplit which may be other than those tried in theexperiment.These questions can be answered bydrawing an analogy of these experiments withexperiments with mixtures. The basic problem inanalyzing the data from these experiments as perexperiments with mixtures methodology is that thenumber of points are chosen arbitrarily and may notallow fitting of canonical polynomials.

To deal with such situations, two methods ofconstruction of designs for mixture experiments withprocess variables have been developed. In Method I,the use of orthogonally blocked response surfacedesigns and projection matrices is suggested. InMethod II, blocking criteria of response surface designssuggested by Wu and Ding (1998; J. Statist. Plann.Inf., 71, 331-348) is employed. The designs for mixtureexperiments with process variables obtainable fromthese methods of construction have been cataloguedfor both Linear and Quadratic models for 2-5 mixturecomponents and one process variable with 2-levels.

Experimental Designs for Agricultural ResearchInvolving Sequences of Treatments

In many agricultural experiments and veterinary trials,it is often required to measure the effect of responsefrom two or more factors. In some of such trials, one ofthe factors does not exhibit residual effects, while theothers do. For this situation, a class of factorial designsinvolving sequences of treatment combinations arisingfrom two factors that are balanced for residual effectsof one factor has been obtained. These designs canbe obtained for all levels of first factor (≥3) with arestriction of number of levels of second factor as 2.These designs are found to be partially variancebalanced with treatment combinations following avarying circular association scheme. Efficiency of thesedesigns has been studied in comparison to a singlefactor design.

The most distinguishing feature of designs involvingsequences of treatments is the presence of residual orcarry over effects of treatments as observations aretaken repeatedly from same experimental units fromperiod to period. These carry over effects may be ofdifferent magnitudes and types. But mostly the carryover effect is in some way or other proportional to thedirect effect of treatments. Designs involving sequencesof treatments with an additive carry over model withcarry over effects proportional to the direct effects aresuitable for such situations. Proportionality parameteris unknown and prior information on the proportionalityparameter would be helpful. Particular interest centerson the sign of the proportion, that is, whether carry overtakes the form of assimilation or a contrast betweensuccessive treatments. But this entirely depends on thenature of the experiment. Model and experimental setup for evaluation of designs involving sequences oftreatments with residual effects proportional to directeffects has been defined. Information for the estimationof contrasts pertaining to direct effects of treatments insix classes of designs involving sequences oftreatments [Williams (1949, Australian J. Sci. Res., A2);Balaam (1968, Biometrics, 24); Sharma 1981,Australian J. Statist., 23(3))] for proportionalityparameter taking values from -1 to +1, is worked outempirically using SAS codes developed, as comparedto an orthogonal design with the same number ofreplications. The value of the proportionality parameteris estimated based on the maximum informationobtained for different number of treatments. This will

21


help the experimenter in selecting an appropriatedesign for a given situation.

In some experimental situations involving sequencesof treatments, the experimenters are interested in thecomparison of several new (test) treatments to anotherset of established (standard or control) treatmentsrather than in all possible pair-wise comparisons. Here,the interest is in drawing inference on a subset ofcomparisons among treatments and so designs needto be developed to meet these requirements. A seriesof designs involving sequences of treatments forcomparing two disjoint sets of treatments has beenobtained and variance of contrasts pertaining to directas well as residual effects of test versus test, test versuscontrol and control versus control treatments have beenworked out. A list of parameters of these designs hasbeen prepared for number of test treatments < 15 alongwith the variances.

Nested Designs involving Sequences of Treatments

In the experimental situations, wherein experimentalunits are required to perform a series of tasks one afteranother under various experimental conditions such asdifferent types of lighting or temperature or equipments,it is difficult to change the experimental conditions. Eachsubject is required to perform all the assigned tasksunder one set of conditions during one session. Theconditions are altered from one session to another. Thishas a resemblance with nested structure withexperimental conditions treated as levels of first factor(bigger set) and different tasks treated as levels ofnested factor (smaller set). For such experimentalsituations, two classes of nested designs involvingsequences of treatments with same number ofexperimental periods and units have been obtained.The precision of estimation of direct and residual effectsis more with the design having more number of levelsof the nested factor.

Neighbour Balanced Designs

Neighbour balanced designs, wherein the allocation oftreatments is such that every treatment occurs equallyoften with every other treatment as neighbours, areused when the treatment applied to one experimentalplot may affect the response on neighbouring plotsbesides the response to which it is applied. Thesedesigns ensure that no treatment is undulydisadvantaged by its neighbours and help in estimating

the neighbour effects besides the direct effects oftreatments. Universal optimality of circular neighbourbalanced block designs under mixed effects model,assuming block effects to be random, has beenestablished. Combined intra-inter block reduced normalequations for estimating direct and neighbour effectshave been derived. Some universally optimal familiesof circular neighbour balanced block designs have alsobeen obtained.

The concept of Neighbour Balanced Block (NBB)designs has been defined for the experimental situationwhere the treatments are the combinations of levels oftwo factors and only one of the factor exhibits neighboureffect. Some methods of constructing complete NBBdesigns for two factors in a plot strongly neighbourbalanced for one factor has been obtained. Thesedesigns are variance balanced for estimating the directeffects of contrasts pertaining to combinations oflevels of both the factors. An incomplete NBB designfor two factors has also been obtained which is foundto be partially variance balanced with three associateclasses.

Conditions have been derived for the estimation ofcoefficients of second-order response surface modelfor the experimental situation in which the experimentalunits, i.e., plots experience the neighbor effects fromimmediate left and right neighboring plots assumingthe plots to be placed adjacent linearly with no gaps. Amethod of constructing rotatable designs for fittingsecond-order response surface in the presence ofneighbor effects has been developed.

Partially Balanced Incomplete Block Designs

Two three-class association schemes called tetrahedralassociation scheme and cubical association schemehave been defined along with methods of constructingpartially balanced incomplete block designs based onthese schemes. Designs based on cubical associationscheme are found to be resolvable. These designs aremore efficient than the circular lattice [PBIB(3) designs]with the same number of experimental units for theestimation of elementary treatment contrasts.

Polygonal Designs

A linear integer programming approach has beendeveloped for obtaining polygonal designs for givennumber of treatments v, block size k, concurrence oftreatments separated by a distance of m + 1 or more

22


as λ and all other concurrences as zero, , here

[.] denotes the greatest integer function. The mainfeature of the proposed approach is that it directlyidentifies the required incidence vectors for generatinga polygonal design. Using the proposed approach, acomplete solution is provided for constructing polygonaldesigns for number of treatments v ≤ 100, block size

k = 3, 2,1=λ and . These designs have

one to one correspondence with balanced samplingplans excluding adjacent units.

Generalized Row-column Designs for AgriculturalExperiments

Row-column designs are widely used in agricultural andhorticultural research for the control of non-treatmentvariability in experiments conducted both in field as wellas glasshouse arising due to two sources of variabilityin the experimental material. However, for manyagricultural experiments, the number of treatments maybe substantially larger than the number of replicatesand standard row-column designs may not be useful.Semi-Latin Squares which are generalized n×n Latinsquares for nk treatments, where k is an integer greaterthan one, have been developed in literature for suchsituations. Intersection of each row and column containsa cell of k units. Each row and each column contains aset of nk units such that every treatment occurs oncein every row and every column.

Most of the work on semi-Latin Squares has resultedin designs with complete rows and columns andrestricted to cell size two. The experimental situationsmay require designs with incomplete rows. For suchsituations, a method of constructing generalizedincomplete Trojan-type design for v = sm (s ≥ 2)treatments in m rows, n columns with cells containingk (= sα) sub-units has been developed. Each treatmentis replicated p (= αn; α, n ≥ 2 and 4 ≤ p ≤ m - 2) times inthe design. The columns of the generalized incompleteTrojan-type design so obtained are complete with eachtreatment occurring α times and the rows areincomplete.

Experiments Planned on Stations under the ProjectDirectorate for Farming Systems ResearchThe experiments under the Project Directorate forFarming Systems Research are planned and conducted

under four types of research programmes viz. (i)development of new cropping systems; (ii) nutrientmanagement in cropping systems; (iii) developmentof system based management practices and (iv)maximum yield research. These experiments areconducted using Randomized complete block (RCB)design, Factorial RCB design, 32 × 2 balancedconfounded factorial experiments.

Data of 75 experiments conducted during the year2007-08 have been received and analysis has beencompleted. Out of 75 experiments, in 26 experimentspercent coefficient of variation was found to be morethan 10% and in 21 experiments CV was less than 5%.Treatment effects were found to be significant in 57experiments. Results have been tabulated in the formof summary tables and have been sent to the respectivescientist- in-charge of the cooperating centres. The finaltables of the results of the experiments conductedduring 2007-08 at OSR centres have been preparedand sent to PDFSR, Modipuram for inclusion in theproject report of AICRP on IFS. Data of 120 experimentsconducted during the year 2008-09 have been receivedand analysis work is in progress.

Developed the software module for online data entryof Experiment 1a (Intensification /Diversification ofcropping sequence based on high value crops). Themodule for analysis of data pertaining to this experimenthas also been developed. Both the modules are intesting stage. Some screen shots are

23


As per the authentication level of the user, the usercan browse the information. A user given the level ofSuper Adminstrator to enter data in respect ofexperiments can view the analysis, year-wise reportas well as use help module to enter data. A screenshot is as:

On selecting Analysis, one gets the following form forwhich analysis could be viewed:

On Farm Research Experiments

Three types of experiments viz. Response of nutrients;Diversification/Intensification of cropping system andsustainable production system are planned andconducted at 32 On-Farm centres in farmers’ fieldsunder the Project directorate of Farming SystemsResearch, Modipuram during 2008-09. The data of 82experiments conducted at 1732 farmers’ fields at 23On-Farm centres are processed for statistical analysis.Distribution of percent coefficient of variation (CV) ofexperiments is obtained and it is observed that majorityof experiments (61%) have CV less than 5% and 31%of experiments have CV in the range of 5% to 10%. In72% of experiment-III (Sustainable production system)the CV is found to be less than 5% whereas it is in 56%of the experiment-I (Response of nutrients).

Software module has been developed for on-line dataentry and statistical analysis of experiment-I (Responseof nutrients) from the respective centres is under testingstage. Some screen shots that give index for users toview introduction of the experiment, login to viewseveral features including data entry, analysis andreports are:

24


The results are displayed as follows: It is observed that the fertilizer response ratios varywidely from region to region and crop to crop. Fertilizerresponse ratios for kharif rice of N over control varyfrom 1.97 kg/kg (North Telengana) to 25.57 kg/kg(Eastern Dry Zone of Karnataka) at NARP zone leveland that of NPK over control vary from 4.34 kg/kg (NorthTelengana) to 26.35 kg/kg (Upper Brahmputra Valleyof Assam). At national level the fertilizer response ratioof all nutrient combinations are high and vary from 11.96kg/kg of N over control to 17.73 kg/kg of P over NK forrice crop whereas these values are low ranged 2.93kg/kg to 7.07 kg/kg for Jowar crop. The response ratios ofvarious nutrients for Maize and Wheat crop areobserved to be of moderate and high order at nationallevel. Among the pulse crops, Redgram shows lowerresponse ratios of 2.51 kg/kg to 4.16 kg/kg for variousnutrient combinations. The response ratios of cottonare found to be 4.16 kg/kg of N over control and 9.49kg/kg of K over NP.

From the study, it is seen that for the cereal group ofcrops the respective response ratios at all India levelfor all nutrient combinations are higher than those ofoilseed and pulse group. The fertilizer response ratiosof N over control are 9.20, 7.73 and 8.51 kg/kg forcereals, oilseeds and pulse group whereas these valueof NPK over control are 10.80, 5.60 and 6.70 kg/kgrespectively. The pooled response ratio for all foodgraincrops put together at national level lies between 8.79kg/kg (NP over control) and 10.98 kg/kg (K over NP).The fertilizer response ratio for all foodgrain crops forNPK over control is observed as 9.27 kg/kg which is morethan response observed for N, NP, NK over control.This indicates that use of recommended dose of NPKenhances productivity.

Experiments Relating to AICRP on STCR

Experiments with new treatment structure involvingorganic manures and major nutrients N, P and K in a33 factorial setup in 24 design points are conductedat 15 centres of AICRP on STCR project using thedesign suggested by the Institute. No data is reportedfrom Coimbatore centre. To examine whether the fertilitygradient has been created, analysis of variance iscarried out using the soil nutrients SN, SP and SKseparately as dependent variables. It is observed thatout of 13 centres (Bangalore, Bikaner, Barrackpore,Hisar, Jabalpur, Kalyani, Vellanikkera, Ludhiana, NewDelhi, Pantnagar, Pusa (Bihar), Rahuri and Raipur) the

Fertilizer Response Ratio

Fertilizer Response Ratio (FRR), average increase ofgrain yield in kg of a crop due to per kg use of fertilizernutrient of 14 crops (5 cereals, 4 pulses, 5 oilseed) atNARP zone level, state level and all India level hasbeen obtained from the data of experiments “Responseof Nutrients” for the period 1999-2000 to 2006-07.Eight fertilizer response ratios for different fertilizercombinations such as N, NP, NK, NPK over control, Pover N and NK, K over N and NP have been workedout for different crops when the recommended dosesof these fertilizers are applied.

25


fertility gradient is created in respect of SN, SP and SKover all the fields of experimentation in 9 centres (exceptin Barrackpore, Kalyani, New Delhi and Kerala). In theremaining centres, it is not created for either in respectof SN or SP or SK. While checking the creation of fertilitygradient (Organic manure level wise) it is observed thatin 7 centres (Bangalore, Bikaner, Hisar, Jabalpur,Pantnagar, Pusa (Bihar) and Rahuri) the fertilitygradient is created for SN, SP and SK. In the remainingcentres, it is not created for either in respect of SN orSP or SK.

The following analyses are also performed:(1) Evaluation of responses to middle (optimum) dosesof N, P and K, (2) Analysis of variance with and withoutcovariates SN , SP and SK, (3) Fitting of responsesurfaces at various levels of organic manure and alsocombined over all levels, (4) Testing of homogeneity ofthe regression equations, (5) Exploration of responsesurface in the vicinity of the stationary point,(6) Estimating the optimal values of N, P and K to beapplied and (7) Estimation of optimal values of N, Pand K with the help of targeted yield equations.

When analysis of variance is carried out for Treatment,FYM and their interaction, it is observed that in 6 centresall the effects are significant. In the remaining centres,it is observed that in most of the cases, the interactioneffect is not significant. When analysis of covariance iscarried out taking the soil available nutrients SN, SPand SK it is observed that in most of the cases, theinteraction effect is also significant along withconsiderable reduction in coefficient of variation.Analysis of covariance helped in identification of thebest level of the organic manure. At Pantnagar it isobserved that for all the 5 crops (Garlic, Mustard, Onion,Potato and Wheat), the treatment, FYM and theirinteraction effects are non-significant for both analysisof variance as well as analysis of covariance.

When analysis of variance is carried out for treatment,farmyard manure (FYM) and strips (within FYM levels),it is observed that at almost all the centres, all the effectsare significant. In some cases, it is observed thatthe effect of the strips (within FYM levels) are notsignificant.

Fitting of response surfaces at various levels of organicmanure and also combined over all levels are

performed and then the homogeneity of the regressionequations are tested. It is observed that at all thecentres, the three regression equations are found tobe homogeneous. Therefore, combined regression overall the levels of the organic manure is obtained to arriveat appropriate response function.

Substituting the site specific soil test values of SN, SPand SK; the combined regression equation reduces tocomplete second order Response Surface in terms ofadded fertilizers N, P and K respectively. Canonicalanalysis of Response Surface gives the nature of thestationary point as maxima, minima or as saddle point(neither maxima nor minima) with optimum doses ofFertilizer Nitrogen, Fertilizer Phosphorus and FertilizerPotassium along with predicted yield at stationary point.The exploration of response surface in the vicinity ofstationary point is performed when the stationary pointis a saddle point. This is done with the help of a SAScode developed under this project. In this approach,given the site specific soil test values of the soil availablenutrients, it is possible to generate various combinationsof optimum values of the nutrients, N, P and K for agiven targeted yield. The optimum values of nutrientsto be applied obtained through above investigation canbe used in demonstration trials for testing the validity.This exercise has been carried out for all the crops ofvarious centres.

Experiments conducted under AICRP on Long-TermFertilizer Experiments

The statistical analysis and summarization of resultsof the data generated from experiments conducted overthe years (1971-2007) to study the effect of continuousapplication of plants nutrients, singly and in combinationwith organic/inorganic form in different croppingsystems, under All India Co-ordinated Research Projecton Long Term Fertlizer Experiments (AICRP on LTFE)at different locations have shown the beneficial effectof farm yard manure (FYM) (10-15 t/ha/yr) applied inconjunction with 100% optimal NPK. Perusal ofresponses computed over un-manured control hasrevealed its enhanced overall mean response (over100% NPK) by 9.8 to 56.5% at various locations.Noteworthy beneficial effect of FYM are observed atLudhiana - maize (overall 52.7% increase over 100%NPK); Palampur - maize & wheat (47.8% & 40%);Bangalore - maize (21.6%); Coimbatore - finger millet& maize (28.4% & 20.1%); Pantnagar - rice & wheat

26


(34.9% & 31.6%) and Ranchi - soybean & wheat (36.7%& 25.6%). In relatively new locations at Junagadh -groundnut & wheat and Pattambi - rice & rice, theimprovement in overall mean responses over100%NPK with the use of FYM are in the range of41 to 56.5%, while at Raipur – rice & wheat and Udaipur– maize & wheat the range is 11 to 33%.

Crop-wise ‘Yield Sustainability Indices’ (YSI), for varioustreatments worked out to identify progressive practicescapable of producing high yields over the years ofexperimentation have also indicated the need ofintegrated use of organic manure (FYM) besiderecommended NPK level for sustaining high crop yieldsas higher YSI values relating to 100% NPK+FYMtreatment are achieved. Comparative low values of YSIobserved under the imbalanced treatments (N and NP)indicates that there may be decline in minimumachievable yield in these treatments, if continued overthe years in future.

The basic objective of integrated nutrient use is torestore organic matter in soils to maintain soil quality.Soil fertility status in terms of soil organic carbon asaffected by continuous cropping and manuring withinorganic and organic fertilizers over the years 1971-2007 is depicted as:

research workers and planners, etc. in the field ofagricultural sciences. Users can generate various realtime reports dynamically as per their requirementsbased on crop, location, treatment factors, soil type,etc. in addition to some most commonly used pre-defined reports. Provision for on-line data analysis hasalso been made for some of the commonly useddesigns. The home page and search pages for theinformation system are:

Agricultural Field Experiments Information System

Agricultural Field Experiments Information System(AFEIS) is a web-enabled information system (http://js.iasri.res.in/afeis), wherein information relating toagricultural field experiments (excluding pure varietaltrials) conducted in the country are stored andmaintained on-line. The objective is to have at a centralplace, in a compatible form, the results and ancillaryinformation of agricultural field experiments conductedin the past to serve as a reference material for scientists,

Presently, the database has information relating to29,284 agricultural field experiments conducted atvarious Agricultural Universities, ICAR ResearchInstitutes, Project Directorates, All India CoordinatedResearch Projects and Directorates of Agriculture ofState Governments, etc. Depending upon the natureof the treatments tried, experiments have beenclassified in various types as Manurial, Cultural,Disease, Pest and Weed Control measures and theircombinations with variety, if any. The typewisedistribution of experiments reveals that 39% of theexperiments in the database has been carrried out withmanurial treatments followed by disease managementexperiments (31%).

27


Programme 2: FORECASTING AND REMOTESENSING TECHNIQUES AND STATISTICALAPPLICATIONS OF GIS IN AGRICULTURAL SYSTEMS

Forecasting Crop Yield and Forewarning Diseasesusing Artificial Neural NetworksArtificial Neural Networks have received a great dealof attention because complicated problems can betreated by this even if the data are imprecise and noisy.Use of this approach has been studied for forecastingcrop yield as well as forewarning diseases. Neuralnetwork models are developed using crop yield(detrended) of rice, wheat and sugarcane for Centralplain zone (Kanpur, Lucknow, Fatehpur and Hardoidistricts), Eastern plain zone (Allahabad, Varanasi,Faizabad and Ballia districts) and Bundelkhandzone (Jhansi, Banda and Jalaun districts) of UttarPradesh in India as response or output variableand weather indices as input variables. For diseaseforewarning, models are developed considering variousaspects viz. maximum disease severity, crop ageat first appearance of disease and crop age at maximumdisease severity for Alternaria blight and Powderymildew for different locations and for different varietiesin mustard crop as response variable and weatherindices as predictors. Forecasts are obtained forsubsequent years. In this study, Multi Layer Perceptron(MLP) and Radial Basis function (RBF) based neuralnetworks with different hidden layers (one and two) anddifferent number of neurons in a hidden layer withhyperbolic function as an activation function areattempted and compared with weather indices (WI)based regression model. It has been found that MLPperforms better in most of the cases in terms of meanabsolute percentage error which indicates that neuralnetwork models possess considerable potential as analternative to regression models for forecastingagriculture system. The mean absolute percentageerror of various models for forecasting crop yield aswell as disease infestation for various crops ispresented in the following tables.

Mean Absolute Percentage Error for various models in differentcrops

Zone Crop MLP based RBF based WI basedANN Model ANN Model regression model

Central Rice 2.8 5.4 4.4Plain Zone Wheat 2.1 3.1 3.9

Sugarcane 1.5 6.0 1.8

Eastern Rice 3.2 2.6 1.9Plain Zone Wheat 2.0 3.3 3.7

Sugarcane 5.2 5.1 5.4

Bundelkhand Rice 6.3 6.7 4.6

Crop groupwise distribution of experiments availabe indatabase shows that maximum number of experimentsare conducted on cereal crops (42%). The number ofexperiments on pulse and oilseed crops are 14%, 21%respectively.

13,626 experiments from the database are validatedand approved for inclusion in the system. For makingprovisions of data entry of field experiments by thescientists of ICAR Institutions/SAUs etc. and as per thediscussions held with the Director, Monitoring andProgramme Evaluation, ANGRAU, Hyderabadregarding data entry to AFEIS web site by theirscientists, user authentication levels under AFEISare reviewed. In this respect identification of types/levels of users and accordingly modification indatabase tables and software development are beingundertaken.

28


Mean Absolute Percentage Error of various models forforewarning mustard diseases

Character Variety ANN(MLP) ANN(RBF) Reg (WI)

Alternaria blMight – Bharatpur 2006-07

Maximum Severity Varuna (on Leaf) 111.0 153.8 150.1Age at First Appearance 14.0 15.1 14.7Age at Peak Severity 14.1 27.3 22.3Maximum Severity Varuna (on Pod) 113.7 143.6 132.6Age at First Appearance 15.7 9.2 14.2Age at Peak Severity 3.9 6.4 5.4Maximum Severity Rohini (on Leaf) 184.0 200.6 196.3Age at First Appearance 12.0 15.5 8.9Age at Peak Severity 28.3 27.8 26.2Maximum Severity Rohini (on Pod) 174.8 220.4 229.6Age at First Appearance 29.3 28.2 24.7Age at Peak Severity 19.2 20.7 17.6

Alternaria blight – Dholi 2004-05

Maximum Severity Varuna(on Leaf) 38.1 29.9 51.9Age at First Appearance 15.6 9.9 8.4Age at Peak Severity 5.0 9.6 9.3Maximum Severity Pusabold (on Leaf) 32.0 45.9 48.5Age at First Appearance 7.2 10.9 10.4Age at Peak Severity 5.9 5.1 7.0Maximum Severity Varuna (on Pod) 88.1 75.4 88.9Age at First Appearance 7.6 12.8 3.9Age at Peak Severity 4.0 4.9 3.0Maximum Severity Pusabold (on Pod) 65.5 82.5 91.8Age at First Appearance 6.4 11.1 6.9Age at Peak Severity 3.5 3.3 3.3

Alternaria blight – Behrampur 2004-05

Maximum Severity Varuna (on Leaf) 60.1 64.4 61.9Age at First Appearance 18.8 20.1 22.3Age at Peak Severity 13.8 10.3 9.7Maximum Severity Varuna (on Pod) 107.2 81.8 68.1Age at First Appearance 21.9 19.3 23.3Age at Peak Severity 6.9 7.8 7.4Maximum Severity Binoy (on Leaf) 50.3 40.1 61.0Age at First Appearance 12.1 12.4 12.4Age at Peak Severity 10.5 11.9 9.7Maximum Severity Binoy (on Pod) 120.4 194.4 182.7Age at First Appearance 22.3 18.4 12.6Age at Peak Severity 3.8 3.0 2.9

Powdery mildew – S.K. Nagar 2006-07

Maximum Severity Varuna 26.5 56.2 35.1Age at First Appearance 12.2 15.1 20.2Age at Peak Severity 9.5 13.5 12.8Maximum Severity GM2 6.7 50.2 64.7Age at First Appearance 21.4 15.3 21.7Age at Peak Severity 12.8 14.1 13.8

It is found that that disease forewarning models basedon MLP architecture are better in 24 cases, RBFarchitecture are better in 6 cases and weather indicesbased regression models are better in 12 cases. Theresults indicate that the neural networks models usingMLP architecture can usefully be employed forforecasting crop yield and forewarning diseases.

Weather based Models for Forecasting Potato Yieldin Uttar Pradesh

Weather based models for forecasting potato yield

in Uttar Pradesh have been developed by usingweather data on maximum and minimum temperatureand morning and evening relative humidity during theperiod 1971-2002. The weather indices are constructedand used for development of regression models(RM) and complex polynomials (CP - using GroupMethod of Data Handling technique). The models aredeveloped at district as well as at zone levels (bypooling the data of various districts within therespective zones). The data for the year 2002-03 isused for validation of models. Using these models,the forecasts are computed at district-level. Thedistrict-level forecasts are combined by taking the areaunder the districts as weights to obtain forecastsat agro-climatic zone/state level. The salient findingsare:

− District level models provide better forecast thanzone level models in most of the cases indicatingthat development of district-level models may bepreferred only when adequate data are available.

− At state level, the per cent deviations of forecastsfrom the observed ones are less than 5%.

− It is feasible to obtain reliable forecasts aboutthree/four weeks before harvest.

Forecasts using these models and observed yields forvarious zones and state as a whole are presented as:

Stochastic Process Modeling and Forecastingthrough Discrete Nonlinear Time Series ApproachIn the versatile nonparametric functional coefficientautoregressive model (FCAR), the coefficient-functionchanges gradually rather than abruptly and this modelis given by

Yt = a1(Ut) Xt-1 + a2(Ut) Xt-2 +…+ap(Ut) Xt-p + et

29


where Yt is response variable, Xt-i , i=1,2,…,p areexplanatory variables, Ut is lag d variable, Xt-d , and {εt }is a sequence of independent random variables withzero mean and unit variance.

The coefficient-functions may be estimated by usingTaylor’s series expansion in which unknown coefficientsare estimated by the method of weighted least squares,weights being the kernel density function. Using thedata with Ui around u0, the following expression isminimized:

where K(.) is a Kernel function and h is the bandwidth.Optimal bandwidth h is selected by Modified multifoldcross-validation criterion. The overall average predictionerror is given by

The FCAR model is fitted to annual lac export data ofIndia for the period 1900-2000. The data is obtainedfrom the Shellac and Forest Products Export PromotionCouncil, Kolkata.

Estimates of parameters are obtained by usingcomputer program written in SAS-IML. The optimumvalues are found as p = 4 and d = 3.

The fitted FCAR (4,3) model for log data is obtained as

logXt= {4.216 + 0.200 (logXt-3 – 4.150)} logXt-1 + {4.423 – 0.2370(logXt-3 – 4.150)} logXt-2 + {4.381 – 0.040 (logXt-3 – 4.150)}logXt-3 + {4.380 + 0.025 (logXt-3 – 4.150)} logXt-4 + εt

The fitted FCAR(4,3) model along with data points isexhibited below:

One step and two step ahead forecasts for ARIMA,SETAR and FCAR models are:

One-step and Two-step ahead forecast of lac export

Forecast by

Years Actual ARIMA SETAR FCARmodel model model

2001 7015 5083.59 6621.03 6903.81(5372.04) (6167.43) (6985.61)

2002 6819 6222.60 8019.83 7768.40 (5024.97) (7138.36) (7670.08)

2003 6632 6221.21 6775.99 6990.92(5405.97) (8148.12) (7801.76)

2004 7301 6188.47 7621.51 7292.87(5347.00) (9198.28) (8676.72)

Values in parenthesis indicate two-step ahead forecast

It is observed that one-step ahead mean absoluteprediction error (Mean squared prediction error) forFCAR, ARIMA, SETAR models are 356.91 (260649.92),2283.68 (13621643) and 514.82 (430166.2)respectively. Similarly, for two-step ahead meanabsolute prediction error (Mean squared predictionerror) for these respective models are found to be856.49 (996534.97), 1654.25 (2809782) and 1147.08(1679664) respectively. This ensures that FCAR modelperforms better with respect to modeling and forecasting.

In the field of agriculture, quite often the time-seriesdata depicts cyclical patterns. Some examples of suchbehaviour are: India’s annual lac production/exportdata, India’s summer monsoon rainfall data andPopulation-sizes of several fish species having prey-predator type of interactions. Self-exciting thresholdautoregressive (SETAR) family of nonlinear time-seriesmodels with more than one threshold is capable ofdescribing cyclical data having sudden rise and fall.

SETAR three-regime model, written as SETAR (3; k1,

k2, k

3) model, can be expressed as

Formulae for one-step and two-step ahead forecastsfor fitted SETAR and FCAR models have been derived.

where k1, k

2, k

3 are orders of three Autoregressive (AR)

models; ai(1), ai

(2), ai(3) are autoregressive coefficients;

are the white noise terms; d is the delay

30


parameter (where the controlled threshold occurs) andrj, j = 1, 2 represent threshold values.

The three operators viz. selection, crossover, andmutation make genetic algorithm an important tool foroptimization. When a string (parameter solution) iscreated by GA, it is evaluated in terms of its fitness,which is the residual sum of squares (RSS). Selectionoperator of GA is performed to identify good solutions,to make its multiple copies and to eliminate badsolutions from the population. Since selection operatorcan not create a new solution, the crossover andmutation operators are used in mating pool to create anew population. If a crossover probability pc is used,100 pc% strings in the population are used in thecrossover and rest of the population is simply copiedto the new population. Diversity in the population canbe ensured by mutation operator. It alters a string locallyto create a better string (parameter solution). To ensurethe chance of entering new chromosomes into thepopulation, mutation with very small probability, say0.01 is required. In real coded GA, pair of real-parameter decision variable vector is used to create anew pair of offspring vectors and a decision variablevector is perturbed to a mutated vector in a meaningfulmanner using Simulated Binary Crossover operator.

The data on all-India annual lac production for theperiod 1930-31 to 2002-03 is considered. The objectivefunction Normalized Akaike Information Criterion (NAIC)given by

NAIC=[AIC(k1)+AIC(k2 )+AIC(k3 )]/(N-d)

is used for selecting the best model by applying GAoperators described above. Real-coded GA with SBX

(crossover operator) where is applied for

estimation of parameters. Computer programs for fittingSETAR three-regime model are developed in C++. TheGA parameters viz. population size, crossoverprobability, and mutation probability for minimization ofequation given below are respectively 100, 0.9, 0.01with number of generations as 100. The best fittedSETAR three-regime model on the basis of minimumNAIC value, viz. 6.23, is

12.00 + 0.51 Xt-1

+�t(1) if X

t-1 ≤ 25

Xt = 29.94 + 0.39 X

t-1 +

�

t(2)

if 25 < X

t-1 40

25.01 + 0.60 Xt-1

+ �t(3) if X

t-1 > 40

with Var (�t(1))=2.15, Var (�

t(2))=4.31 and Var(�

t(3))=8.61.

To get a visual idea, the fitted SETAR (3; 1, 1, 1) modelalong with data points is exhibited below:

A mechanistic interpretation of fitted SETAR model isas follows. The above fitted model can be written as

12.00 - 0.49 Xt-1, if Xt-1 ≤ 25 X

t - X

t-1 = 29.94 - 0.61 Xt-1, if 25 < Xt-1 ≤ 40

25.01 - 0.40 Xt-1, if Xt-1 > 40

In the lower regime, i.e. Xt-1≤ 25, Xt − Xt-1 tends to bepositive but small, implying slow increase in lac production.In the middle regime, i.e. 25<Xt-1≤40, Xt−Xt-1 tends to bepositive but large, implying comparatively faster increasein lac production. However, in the higher regime, i.e. Xt-1

> 40, Xt−Xt-1 tends to be negative, implying decrease inthe lac production. This type of behavior leads to cyclicity,which is in agreement with observed lac production data.

The forecast value for country’s lac production has beencalculated and presented below for the year 2003-04 to2007-08 using the fitted model. The forecast performancefor hold-out data on the basis of root mean square errorand mean absolute error for the fitted SETAR modelare computed as 2.71 and 2.27 respectively.

Forecasting for hold-out data of all-India lacproduction data (metric tonnes) by SETAR three-regime model

Year Actual Forecast

2003-04 20.05 20.772004-05 21.30 22.052005-06 18.00 22.672006-07 23.23 21.022007-08 20.64 23.64

31


To sum up, for country’s lac production data, it isconcluded that three-regime SETAR model hasperformed satisfactorily for modelling and forecastingpurpose.

For multimodal rainfall data, methodology of fittingmixture of distributions to ‘body’ and ‘tail’ using statisticallearning theory is demonstrated. Three estimators ofextreme value index are computed to fit the theoreticaltail distribution to the rainfall data. “Structural riskminimization procedure” is applied to fit the ‘body ‘ofthe rainfall distribution. As an illustration, the probabilitydistribution of monthly rainfall data for Orissameteorological subdivision is obtained by combinedbody-tail estimation method and it is shown that Hill’smethod has performed the best.

Remote Sensing Based Methodology for CollectingAgricultural Statistics in North-East Hilly Region

At present the Meghalaya state does not have anyobjective approach for collection of agricultural statisticsfor various crops. Only approximately 10% of thegeographical area of the state is under agriculture,which is scattered throughout the state. Therefore, it isrealized that it may be difficult to collect the informationabout agricultural statistics using only remote sensingdata, as identification of these small pockets ofagricultural land may lead to large extent of errorcomponents. Moreover due to the problem of cloudcover, cloud free satellite data is also not available.Further no cadastral maps and clear-cut villageboundaries exists, therefore traditional method ofsample survey is not appropriate for providing suitableestimates of area under various crops. Thus, there isneed to develop an integrated methodology forcollection of agricultural statistics using remote sensingsatellite data combined with ground survey andgeographical information system (GIS). Thus this studyis taken up with the objective of developing remotesensing based sampling methodology for multiple cropacreage estimation in Meghalaya. Under this studymajor crops of the state like paddy, maize, potato,pineapple, cashewnut are cosidered covering fourdistricts (East Garo Hills, West Garo Hills, East KhasiHills and Ri-Bhoi) of the state.

The data analysis for Rabi season was completed forall the four districts. Primary data collection is carriedout in two districts of Ri-Bhoi and West Garo Hills for

the Kharif season. The estimates of area under majorcrops are obtained on the basis of two season datausing the proposed integrated methodology based onground survey, remote sensing/satellite data and GIS.Analysis using post-stratification considering the layersof cropped area, jhum cultivation layer and DigitalElevation Model (DEM) layer, is also performed.

Programme 3: DEVELOPMENT OF TECHNIQUESFOR PLANNING AND EXECUTION OF SURVEYSAND ANALYSIS OF DATA INCLUDING ECONOMICPROBLEMS OF CURRENT INTEREST

Spatial Market Integration Studies

Spatial market integration is studied using advancedeconometric tools namely Augumented Dickey Fullertechnique for testing stationarity of time series,Johansen’s Co-integration method for finding thecointegrating vectors and Vector Error Correctionmechanism for finding out the speed of adjustment ofprice series to equilibrium for whole sale market ofimportant cereals (rice, wheat, jowar, bajra, maize),oilseeds (ground nut, mustard), edible oils (coconut oil,ground nut oil, mustard oil) and pulses (gram, moong,arhar, urd, etc.) using time series data on wholesaleprices for the period 1996 to 2008. The analysisrevealed that the integration among the markets hasimproved over the recent years. The prices ofagricultural commodities tend to converge among a fewselected state-level wholesale markets in India. Further,the speed of convergence to the long-run path resultingfrom a shock in price is slow in case of almost all theselected commodities except paddy and wheat. Theminimum support price and procurement policy areeffectively implemented in rice and wheat crops whichensured price stability and stronger market integration.Similarly these schemes may be effectivelyimplemented in other crops along with development ofinfrastructure and market intelligence to ensure bettermarket integration.

There is evidence of high volatility in the wholesaleprices of apple and pineapple crops. State levelwholesale markets are found to be weakly integratedfor these horticulture crops in India as metropolitanmarkets like Kolkata and Mumbai have failed to showintegration with markets operating in other major states.Further, integration in case of fruits like apple andpineapple may be weak for several other markets inIndia, particularly in non–metro towns /cities /remote

32


areas, which are poorly connected with other marketsdue to inadequate road connectivity, availability of timelytransport facilities, weak storage facilities etc. Theextent of spatial market integration of cereals, oilseeds,edible oils and pulses has improved in recent yearsfrom 1996 to 2008, compared to that in earlier years.The prices of agricultural commodities tend to convergeamong a few selected state-level wholesale marketsin India. The analysis for wheat and paddy cropsindicates the presence of similar long-runcharacteristics among the domestic prices except infew state level markets. The short run dynamicscaptured through VECM shows that the pricemovements along the long run equilibrium path in paddyare more stable. Greater spatial integration and fastspeed of adjustment to any shock in wheat and paddycould be attributable to price policy backed byprocurement in most of the states, which ensuresgreater price stability. Estimates of short run dynamicscaptured through VECM in case of jowar and maizecrops reveal negative and significant error correctioncoefficients, indicating that the price series are stablein the long run and any deviation caused in their pricesby any external shock is adjusted over a period of time.There exists full integration in the markets of groundnutand mustard oils while on the other hand, the integrationof oilseed markets is partial and there are higherdiversions in the long-run equilibrium path.

Futures Trading

In the area of futures trading, price volatility, pricediscovery and risk management are studied forimportant crops, and the contract designs of Indian wheatand maize crops are compared with US contracts.

It has been seen that there exists unidirectional Grangercausality from futures to spot markets in case of gram.The volatility of futures market is greater than the spotmarket volatility. The distribution of spot prices iscomparatively more skewed than futures prices. Theoccurrence of unit roots in the price generation processof spot and futures markets gives a preliminaryindication of shocks having permanent or long lastingeffect on price series. There is instantaneoustransmission of price signals between the markets andthe futures prices of one day lag influence spot prices.

Econometric Study of Women Empowermentthrough Dairying in Selected Districts of HaryanaBased on the analysis of data pertaining to various

agricultural and dairy attributed it is observed thatdairying is an important component of diversifiedagriculture in the selected districts (Karnal, Kurukshetra,Bhiwani and Mahendergarh) of Haryana. This sectorprovided the maximum amount of employment (35-60%) in all the selected blocks for the study. Besidesdairying, the household activities provide anotherimportant avenue for employment (27-40%). The cropproduction activities are also another segment, wherewomen are gainfully employed (10-28%). The availableevidence indicates that in all the blocks under study,feeding of animals is very important and is responsiblefor the maximum utilization of time. The contribution ofmilking of animals and cleaning of stall activities in thetime utilization schedule is large. More than 40% of thetime among dairy work is devoted for these twoactivities. Dairying in the state is helpful in theempowerment of women folk in rural areas. Amongseveral attributes studied for examining the extent ofempowerment of rural households, the coping capacityof women to the household shocks has highest rankfollowed by their participation in rural householddecision making followed by contribution to householdincome. It has been seen that dairying in the state hasan important role to play in the empowerment of ruralwomen. The spread of education of self and spouseas well as improvement in family income have positiveand significant impact on women empowerment.Though, the age of self and spouse are importantvariables, but very little can be done to make anychanges in it. Incentives for educating men and womenin rural areas, would improve the level of empowermentof women, which in turn will lead to empowerment ofwomen in Haryana.

Impact of Micronutrients on Crop Productivity andReturns

The analysis of data pertaining to the Site SpecificNutrient Management (SSNM) experiment planned atOn Stations under the aegis of Project Directorate ofFarming Systems Research reveals that Marginal ValueProduct (MVP) of micronutrients for kharif (every Year)is positive which implied that farmers will gain frominvestment on additional doses of micronutrients. Thevalue of MVP of ZnO/ZnCl

2 is negative at Palampur

centre for maize crop, indicates that the micronutrient isalready surplus in the soil. The MVP of micronutrients(applied alternate year) revealed that the expenditure onmicronutrients is profitable at Kanpur, Bhubneshwar andKalyani centres in rice crop, Sehore centre in soyabean

33


crop and at Thanjavur centre in groundnut crop. Whilein other centres/crops the additional investment onmicronutrients is not advisable. Similar trends areobtained in rabi (every/alternate year) treatments.

Identification of Factors Contributing towardsEnhancing Agricultural Productivity

Multidimensional scaling (MDS) approach is used foridentifying the factors contributing towards enhancingagricultural productivity pertaining to the subdomain“Plant Genetics and Breeding”.

Transformative activity index of the countries indifferent areas of Plant Genetics and Breeding

Areas USA CHINA INDIA2005 2009 2005 2009 2005 2009

Abiotic Stress 51 90 70 268 78 291Marker Assisted 78 86 149 105 98 188Selection (MAS)

Transgenics/ Tissue 101 75 139 121 217 181CultureBiotic Stress 114 102 112 88 84 116Pre-Breeding/ 104 115 64 78 79 113Germplasm

Varietal Improvement/ 103 110 110 72 121 105Conventional BreedingPollination System/ 100 127 119 94 47 95Mating SystemCytogenetics/Cytology 101 87 88 93 96 87

Gene Expression 103 92 119 128 97 74Bioinformatics 82 99 56 115 16 58Genetics/Inheritance 106 105 56 97 53 57

Hybridization 108 83 144 107 77 56Genetic Evolution/ 113 111 84 77 70 55MutationQuantitative Genetics/ 134 118 80 49 110 26Biometrics

Molecular Biology & 100 94 106 102 106 100Genomics

Estimation of Extent of Farming Practices,Resources and Activities with Energy use

National Sample Survey Organisation (NSSO) took upthe special study on Indian farmers and conducted aspecial survey “Situation Assessment Survey ofFarmers (SAS)” in 2003 in the rural areas of India aspart of NSS 59th round. Several reports have beenbrought out from the findings of this survey. Theestimates so obtained are lacking in their reliabilitymeasures and with insufficient use of informationavailable at different stages of sampling which couldotherwise be used as weights resulting in betterprecision of the estimates.

Making use of Projective Geometry Approach, MinimumVariance Linear Unbiased Estimators (MVLUE) areobtained for various parameters viz. (i) extent andseasonal variation of land use in different kinds offarming i.e. cultivation & allied agriculture, orchards &plantation, dairy, fishery and other farming (farming ofgoats, sheep, piggery, poultry & duckery, bee-keepingand other animal farming), (ii) extent and seasonal

Major policy and research factors for enhancingagricultural productivity

Figure above suggests that many of the factorsmentioned can be viewed as both policy and researchfactors.

Moreover, emerging areas have been identified throughscientometric techniques. For this, using the Web ofScience database, the relative position of India inresearch vis-à-vis other countries (U.S.A., U.K., Chinaand Brazil) over the years 2005 to 2009 have beenstudied using transformative activity index. Tablerepresented below shows the change in emphasis onresearchable areas for the countries viz., India, USAand China over the past five years. From the tablebelow, it can be seen that India is focusing more notonly on abiotic and biotic stresses but also on evolvingareas such as bioinformatics, molecular assistedselection, transgenics etc.

34


the infrastructure developed, items of data beingcollected under the scheme etc. and to suggestimprovements, if any.

The objectives of the RMIS scheme are examined. Themethodology being followed in the scheme is studiedand suggestions for improvements are made. The itemsof data being collected in the scheme are examinedand an assessment of data quality is made. Further,the infrastructure developed under the scheme isstudied and suitable suggestions are made forimprovements in the infrastructure.

Some of the recommendations made are:1. The infrastructure available under the RMIS

scheme is not adequate and needs to bestrengthened. There is shortage of manpower andaccommodation, lack of adequate data processingfacility and lack of transport.

2. There is a scope for improvement in the trainingprovided to the primary workers. In addition toclass-room lectures, the training be made morepractical oriented by actual collection of data insome villages. Instructions in the schedules beexplained with the help of suitable examples.

3. There is a need for modifications in Schedules.Difficulty is reported in collection of data on itemslike cost of construction of the scheme, measuringdepth of water, depth of well, Irrigation PotentialCreated/Utilized etc. These aspects need to belooked into.

4. The schedules and instructions manual need to bemade bilingual (English and local language).

5. The census of Minor Irrigation be given duepublicity in the local areas so as to createawareness among the farmers about itsimportance.

6. The budget sanctioned under RMIS scheme needsto be released to the states in time. This will help intimely implementation and completion of assignedwork of RMIS scheme.

7. Data processing facilities and networking systemof RMIS scheme for regular flow of data/informationat various levels and timely analysis of data needto be strengthened.

8. Concerted efforts should be made by the Nodalofficers implementing minor irrigation schemes, withthe help of village officials, for formation of Water

variation of available farming resources i.e. fertilizers,organic manure, improved seeds, pesticides andveterinary services and their use and (iii) extent offarming activities i.e. ploughing, irrigation, harvesting,threshing and others (cooking, lighting, cane crushingand transport) with energy use. The estimates of totalland possessed per farmer household (FHH) averagedover seasons (kharif & rabi) in different kinds of farmingranged between 0.008 ha-1.238 ha for all-India and0.011 ha-0.894 ha in North Eastern Hilly region.Estimated seasonal variations of these lands per FHHfor all-India and NEH region ranged between 0.002 ha-0.381 ha and 0-0.320 ha respectively. Farmingresources such as fertilizers, organic manure,pesticides and veterinary services are available withinthe village to 6-93% FHHs, while improved seeds arenot available to FHHs even within the reasonabledistance (5 km) in most of the states. Percentages ofFHHs using fire-wood for cooking, animal power forploughing & harvesting and electricity for lighting,irrigation & threshing as main sources of energy rangedbetween 20.6% (Punjab), 92.1% (Rajasthan), 13.7%(Orissa), 90.1% (Jharkhand) and 15.6% (Bihar)-94.5%(Punjab) respectively.

Evaluation of Rationalization of Minor IrrigationStatistics Scheme

Minor irrigation (MI) schemes are very relevant in Indiancontext. The MI schemes require very low investment.The farmer can spend a small amount and can haveassured supply of water. Due to the introduction of largenumber of MI schemes the area under irrigation hasincreased substantially. With a view to generateaccurate statistics on MI schemes a scheme entitledRationalization of Minor Irrigation Statistics (RMIS)scheme was initiated in 1987-88. Three census of MinorIrrigation have been conducted so far. The field workfor the fourth census has been completed. DuringEleventh Five Year Plan, the RMIS Scheme is broughtunder Central Sector as one of the components ofDevelopment of Water Resources Information Systemscheme of the Ministry of Water Resources. In thiscontext, the Planning Commission felt the need forcarrying out an evaluation of the RMIS scheme toassess its effectiveness and usefulness. The MinorIrrigation Statistics Division, Ministry of WaterResources awarded the evaluation study to IASRI witha view to determine whether the objectives of thescheme have been met, examining the methodology,

35


Users Associations under minor irrigation scheme.These bodies may be asked to maintain informationabout the potential created and potential utilized inthe respective minor irrigation schemes under theguidance of village officials.

Small Area Estimation for Zero-Inflated Data

The thrust of planning process, in recent years, hasshifted from macro to micro level. There is demand bythe administrators and policy planners for reliableestimates of various parameters at the micro level. Inview of the demands of modern time, the thrust ofresearch efforts have shifted to development of preciseestimators for small areas. An offshoot of thisdevelopment is that various Small Area Estimation(SAE) techniques are being proposed by theresearchers for implementation. SAE techniques arenow increasingly used in many developed countries.In our country large number of surveys/censuses arebeing carried out. There are, therefore, opportunitiesfor use of SAE techniques so that reliable estimates ofvarious parameters of interest are available toadministrators and policy planners. Commonly usedmethods of SAE based on a linear mixed model, forexample, the empirical best linear unbiased predictor,pseudo-empirical best linear unbiased predictor andmodel-assisted empirical best predictor of Jiang andLahiri (2006, J. American Statist. Assoc., 101) can beinefficient for zero-inflated data situations. Presenceof excess zeros in the data is a well-known problem insmall area estimation. A variety of approaches havebeen suggested for dealing with this problem. However,when the focus is on SAE using survey data, muchless is known- even though presence of excess zeroswithin a small area are clearly much more influentialthan they are in the larger overall sample. Accordingly,in the study “Small Area Estimation for Zero InflatedData” a method has been developed for SAE using themixture model (a combination of linear mixed modeland generalized linear mixed model) that accounts forpresence of excess zeros in the data. The proposedapproach of SAE works in three steps. First a linearmixed model is fitted for positive values of the variable.In the second step, a generalized linear mixed modelis fitted for probability of positive values. Finally thetwo models are combined at estimation stage. Theperformance of the proposed method is evaluatedthrough simulation studies using both datagenerated under the model and the real survey data

of 59th round of the National Sample SurveyOrganization on Debt-Investment Survey 2002-03 forrural areas of the State of Uttar Pradesh. The variableof interest is amount of loan outstanding perhousehold with an aim to predict the district levelaverage value of amount of loan outstanding perhousehold.

Region-specific Relative RMSE of the EBLUP (thin line)and proposed estimator (solid line) under model basedsimulations for different proportion (p) of zeros arepresented below:

Study on Status and Projection Estimates ofAgricultural Implements and Machinery

The 18th Indian Livestock Census was conducted byDepartment of Animal Husbandry, Dairying andFisheries (DAHD&F), Ministry of Agriculture,Government of India in 2007, during which informationon tractors, power tillers and other power-operatedagricultural machinery/implements was not collected.Accordingly, it became important to have projectionestimates of these for the future years.

State-wise data on total number of different items ofagricultural machinery and implements on which thedata had been collected in Indian Livestock Censusesduring 1951 to 2003 have been compiled in digital form

36


into a comprehensive database. During these livestockcensuses years, in few states data has not beencollected or partly collected.

The percentage contribution of Human Power, AnimalPower and Mechanical Power over the years 1960-61to 2006-07 is:

may arise in which there is negative correlation of sizesof units with the variable under study. To deal with suchsituations, the concept of inclusion probability inverselyproportional to size sampling scheme (IPIPS scheme)is introduced. IPIPS scheme ensures that the firstorder inclusion probabilities of units are inverselyproportional to size measures of the units. Themethod of IPIPS scheme has been obtained bymaking use of Sampfords’ Inclusion ProbabilityProportional to Size sampling scheme (IPPS samplingscheme). As an alternative, Probability Proportional toAggregate Inverse of Sizes sampling plan (PPAISsampling plan) is introduced and its properties arestudied. A unit by unit sampling is also suggestedto achieve the above proposed sampling plan.An analogue form of ratio estimator is alsointroduced, which is shown to be unbiased under thePPAIS scheme. The expressions for the second orderinclusion probabilities of the PPAIS are alsoobtained. Performance of the proposed estimatorunder PPAIS plan and IPIPS sampling scheme iscompared with alternative plans and their superiorityover other unequal probability sampling schemes isestablished thorough a simulation study on bivariatenormal populations for different correlations betweenY and X.

Two phase sampling

Estimators of both domain and population totals for anitem of interest are developed under two-phasesampling where the domain identity is realized, but theitem response is not necessarily available from a phaseI sampled unit. The optimality of sampling design isstudied considering the probability of item response,the cost of phase I versus phase II sampling, and theitem variability in the domains. Through numericalevaluations using a simulation study, the proposedestimators are shown to be more efficient than analready available estimator.

An approximately unbiased estimator of the varianceof the ratio estimator under the two-phase samplingwhich is more efficient than the existing estimatorsunder a super population model with intercept, has beendeveloped.

Multiple objective functions for minimization ofsampling variance

The concept of multiple objective functions has beenproposed for minimization of sampling variance of the

From Indian Livestock Censuses 1992, 1997 and 2003,on the basis of compiled data on power sources aswell as using data on human farm labour, average foodgrain productivity, state-wise mechanization indicators(ratio of mechanical power to total farm power) havebeen obtained and correlation coefficients betweenmechanization indicators with the average food grainproductivity have been obtained. Making use of yearlydata, the projected population of agricultural machineryand implements for future years at All-India level aswell as for Punjab state have been worked out. On thebasis of five-yearly data compiled from different IndianLivestock Censuses, projected population of agriculturalmachinery and implements for future years for AndhraPradesh, Haryana and Uttar Pradesh states have beenobtained.

Inclusion Probability Inversely Proportional to SizeSampling Scheme

Inclusion probability proportional to size samplingschemes (IPPS) are the sampling schemes in whichthe first order inclusion probabilities are proportional tosize measures. IPPS sampling scheme perform betterthan the available alternative sampling schemesprovided that the sizes of the units are positivelycorrelated with the variable under study and there isproportionality relationship between variable understudy and size measure of the units. However, situations

37


Yates-Grundy form of the Horvitz-Thompson estimatorin an optimal controlled nearest proportional to sizesampling scheme. It has been shown empirically thatthe true sample variance of the proposed procedurecompared favorably with that of the existing optimalcontrolled and uncontrolled high entropy selectionprocedures.

Agricultural Research Data Book

Agricultural research is a vital input for planned growthand sustainable development of agriculture in the country.The Indian Council of Agricultural Research (ICAR), is anapex scientific organization at national level. It plays acrucial role in promoting and accelerating the use ofscience and technology programmes relating toagricultural research and education. It also providesassistance and support in demonstrating the use of newtechnologies in agriculture.

Information pertaining to agricultural research,education and related aspects available from differentsources is scattered over various types of publishedand unpublished records. The Agricultural ResearchData Book (ARDB) 2009, which is thirteenth in theseries, is an attempt to put together main components/indicators of such information. The Data Bookcomprising of 258 Tables, is organized, for the purposeof convenience of the users into eleven sectionsnamely, Natural Resources; Environment; AgriculturalInputs; Animal Husbandry, Dairying and Fisheries;Horticulture; Production and Productivity; AgriculturalEngineering & Produce Management; Export & Import;India’s Position in World Agriculture; Investment inAgricultural Research & Education; and HumanResources under National Agricultural ResearchSystem (NARS). It also contains at the end, list ofimportant National and International AgriculturalResearch Institutions associated with agriculturalresearch and education along with their addresses,telephone numbers and e-mail addresses. This editioncontains latest information/ data as available in thecountry till up to end of November, 2009.

Programme 4: MODELING AND SIMULATIONTECHNIQUES IN BIOLOGICAL SYSTEMS

Statistical Study of Rainfall Distribution and Rainfallbased Crop Insurance

The probability distribution of unimodal data sets isgenerally obtained by using the Pearsonian system.

However, its main limitation is that each family requiresdifferent functional forms. To this end, a very versatilefamily of generalized lambda distributions (GLD) isthoroughly studied. The GLD uses one general formula,unlike Pearsonian system in which different Types(depending on the value of kappa) have differentfunctional forms. The variety of shapes offered by GLDare enumerated. Various methods for estimation ofparameters of GLD, viz. Method of moments, Methodof maximum likelihood, Discretized method, andStarship method are discussed. The goodness of fit isexamined by several methods. A brief description isalso given of the recently developed GLDEX package,which is freely downloadable. As an illustration, theprobability density function of monthly rainfall data forAssam and Meghalaya meteorological subdivision isobtained. For describing multimodal data sets, thepromising methodology of “Statistical Learning Theory”is thoroughly studied. The “tail” is estimated throughthree methods. The threshold value is determined byParametric bootstrap and Minimum mean square errorcriteria. Further, the “body” is estimated bynonparametric Structural risk minimization methodunder correlated structure. Relevant computerprograms are developed in SAS and R softwarepackages. As an illustration, monthly rainfall data formeteorological subdivision of Orissa during 1871-2006is considered. Hill’s method performed best for fitting“tail” of the distribution. Finally, estimated “body” of themultimodal distribution is shown to capture the existingmultimodality. Drought thresholds for several rainfedcrops in different districts are obtained by applyingthe Modified Barger and Thom methodology. Thismethodology is then extended to obtain surplus / excessrainfall thresholds also. Performance of the proposedapproach is also examined.

Computational Analysis of SNPs in Rice GenomeRice is the first crop to be sequenced and has a greatimpact in the field of crop genomics. Rice genome hasabout 390 million bases and its genomic information isquite useful in elucidating the genome structure andtarget genes in other crops. A web based informationsystem on functional elements of rice genome has beendeveloped. Online facilities have been created toaccess the information on Single NucleotidePolymorphisms (SNPs) at functional elements. Visualgraphic display tools have also been developed toannotate SNPs at different functional elements ofgenome. Web information system on rice functional

38


elements help facilitate users to extract sequenceinformation on promoter regions, untranslated regions,translation start sites, splice sites, exons, introns,translation stop sites, etc. A special emphasis is givenon Splice Store, which is a collection of 5 prime and 3prime splice sites. Information on classification of splicesites, position weight matrices, Phylogeneticrelationships etc. is also provided in the Splice Store.A SNP-centric functional elements database isdeveloped by integrating information on SNPs andfunctional elements. Online access facilities areprovided to study the distribution of SNPs at functionalelements of rice genome. Computational analysis ofSNPs at genes, exons, 1K upstream, splice sites,coding sequence (CDS) and untranslated regionsreveals that more SNPs are present on chromosome 2followed by chromosome 1. Light Weight GenomeViewer based visual graphic display of functionalelements, SNPs on genome and SNPs at variousfunctional elements have also been developed. Anonline BLAST facility is developed and provided to usersfor sequence alignment purposes. Few important linksfor analysis of genome and proteome data are collectedand given at one place. A website on AgriculturalBioinformatics Lab (ABL) has been developed toprovide the developed tools, on line informationsystems and important links for analysis of genome andprotecting data.

Estimation of Genetic Correlation

The heritability of traits and sample size has pronouncedeffect on the estimates of standard error and bias andboth of them decreases considerably with increase insample sizes and heritability of the correlated traits forwhole range of positive and negative genetic correlation(rg). The Root Mean Square Error (RMSE) of rg for lowlyheritable traits is found higher in 70% of cases in datasets with gamma sire effects as compared to data setswith normal sire effects. In case of moderately andhighly heritable traits the RMSE of rg are found higherin 95% and 97% of cases respectively in data sets withgamma sire effects as compared to normal sire effects.The RMSE is also found to be deceasing with increasein sample sizes and population rg for low, moderateand highly heritable traits. It is also observed that forlarge sample sizes i.e. 500 and above the differencesin two RMSE’s with gamma and normal sire effectsare very small for both moderately and highly heritabletraits.

The probabilities of inadmissible estimates areconsiderably higher in case of gamma sire effects forwhole range of genetic correlation for lowly heritabletraits and varied from 0 to 20% as compared to 0 to14%. These probabilities reduce substantially withincrease in heritability to 0.5 and varied from 0 to 3%in case of normal sire effects as compared to 0 to 10.5%in case of gamma sire effects. The sample of size ofmore than 1500, equal to 600 and 500 are essentialfor obtaining admissible estimates of rg for low,moderately and high heritable traits respectively. Inpresence of outliers the estimates of genetic correlationare highly underestimated with the result that the biasincreases considerably. The standard error in thepresence of outliers also increases considerably andfor lowly heritable traits it is found to be ranging from0.914 to 2.959 and 0.847 to 4.018 in case of gammaand normal sire effects respectively. The standard errorin general decreases as the levels of heritabilityincreases except in case of small sample sizes andranges from 0.199 to 1.701 and 0.163 to 1.179 in caseof gamma and normal sire effects respectively.The probability of inadmissible estimates of rg withnormal sire effects increase rapidly in case of lowlyheritable traits which ranges from 0.5% to 39.5% inabsence of outliers and 8.5% to 47% in presence ofoutliers. It decreases rapidly with increase in sample size.

The large sample approximation of standard errorgiven by Tallis is always underestimating the standarderror even in large samples of size 1000 andabove and hence should not be used even for largesamples of size upto1500. The predicted standarderror by Robertson’s formula is always found slightlylower as compared to Tallis expression. Baringsmall sample size the bootstrap estimates of SE arevery close to predicted SE and can be used as anestimate of SE of genetic correlation. The bootstrapestimates of standard error of genetic correlation arefound to be very close to the predicted standard errorfor sample size 500 and above in case of low heritabletraits for both positive and negative genetic correlationvalues. It can be said that the bootstrap estimates ofstandard error which are close to predicted values andcan be used to estimate the standard error instead ofapproximate formulae given in literature.

Bioprospecting of Genes and Allele Mining forAbiotic Stress Tolerance

A centralized statistical and computational genomics

39


lab facility for the analysis of genomic data has beendeveloped. Genomic sequence information on abioticstress related genes of different traits and species wascollected from public domain and a library wasdeveloped. Phylogenetic analysis of the genesresponsible for abiotic stress tolerance traits acrossspecies has been studied and further compared forconserved regions through structural visualization. Analgorithm has been developed to determine and identifyoptimum number and combination of molecular markersrequired for explaining the maximum diversity presentin the data. A database on core collection of germplasmfor rice, cucumis, lathyrus and mothbean has beendesigned and data is being populated. A website forthe project has been designed and developed (http://bioinformatics.iasri.res.in/BAMAST/BAM.html).

– Genetic advance in closed and open nucleusbreeding schemes

– Testing the homogeneity of variance-covariancematrices (Likelihood ratio test)

– D-square analysis (Oblique axis and Iterative mini-max)

– Simulation of sib data– Bootstrapping for estimation of standard error of

genetic parameters– Skillings and Mack non-parametric test.

Programme 5: DEVELOPMENT OF INFORMATICSIN AGRICULTURAL RESEARCH

Statistical Package for Animal Breeding 2.1(SPAB 2.1)

A β−version of Statistical Package for Animal Breeding(SPAB 2.1) has been developed. The package is quiteuseful for animal breeders for estimation of geneticparameters and for formulating sound breedingstrategies and selection processes. This is a modifiedversion of SPAB 2.0 which became functional in 2006.

The new programs added in SPAB2.1 are:– Application of Sanders correction and calculation

of repeatability

– Estimation of heritability for threshold traits– Recurrent selection and reciprocal recurrent

selection

All the available programs have been grouped into11 modules.

Expert System on Wheat Crop Management

Developing a system in a language better understoodby the farmers is the need of the hour. It is felt thatthe “Expert System” will increase its impact andutility in many folds if developed in Hindi. Unicodestandard (UTF-8 and UTF-16) are used as theseprovide a platform by which end user is free fromdownloading and installing a font on the local machine.Incorporating Unicode into client-server or multi-tieredapplications and websites offers significant cost savingsover the use of legacy character sets. Unicode enablesa single software product or a single website to betargeted across multiple platforms, languages andcountries without re-engineering. It allows data to betransported through many different systems withoutcorruption.

For the development, information available on varieties,diseases, insects, cultural practices are translated inHindi. The database design of the system is accordingly

40


Home Page of Hindi Module

modified. Inference mechanism is also redeveloped toaccommodate Hindi Version of the System. By applyingUnicode, two important modules i.e., variety selectionmodule and disease diagnostic module of the expertsystem have been successfully developed. All thefunctionality available in the English version of theexpert system has been incorporated in this version.The starting page of the variety selection module anddisease diagnostic module are:

written for generating cubical designs with parametersv = 8m, b = 8, r = 4, k = 4m, n

1 = m-1, n

2 = 6m, n

3 = m,

λ1 = 4, λ

2 = 2, λ

3 = 0 and tetrahedral PBIB(3) Designs

with parameters v = 6m, b = 4, r = 2, k = 3m, λ1 = 2, λ

2

= 1, λ3 = 0 where m �� and a series of two associate

Latin Square design using BIB design with parametersv = s2, b = 2b*, r = 2r*, k = sk*, λ

1 = r* + λ*, λ

2 = 2λ*,

where v* = s, b*, r* k* and λ* are parameters ofBIB design. For constructing PBIB designs, followingclasses of BIB designs have been compiled from theliterature and a class library containing computermodules for their generation has been developed:

v = 4t+1, b = 8t+2, r = 4t, k = 2t, λ=2t-1v = 4t+3, b = 4t+3, r = 2t + 1, k = 2t +1, λ=tv = v, b = vCk, r = v-1Ck-1

, k = k, v-2Ck -2

A link (http://www.iasri.res.in/WebAnalysis/index.aspx)for the online analysis of general block design has beenprovided on the home page of the Institute’s website.

Web Solutions for Partially Balanced IncompleteBlock (PBIB) Designs

A module containing the information about generationof various types of lattice designs along with theirassociation schemes with examples, steps of analyzingthese designs using SPSS and SAS, quiz, lecture notesand demonstration. Computer programs have been

The following snapshots explain the steps in analysisof data obtained using a PBIB design.

ANOVA

41


This website has integrated facility of on-line decisionsupport system, information systems, e-documentation,discussion forum, email etc. Thematic spatial mapsfor different field crops and vegetables have beendesigned from 1970 onward with respect to differenttriennium.

Knowledge Data Warehouse for AgriculturalResearch

In knowledge data warehouse during the periodunder report, multidimensional model for theIntegrated Data Mart has been designed. Modelshave been developed and implemented for on-lineanalysis and prediction / forecasting based on timeseries data to different data marts. Three typesof models i.e. trend, growth, and auto regressionare incorporated for this on-line prediction.

Multidimensional models have been designed andimplemented for on-line analysis for census data onhousehold assets for number of assets. Website ofknowledge data warehouse has been launched andall cubes are published for online analysis by the users.

Treatment Associates

Post Hoc ResultsOn-line prediction of paddy productivity (t/ha) in different districts ofPunjab through auto regression model in knowledge managementsystem

Online spatial mapping of groundnut productivity for TrienniumEnding (TE) 2000 for India

42


Features in Nodal Officer Module

Features in RMP Module

On-line implementation and analysis of different agro-meteorological indices in knowledge management system

PERMISnet-II was organized. Constant support has beenprovided to nodal officers in implementation of the system.System has been debugged in light of comments receivedfrom nodal officers. New functionalities has been addedin the system as desired by nodal officers and managersfrom the Council.

System has been designed in modular approach withdifferent access rights to different users. Informationaccess to different type of users is presented below:

Nodal Officer Module: Nodal officers after authenticationcan update and manage the data, generate reportscorresponding to their institutes. Nodal Officer modulehas many features under different categorie● Data Management● Reports on Personnel Parameters● Reports on Cadre Strength● Complete Bio-Data Report of an Individual Personnel● Selective Report provides the flexibility to generate

report based on different combinations of parameters● Monitoring Reports

Numbers of indices have been developed andimplemented subject wise for on-line analysis.Simpson’s diversification index has been calculated fordifferent districts at regular time interval to observe thecrop diversification pattern. Further, Total FactorProductivity (TFP) has been calculated at state levelto work out the contributions of research anddevelopments in agriculture for major states of thecountry.

Decision Support System for Manpower Planning-II(PERMISnet-II)Personnel Management Information System Network-II (PERMISnet-II) for ICAR is higher version ofPERMISnet. System has been redesigned anddeveloped using .NET technology. PERMISnet-II hasbeen implemented and enriched with new modulesunder the institute project Decision Support System forManpower Planning – PERMISnet. Informationcoverage in PERMISnet-II system is vast and it containspersonal, professional and referential attributes of ICARpersonnel along with information on plan wise cadrestrength and institutional parameters for differentcategories of ICAR institutions. System providesexhaustive report modules and different access rightsto different type of users which includes ResearchManager Personnel, Nodal Officers, Individual usersand General users.

PERMISnet-II system has been implemented in ICARfrom IASRI server at the address http://permisnet.iasri.res.in/. For implementation, data fromearlier PERMISnet system was incorporated intoPERMISnet-II system. Brochure was prepared onPERMISnet-II. Training and Launch workshop of

RMP Module: Research Managers at the Council havethe privilege to view information at different levels whichranges from single Institute to compiled reports of allICAR institutions and Subject Matter Divisions. RMPmodule has many features under different categories● Institute Report● Council Reports (Consolidated reports of all ICAR

Institutions)● Divisional Reports (Consolidated reports of Subject

Matter Divisions)● Complete Bio-data Report of an Individual

Selective/ Customized Report: This module is partof nodal officer as well as RMP modules. This module

43


Graphical Report Module

provides the flexibility to generate report based ondifferent combinations of parameters such as ServiceType, Designation, Discipline/ Functional Group, Sex,Qualification, Caste Category, Religion, Abroad Visits,Age, Retiring Age etc. Report can be generated forsingle institute or all institutions in the category ofSubject Matter Divisions, Zone and State.

Individual Users: Individual users after authenticationhave the following privileges● View the Bio-data covering all the parameters● Print the Bio-data● Change the Password● Download complete bio-data in MS word format

Multi dimensional Cubes: Access to this module willbe provided to RMPs. This will facilitate the policy makersto view the data on multi-dimensional parameters.

Individual User Module

Multi dimensional Cubes

Intranet Solutions for PG School IARI

PG School IARI is a deemed University and has 25disciplines in which Masters and Doctorate degreesare awarded. The present system for PG Schoolactivities involves manual processing of variousactivities. As the disciplines of PG School are physicallyscattered, a lot of time is wasted and also requiresadditional paper work. One has to contact the concernedoffices and disciplines of PG School to get or submit apiece of information. The collection and disseminationof information is not readily available. To take theadvantage of advances in the Internet technologiesand the available network infrastructure a onlinemanagement system for PG School, IARI has beendeveloped under project " Intranet Solutions for PGSchool, IARI". The system helps in achieving the PGSchool objectives by giving online access to variousresources. The system is available to students, facultymembers, scientists and administrative staff of PGSchool, IARI, It has five sub modules for managementof Courses, Students, Faculty, Aministration ande-Learning.

The system has over 300 web pages for differentfunctionalities. The system has workflows for studentadmission, faculty registration, inducting guide fromfaculty, for becoming professor from guide, adding /modifying/deleting courses under different disciplines,offering courses in trimesters, allocating faculty tocourses, allotting guide to students, advisory committeeof students, PPW of students, student trimesterregistration, ORW of students, fees, fellowship andgrade allotment. The system has discipline wise reportsfor getting information about students, faculty,

General Users: General users can view generalinformation about ICAR.● Institute List based on Institute Type (Research

Institute, Project Directorate, National ResearchCenters, Zonal Coordinating Units, National Bureau)

● Subject Matter Division wise list of Regional Station● Zone wise list of Institutes● List of Institutes in Difficult Area● List of the Directors of Institutes● List of Nodal Officers● Institutional Organizational Structure Report

Graphical Reports: Module for graphical reports hasbeen added for RMPs. This will facilitate pictorialrepresentation of compiled information.

44


A page from the Lesson “Testing of Hypothesis”

A page from the Lesson “Problem Solving, Algorithms and Flowchart”

professor, courses, courses offered in each trimester.The system has been implemented from the academicyear 2009-10. At present the system has 267 registeredstudents and 412 faculty members.

contents (Chapters, Glossary, Quiz, Power pointpresentations) for various lessons are prepared. Thelessons covered are: Testing of Hypothesis: Normal, t,Chi - square and F – Test, Sampling distributions: t,Chi-square and F. A page from the lesson “Testing ofHypothesis” is depicted as:

The system has 536 courses listed in 23 disciplines.All the students have been registered online for I, IItrimesters of academic year 2009-10. The onlinecapability of the system allowed the students, facultymembers and administrators to publish and retrieve theinformation from their respective disciplines. This hashelped the users of the system to save their time andefforts. The time so saved may be utilized for otherdevelopment activities of the PG School, scientificresearch and better education.

Screen shot of the system showing students registered for a course

Screen shot of the system showing Examination Scheme for a course

An eLearning Solution for Agricultural Educationusing MOODLEIn the course “Elementary Statistical Methods” underthe discipline of Agricultural Statistics, the standardized

In the course “Fundamentals of computers andprogramming” under the discipline of ComputerApplications in Agriculture, the standardized coursecontents are prepared on the following topics:Fundamentals of Programming, Problem Solving, Flowcharts and Algorithms, Constants and Variables, DataTypes in C and Strings and Arrays in C. A page from thelesson “Problem Solving, Algorithms and Flowcharts”is depicted as:

45


Constructing an equation in MOODLE using DRAGMATH EquationEditor

The contents of the Lessons “Fundamentals ofProgramming”, “Flow charts and Algorithms”, NumberSystems” and “Testing of Hypothesis” are integratedwith the eLearning site. The equations for these lessonsare prepared using the DRAGMATH Equation Editorintegrated with MOODLE. Construction of an equationusing the editor is shown below:

The website (http://elearnagri.iasri.res.in) is beingmaintained and back up is being taken up regularly.The common template for course material collectionfrom faculty members of IASRI has been designed andhas been mailed to all the scientists/faculty membersof the institute for preparing the courses they areteaching. The proceedings of the workshop conductedunder the project have been published under theWorkshop Series of the institute.

SPAR 3.0Programs were developed for the following modules(a) Basic Statistics (Descriptive Statistics) (b) DataManagement (c) Three-Way Cross Analysis (d) NorthCarolina I, II, III (e) Line × Tester (with /without) parents(f) Some sub-modules of Web online help of SPAR 3.0completed using C#/ASP.NET in .NET Technology.

Project Information & Management System of ICAR(PIMS-ICAR)

To check duplication in research projects both atdivisional as well as inter divisional level, ProjectInformation & Management System of ICAR (PIMS-ICAR) has been developed and hosted at http://pimsicar.iasri.res.in . The system will act as a decisionsupport system and would be quite useful toacademicians, planners, policy makers, scientists/technologists and other stake holders in the field ofagricultural sciences and technology.

The Requirement Analysis is completed on the basisof existing RPF-I, II, and III. The designing of thedatabase is completed according to requirementanalysis. To check duplication of research projects,Keyword Based Approach and Ontology BasedApproach are considered for the development ofthe mechanism. PIMS-ICAR is launched on thenet in August 2009 for testing purpose. A mechanismfor duplication detection of research is developed andpart of the same is translated into the system. Thesystem can now extract Keywords from the title,objective, and activities of the project and can matchacross all the ongoing projects. Nodal Officers for PIMS-ICAR have been identified in 87 ICAR institutions.A workshop of Nodal Officers in Delhi based Institutesand nearby Delhi was organized and the suggestionsand observations of the Nodal Officers of PIMS-ICARwere noted during the workshop. A reference guide fordata management has been prepared and distributedto the Nodal Officers. Some of the input forms havebeen revised according to the feedback from theworkshop. The ProjectID and Password are issued tothe Principal Investigator of all the projects at IASRI.The data of the projects is being entered. As desiredby DDG (Agricultural Engineering), ICAR a briefproforma is designed for submission of researchprojects data for checking duplication of research inthe ICAR as per RPF-I. This proforma is sent toDirectors of all the ICAR Institutions for seeking theircomments/suggestions. Suggestions received havebeen incorporated into the system.

Expert System on Seed Spices

The system is being developed for 10 seed spices incollaboration with National Research Centre on SeedSpices, Ajmer. Two modules of the system aredeveloped. The system can be considered as a

46


Home Page of Expert System on Seed Spices

Homepage of Expert System of Maize

combination of ten expert systems. Each seed spicecrop has four different modules of variety selection,crop protection, cultural practices and harvest. Inaddition to this one separate module for knowledgemanagement has been added.

Expert system for Maize Crop

Expert System for maize crop aims at developing aweb enabled knowledge base system for effectivedissemination of maize knowledge and technology. Thesystem is conceived as a model of existing ExpertSystem of Extension. For this, information is collectedin electronic and/or printed forms on maize varieties,management of maize diseases, cultivation of maize,integrated pest management, management andharvesting of baby corn and post harvesting technology.The compilation of maize information is done in

consultation with the experts from Directorate of MaizeResearch (DMR), New Delhi. The material received isstudied to identify the characters to be included in thesystem for variety, disease, insect and weed. Theinvestigators at DMR are also encouraged to take thepictures of the maize crop from the field at regularintervals. This has enriched the system with the photosfor different stages of crop growth and also providedthe pictures for identification of diseases and pests.The system has an online knowledge acquisitionmodule for maize experts. Post Harvesting Technologysubsystem is also developed and integrated with theexisting system.

The Library of IASRI is one of the Regional Libraries ofNARS (National Agricultural Research System) of thecountry. The Library has an excellent print andelectronic resource base in the fields of AgriculturalStatistics, Computer Applications, AgriculturalEconomics and allied sciences to support teaching,research and consultancy in the relevant areas. This isa sole referral library in Agricultural Statistics andComputer Applications in India. It caters to theinformation needs of students, faculty, researchers,scientists and trainees etc. not only of IASRI but alsofrom different Institutes of ICAR and State AgriculturalUniversities under NARS both in conventional as wellas electronic format.

The Library Advisory Committee plays an important rolein management of the Library and it clears proposalsrelating to enrichment of resources of the librarysuch as books, journals, on-line bibliographical,statistical, abstract and CD-ROM databases as well asinfrastructural development etc. The Library Advisory

Committee for the year 2009-10 was as under:

Dr. VK Bhatia Chairman

Dr. VK Gupta Member

Dr. UC Sud Member

Dr. PK Batra Member

Dr. Rajender Parsad Member

Dr. PK Malhotra Member

Dr. Ranjana Agrawal Member

Dr. Prajneshu Member

Dr. Amit Kumar Vasisht Member

Sh. AK Chaturvedi Member

Capt. Mehar Singh Member

Sh. Krishan Kumar Student Representative

Dr. (Mrs.) P Visakhi Member Secretary

The internal administration and organization of theLibrary & Information System is supervised byDr. (Mrs.) P. Visakhi, Librarian under the guidance ofDr. P.K. Malhotra as Scientist-in-Charge, Library.

Library and Documentation

48

Library and Documentation

The following Computer Activities were undertaken:

● All resources added during the year in the libraryhave been classified, catalogued and bar-codedand updated in the Library BibliographicalDatabase using “Alice for Windows” LibraryManagement software.

● Library users were given hands-on trainingwhenever necessary on the use of librarycomputerized services/resources.

● All trainees of the short term training programmesheld in the Institute were given lectures and Hands-on training on “On-line Library Information Services”.

Library subscribed/renewed the following Biblio-graphical, Statistical and Abstracting on-line portalsduring the period:– MathSciNet (http://www.ams.orgmathscinet.com)– Indiastat.com(http://indiastat.com)– Indian Harvest (http://lib.iasri.res.in/cmie.asp)– Developing Library Network (http://delnet.nic.in)– Sciencedirect (http://www.sciencedirect.com)– Consortium for e-resources in Agriculture (CeRA)

(http://www.cera.jccc.in)

Physical Verification of Library Holdings: Stock oflibrary documents have been verified by the Committeespecially constituted for the purpose by Competentauthority and preliminary report has been received inlibrary for further necessary action.

During the year, the library provided following servicesto its users.

Reprographic Service (Manuals)

Periodicals● Indian Journals - 39 (Print)

● Foreign Journals - 49 (Print)

● Computerized Services

- On-line Catalogue - OPAC

- Archival Database (Digitized Thesis and Old &Fragile Journals) - 2

- On-line Journals - 40

- On-line Bibliographical Database - 7

- CD-ROM Database (On-line and Off-line) - 25

- Internet Search

- On-line Enquiry (OPAC)

- Current Awareness Service (New Arrivals)

- On-line Reservation of Documentation

- On-line User Profile Service

Statistics Relating to the Library

Item Number

Number of books added (English) 69Number of books added (Hindi) 11Number of grey literature added 125Number of Indian journals subscribed 39Number of Foreign journals subscribed 49Number of on-line journals subscribed 40(Indian and Foreign)Number of electronic and printed theses added 17Number of publications issued from the library 14,500Number of users visited library website 31,000Number of articles (E+P) received from DELNET 47Number of books received on inter-library loan 25through DELNETNumber of outside users accessed e-services in 600library premises (NARS)Number of publications lent out on inter-library loan 115Number of readers visited and consulted the library 15,900Number of scientific and technical papers 11,500reprographed (pages)Number of CD-ROM added 40Number of articles provided under CeRA document 300deliveryServices including digital format internet/databases 75,000access searches

The Full text of M.Sc. and Ph.D. Theses added duringthe period have been digitized and added in onlinedigital format. Library has updated its well featuredwebsite http://lib.iasri.res.in which is accessible acrossthe world in all 365 days.

● Directorate of Sorghum Research, Hyderabad

�-designs have been suggested for the AVHT andIVHT trials conducted under the aegis of All IndiaCo-ordinated Sorghum Improvement Programme.These designs are resolvable block designsand have been generated through computeraided search. The parameters and layouts ofdifferent �-designs recommended are:

(i) v = 33, b = 9, r = 3, k = 11, A-efficiency = 0.9682,D-efficiency = 0.9860 (IVHT)

REPLICATION 1Block-1 1 4 7 10 13 16 19 22 25 28 31Block-2 2 5 8 11 14 17 20 23 26 29 32Block-3 3 6 9 12 15 18 21 24 27 30 33



Different randomized layouts of this design wereprovided for 16 locations.

(ii) v = 28, b = 12, r = 3, k = 7, A-efficiency = 0.9603, D-efficiency = 0.9812 (AVHT shallow soil)

REPLICATION 1Block-1 1 5 9 13 17 21 25Block-2 2 6 10 14 18 22 26Block-3 3 7 11 15 19 23 27Block-4 4 8 12 16 20 24 28


Technology Assessed and Transferred

50

Technology Assessed and Transferred


(iii) v = 16, b = 6, r = 3, k = 8, A-efficiency = 0.9683, D-efficiency = 0.9859 (AVHT deep soil )

REPLICATION 1

Block 1 1 3 5 7 9 11 13 15Block 2 2 4 6 8 10 12 14 16

REPLICATION 2

Block 1 1 4 5 8 10 12 13 16Block 2 2 3 6 7 9 11 14 15

REPLICATION 3

Block 1 1 4 6 8 9 11 14 15Block 2 2 3 5 7 10 12 13 16

Splice Site Collection & Rice Genome

● A web-based functional elements informationsystem and SNP-centric functional elementsdatabase of rice genome (http://bioinformatics.iasri.res.in/BAMAST/ BAM.html) hasbeen developed for the users. Visual graphicdisplay tool (genome browser) for annotation offunctional elements on rice genome has also beendeveloped. Some screen shots for the InformationSystem are:

For human resource development programmes, theInstitute conducts post graduate teaching and in-servicecourses in Agricultural Statistics and ComputerApplications. Institute has M.Sc. and Ph.D. programmesin Agricultural Statistics since 1964 and M.Sc. inComputer Application since 1985-86. A brief descriptionof human resource development during the yearthrough degree courses, certificate courses, ad-hoctraining programmes, customised national andinternational training programmes are given in thesequel.

DEGREE COURSES

The Institute continued to conduct the following degreecourses in collaboration with the Post Graduate Schoolof Indian Agricultural Research Institute (IARI) whichhas the status of a Deemed University:

(i) Ph.D. (Agricultural Statistics)

(ii) M.Sc. (Agricultural Statistics)

(iii) M.Sc. (Computer Application)

Both Ph.D. and M.Sc. students are required to studycourses not only in Agricultural Statistics but also inAgricultural Sciences like Genetics, Agronomy,Agricultural Economics, etc. The courses inMathematics, Agricultural Statistics and ComputerApplication are offered at this Institute while the coursesin Agricultural Sciences are offered at IARI.

The eligibility qualification for admission to Master’sdegree in Agricultural Statistics is a Bachelor’s degreewith atleast 60% marks or its equivalent overall gradepoint average (OGPA) in Agriculture/Horticulture/Forestry/Agroforestry/Sericul ture/Agricul turalMarketing/B.Sc. (10+2+3 System). For admission toMaster’s degree in Computer Application, the eligibilityqualification is a Bachelor’s degree with atleast 60%marks or its equivalent overall grade point average(OGPA) in Agriculture/Computer Science/AgriculturalEngineering/B.Sc. (Horticulture), Veterinary Science,Home Science, B.Sc. (Forestry)/B.Sc. with Maths./Statistics/Physics/Biology/B.Sc. (10+2+3 System).

Education and Training

52


Further, for admission to Doctor’s degree in AgriculturalStatistics, the eligibility qualification is a Master’s degreewith atleast 60% marks or its equivalent overall gradepoint average (OGPA) in Agricultural Statistics/Statistics/Mathematical Statistics/Bio-Statistics of IVRI/Professional Statisticians’ Certificate Course (PSCC)from IASRI.

Number of students admitted/completed variouscourses are:

(a) Ph.D. (Agricultural Statistics)Admitted : 7Completed : 3

(b) M.Sc. (Agricultural Statistics)Admitted : 8Completed : 5

(c) M.Sc. (Computer Application)Admitted : 8Completed : 8

Brief of research work carried out by students whocompleted various courses during 2009-10 is as follows:

Ph.D. (Agricultural Statistics)

i) Dharm Nath Jha

A study on spatial regression models undermeasurement errors framework

Measurement Errors (ME) in explanatory variables ofclassical regression model makes the estimators ofregression coefficients biased and inconsistent. Furtherfor the variables of interest of geographical in nature,regression coefficients do not remain fixed over spaceand usual regression analysis takes no account ofspatial location in its analysis. Therefore, a newtechnique called Geographically Weighted Regression(GWR) is used in which estimates of regressioncoefficients are based on local relation instead of globalrelations among spatial variables of interest. Estimationof regression coefficients when spatial explanatoryvariables with ME are fixed or random in GWR modelis expected to provide efficient estimates as comparedto corresponding usual regression model. A FunctionalSpatial Regression (FSR) model and a Structural SpatialRegression (SSR) model under ME have beenproposed for estimation of regression coefficients incase of spatial variables. Explanatory variables underFSR model are assumed to be fixed while it is random

in case of SSR model. Modified estimates of regressioncoefficients are proposed following Ordinary LeastSquares (OLS), Generalized Least Squares (GLS),Maximum Likelihood Estimation (MLE) and Method ofMoment Estimation (MME) approaches. Through spatialsimulation it has been shown that proposed estimatorsare unbiased, consistent and comparatively moreefficient than corresponding usual estimators.

Guide: Dr. Anil Rai

ii) Nurnabi Meherul Alam

Some contributions to design and analysis ofmixture experiments

Experiments in which the response is a function of theproportions of the components (constituents) presentin the mixture and not of the total amount of the mixture,are called mixture experiments. A lot of literature isavailable for single factor mixture experiments. There,however do occur experimental situations in which theexperimenter is interested in studying the effect ofmixtures of two or more independent factorssimultaneously. Such type of experiments are knownas multifactor mixture experiments.

In agricultural experiments, the behavior of differentingredients is generally quadratic in nature, therefore,designs for multifactor mixture experiments have beenobtained so as to fit the second order response surfacemodel. A method for obtaining unique parameterestimates for the second order model for multifactormixture experiments has been developed. Methodshave been developed to construct designs with numberof runs less than those required for usual kroneckerproduct designs from single factor mixture experiments.Simultaneously it has been taken care of that it ispossible to fit the second order mixture models.Thedesigns generated from these methods of constructionshave been evaluated with G-efficiency and/or relativeA-efficiency and perpoint relative A-efficiency.A catalogue of designs has been prepared for n ≤ 4;pi ≤ 4, where n is the number of factors and pi is thenumber of constituents for i th factor.

For multifactor mixture experiments, situations may arisewhere restrictions are imposed on one or more thanone components of different factors. Four methodsof construction of designs for multifactor mixtureexperiments under restricted region usingtransformation/projection of response surface designs

53


have been given. Methods of construction of designsfor multifactor mixture experiments have been given forthe cases where upper bound or lower bound restrictionsare imposed on one component of each factor andboth lower bound and upper bound restrictions areimposed on some of the components for each factor.SAS code for obtaining designs for multifactor mixtureexperiments has been developed and catalogue ofdesigns has been prepared for n ≤ 3; pi ≤ 4.

In many mixture experiments the product characteristicsdepend not only on the proportions of the componentsin the blend but also on the processing conditions. Twotypes of models for multifactor mixture experiments inthe presence of process variable(s) have been given.Based on these models three methods of constructionof designs for multifactor mixture experiments in thepresence of process variable(s) have been constructedso that one can estimate the model parametersorthogonally and the G-efficiency of the resulting designis high.

Guide: Dr. PK Batra

iii) Dwijesh Chandra Mishra

On some aspects of estimation of geneticparameters under selection pressures and modelinadequacy

Classical statistical methods generally used in theanalysis of data assume that the data is a randomsample. This assumption is generally violated and thedata is a result of continuous selection of individuals.The means and variances of random variables are thusdifferent for selected individuals than those in theunselected one. This, therefore, advocates the use ofspecial statistical techniques wherein the effects ofselection are incorporated in the procedures ofestimation of genetic parameters.

In addition to selection, estimates of genetic parametersare also influenced by not considering complete linearmodel. For a given set of experimental data, theestimates of variance components are affected by bothstatistical procedures and analytical linear models beingused. Previous studies reported biases when usingincorrect models. Therefore, model inadequacy alsodemands special statistical techniques to quantify thisbias for different values of true genetic parameters.

Further the underlying distribution of the observationsmay not be normal and as such traditional methods maynot be suitable to tackle the problems arising from thenon-normality. Inspite of the non normality of the data,there may be some abnormal or aberrant observationsin the data or some data may be missing which alsodemands the search for robust methods of estimationof genetic components of variances and covariances.

In the present investigation, consequence of estimationof variance components has been discussed when datacomes from selected population. Expressions forestimating variance components and consequentlyheritability are developed after incorporating the effectsof selection in the model. Proposed method has beencompared with the existing methodologies for estimationof variance components like Analysis of VarianceEstimation (ANOVA), Maximum Likelihood Estimation(MLE), Restricted Maximum Likelihood Estimation(REML) and Minimum Variance Quadratic Estimation(MIVQUE) with the help of simulated data for differentpopulation parameters. It has been demonstrated thatthe use of proposed methodology results in gain inprecision of estimate of heritability over the existingtraditional methodologies.

Problems related with estimation of variancecomponents have also been discussed, when model isinadequate. An explicit expression of bias of the estimateof heritability has been developed in the case of modelinadequacy. Results of proposed method along with theexisting methodologies for estimation of variancecomponents like ANOVA, MLE, REML and MIVQUE areobtained in different cases of model inadequacies.Simulated data generated by taking suitable parametersfor half-sib as well as full-sib genetic models has beenused. It has been demonstrated that bias and MSE ofthe estimates decrease with increasing the number ofsignificant fixed effects in the model.

A comparative study has been made to examine theinfluence of outliers, missing observations and non-normality on the estimates of genetic parameters in thepresence of selection pressure and model inadequaciesby using a robust estimator called RAVE estimator forhalf-sib model.

Guide: Dr. VK Bhatia

54


M.Sc. (Agricultural Statistics)

i) Arpan Bhowmik

A study on logistic regression modeling forclassification in agriculture

Classification and prediction in agricultural systems arequite useful for planning purposes. In this study, logisticregression modeling has been employed forclassification purposes in the field of agriculture. Thedata pertains to the area of agricultural ergonomics withdependent variable as the presence or absence ofdiscomfort for the farm labourers in operating farmmachineries along with associated quantitative andqualitative regressors. From the different possiblevariable subset datasets, only appropriate logisticregression models that best fit these datasets have beenselected for further study. Relevant goodness of fit andpredictive ability measures have been utilized forevaluating the fitted models. A single best regressor i.e.load given to the farm machinery during operation hasalso been identified by employing variable selectionbased on collinearity diagnostics and stepwise logisticregression. Comparison made between the length ofconfidence intervals of estimates from MaximumLikelihood Estimation (MLE) and quadratic bootstrapmethods upon the original sample using the single bestregressor revealed that the latter is better than theformer as quadratic bootstrap estimates has smallerlength of confidence intervals. In addition, resamplingbased estimation method viz. quadratic bootstrap hasbeen applied for estimating the unknown parameters ina simple logistic regression model under a simulationstudy whose parameter estimates has less bias thanthat obtained using the conventional MLE procedurewithout increase in their corresponding estimatedvariances. Also when the classificatory performancesof the logistic regression models (using the bestregressor) fitted using both MLE and quadratic bootstrapapproaches are compared, the results came out to beat par under the two approaches. Classifications of thehold-out datasets revealed that results obtained usinglogistic regression models are found to be better whencompared to those obtained from discriminant functionanalysis method. Moreover, when comparisons aremade among the MLE based logistic regression models,the model with the single best regressor come outto be the best. The study revealed that logistic regressionmodeling can be employed as a viable alternative forclassification purposes in the field of agriculture.

Guide: Dr. Ramasubramanian V

ii) Sankalpa Ojha

A study on outliers in multi-response experiment

Outlier(s) in a set of data is (are) defined to be anobservation that is inconsistent with the rest of the data.If the data set contains outliers the conclusion drawnfrom the experiments may be wrong. Outliers may arisein the experimental setup where observations are takenon more than one response. Cook-statistic has beendeveloped for two likely situations of occurrence ofoutliers in multi-response experiments. In the firstsituation, more than two outlier observation vectors havebeen considered. For developing Cook-statistic, mean-shift outlier model has been considered, that is, meanof each of the outlying observations has been shiftedfrom the mean of the clean observations. A generalexpression of Cook-statistic for detecting any t outlierobservation vectors has been obtained. Two upperbounds of Cook-statistic have also been obtained. Theseupper bounds help to reduce the computation of allpossible set of t outlier observations vectors. It isconcluded that if these upper bounds are not statisticallysignificant, then there is no need to compute all possibleset of vectors. Developed statistic is applied to realexperimental data. For applying to data only two outlierobservations vectors have been considered. A pair ofsuch vector is identified as outliers. In the second casethe situation where observations from all the responsesmay not be outlier is considered. A general expressionof Cook-statistic has been obtained for detecting anyk observations from each of any t observation vectorsas outliers. Appropriate expressions for some particularcases are obtained. The developed statistic is thenapplied to the same data set by considering that anytwo observations from each of any two observationvectors are outliers. SAS codes have been written forapplying the above procedures for detection of outliersin multi-response experiments.

Guide: Dr. Lalmohan Bhar

iii) N Mohondas Singh

Some empirical investigations on statisticalproperties of growth curvesGrowth is an important phase in the life of animals whichinfluences different forms of production such as milk,meat, etc. in the later ages. The relationship betweenbody weight and age is important particularly in meatproducing animals. Since a series of weight-age datapoints are analytically difficult to interpret, it is, therefore,desirable to study statistically the growth of animals.

55


On the basis of bootstrap samples the distributions ofthe goodness of criteria R2 (Determination Coefficient),RMSE (Root Mean Square Error) and ARR (AbsoluteReduction Ratio) are found to be non normal. Basedon these statistical measures Von bertalanffy model isselected as the best model to describe growth patternin given body weight data of goat.

Inheritance of growth curves is critical for understandingevolutionary change and formulating efficient breedingplans. The growth parameters are important in the sensethat they are good indicators of the growth pattern. Thegenetic parameters of growth parameters are necessaryto examine the potential usefulness of the growthparameters as selection criteria. So it is important tohave the complete information of genetic parametersof the curve parameters. In the present study thestatistical properties of the genetic parameters of thegrowth curve parameters have been discussed and thedistributions of these genetic parameters are foundto be non-normal. The genetic correlation betweenthe mature weight and maturity rate has been found tobe moderately negatively correlated which indicatesthe selection of animals having higher maturity ratecould lead to lighter mature weight. The heritability ofmature weight are found to be highly heritable indicatingthat the mature weight can be used for selection purposes.

Guide: Dr. AK Paul

iv) Ankur Biswas

Variance estimation using Jackknife method inranked set sampling under finite populationframeworkIn experimental settings where measuring anobservation is expensive, but ranking a small subset ofobservations is relatively easy, Ranked Set Sampling(RSS) can be used to increase the precision of theestimators. The majority of research in RSS has beenconcerned with estimating the mean in the context ofinfinite population. Estimating the variance in case ofRSS has been found to be cumbersome in the contextof finite population. Therefore, an attempt was made todevelop variance estimation procedures using Jackknifemethod in RSS under finite population framework. Threedifferent variance estimation procedures have beendeveloped. The efficiency of these developed varianceestimation procedures has been compared amongthemselves through a simulation study. Theperformance of variance estimation procedure following

cycle based approach has been found to be at par withstrata based approach for varying number of cycles aswell as for varying ranks. The variance estimationprocedures following cycle based approach and stratabased approach have performed better than thevariance estimation procedure following unit basedapproach for varying number of cycles as well as forvarying ranks.

Guide: Dr. Tauqueer Ahmad

v) Prabina Kumar Mehar

A study on multivariate outlier detection and itsapplication in breeding dataIdentification and proper treatment of multivariateoutliers have become increasingly important in the areaof agricultural statistics, particularly, in breeding dataanalysis. In literature methods are available for detectionof multivariate outliers and their treatments have beenconsidered. Four methods of multivariate outlierdetection (one commonly used & three computerintensive methods) have been considered. Thesemethods are compared for their performance based onprobability of identified outliers from outlier distribution(correct outliers) as well as probability of outliers from“clean data” distributions (wrong outliers). Also theperformance of all the methods has been assessed byconsidering shift outliers alone, scale outliers alone andboth shift and scale outliers in the samples generatedthrough simulations. The probabilities have beencalculated over thousand simulations. The averageprobabilities of correct outliers and wrong outliers alongwith their standard errors are also obtained. The methodwhich identifies high average probability of correctoutliers and low average probability of wrong outliershas been judged as the best one. The identified bestprocedure has been applied on real data obtained frommulti-location trial multivariate data on maize.Multivariate outliers are then treated by deletion followedby multiple imputations. The treated data is furtheranalyzed for identifying stable maize genotypes.

Guide: Dr. AR Rao

M.Sc. (Computer Application)

i) Rakesh Kumar Meshram

Information system for varietal experiments(ISVE)

The All India Coordinated Wheat Improvement Project

56


(AICWIP) has a main mandate of accelerating theprocess of varietal development. But the lack ofinformation on the availability of best varieties is one ofthe main reasons for its limited use. Sometimes, thefarmers may not be aware of the right variety, right timeand right locations etc. Due to this constraint, farmersmay not be able to get expected results after using it.As varieties are zone specific, hence proper selectionof the varieties according to their locations is veryimportant for better yield. Information System for VarietalExperiments (ISVE) is a Web-based Information Systemto provide information to extension personnel, students,researchers, etc. ISVE has a simple query and reportgeneration module to provide the information aboutzone, centres, variety, trial type, trial series etc. even inthe printable formats.

The software has one level of authentication i.e.administrator. Administrator has the privilege to add,modify or delete information from the database. Userscan ask questions regarding any information or aboutthe software to the concerned experts by sending ane-mail. Users can also view some frequently askedquestions (FAQs).

ISVE has been developed using ASP.NET. It is an easyand effective tool to develop web based applications.Back End is developed using SQL Server 2000. It is theRelational Database Management System (RDBMS)widely used for its simplicity and ease in operation.

Guide: Dr. VK Mahajan

ii) Ramjilal Sharma

Online information system for intercroppingexperiments (OISIE)

OISIE is an attempt to add a new web baseduser-friendly, information system for Intercroppingexperiments. It is developed for informationmanagement of all the intercropping experimentsconducted in India.

OISIE has been designed using three-layeredarchitecture. Client Side Interface Layer is in HTML andJavaScript, Server Side Application Layer uses JavaServer Pages (JSP) and Java Database Connectivity.Database Layer is implemented using Microsoft SQLServer 2000. OISIE can be implemented as a network-based system with a server at a central location.

OISIE can run at any node of the Internet through aweb browser. Security features are provided in such away that only authorized person can access thedatabase. There is provision for administrator to insert,update and delete the information.

OISIE provides information regarding Intercroppingexperiments including experimental site history, locationdetails, design details, objective of the experiment,treatment details, soil types and their texture, seasonin which the experiment is conducted, basal conditiondetails which in turn includes sowing dates, seed rates,spacing, basal manuring, preparatory cultivation,planting methods, irrigation details date of harvest forboth main crop and inter crop and some generalinformation’s like disease and pest attack, cropscondition, etc.

OISIE also provides search facility for centre information,experiment information, treatments applied, main cropand inter crop information, fertilizer doses, designinformation, experimental data in case of unanalyzedexperiments and results in case of analyzed experiments.

User can also view customized results on variousaspects of the intercropping experiments and caninteract with concerned people through e-mail. On-linehelp is also provided to help administrators and usersboth.

Guide: Dr. IC Sethi

iii) Robin Singh

Software for online analysis of split-plot designsSplit plot design is often used by the experimenters,where ever the objective is to compare two or morefactors requiring different plot sizes for operationaldifficulties. Factor(s) which require larger plot size areapplied to the bigger plot called main plot and the onewhich require smaller plot size are applied to the smallerplot called sub-plot. The experimenter may also havetreatments either in the main plot or in sub-plot whichare not part of factorial set up and are called control orextra treatments. From the review of literature onsoftware’s available for data analysis, it appears thatno software is readily available to the agriculturalexperimenter for carrying out the analysis of datagenerated under such type of experiments, particularlyin situations when there are more than two factors anda control/extra treatments.

57


The software developed has the facility to analyze splitplot design upto four factors with or without controltreatments. The control/extra treatments are providedin the sub plots. It also provides facility to create newdata files for analysis using split plot design up to fourfactors with or without control/extra treatments.

Guide: Sh. HS Sikarwar

iv) Ashutosh Karna

Software for fitting of distributions

An indigeneous software has been developed thatcan fit certain number of discrete and continuousdistributions as per the real life situations and fit thetheoretical data using Kolmogorov - Smirnov and Chi-Square tests of goodness of fits, once the parameterhave been estimated (broadly using MLE techniques).The software has been developed using Visual C# 2008language with ASP.NET 3.5 framework. Data file formatssupported by this software are .txt and .xls. In additionto fitting of distribution, the software can also be usedinteractively to draw Quantile-Quantile plot forcontinuous distributions; and computing various specialfunctions (including Gamma, Beta, and IncompleteGamma etc.) at runtime. A user friendly help file withstep-by-step method for using the software has alsobeen provided.

Guide: Dr. RC Goyal

v) Ragini Singh

Development of statistical package for analysis ofcropping system experiments

Statistical Package for Analysis of Cropping SystemExperiments (SPACSE) is a web based software for theanalysis of the data collected from farmers’ field trialsat various NARP Zone level and the data collected fromOn-Station trials. The intent of SPACSE is to provide aneasy-to-use statistical analysis facility for the noviceuser. SPACSE supports randomized complete blockdesigns.

SPACSE provides the analysis and consolidated reportfor grain yield, straw yield, N uptake of grain yield, Nuptake of straw yield, P uptake of grain yield, P uptakeof straw yield, K uptake of grain yield and K uptake ofstraw yield for On-farm experiments. It provides theanalysis and consolidated report for grain yield and straw

yield for On-station experiments. The result for analysisinclude character analyzed, crop-sequence, year, typeof experiment, variety, treatment details and raw andconverted data, ANOVA, mean table, standard error andcritical difference for cropping systems experiment. Theconsolidated report for On-farm experiments is year-wise and for On-station trials is experiment wise. There isno restriction on the number of replications and treatments.

The overall design of the system can be regarded asthree-layered architecture. Client Side Interface Layeris implemented in HTML and JavaScript. Server SideApplication Layer is implemented in Java Server Pagesand Java Database Connectivity. Database Layer isimplemented in Microsoft SQL Server 2000. SPACSEcan be implemented as a network-based system so thatinformation is available on-line.

Guide: Dr. IC Sethi

vi) Sarita Patle

Web based software for estimation of regressioncoefficient

A sample survey is a process for collecting data on asample of observations which are selected from thepopulation of interest using a probability-based sampledesign. Statistical software, mostly, assumes thatthe observations are selected independently andthat each observation has the same probability ofbeing selected and does not take into account fewcommon characteristics of survey data: (i) clustering ofobservations, (ii) stratification, etc.

Therefore, a web based Software for Estimation ofRegression Coefficient (SERC) for survey data has beendeveloped. This software can upload the data fromMS-excel/ MS-access files. Data files can be opened,deleted and saved as done in other web applications.SERC has the two analyses modules i) descriptivestatistics (mean, variance, and coefficient ofvariance), ii) estimation of regression coefficient andestimate of its variance. SERC can analyze the dataif it is obtained using simple random sampling andstratified sampling designs. On line help is providedregarding formulae used for various samplingschemes and using SERC. SERC is developed usingASP.NET.

Guide: Dr. VK Mahajan

58


A participant receiving the certificate during Valedictory Function ofSenior Certificate Course in Agricultural Statistics and Computing

vii) Amreshsing Ashoksing Rajput

Development of decision support system forsurface runoff estimation

Computation of surface runoff is difficult as it dependsupon several factors concerned with atmospheric andwatershed characteristics. To facilitate this, a DecisionSupport System for Surface Runoff Estimation (SURE)has been developed which is a web based software.SURE provides estimate of surface runoff based onCurve Number, Rational, Infiltration, Cooks andEmpirical methods. The intent of SURE is to provide aneasy-to-use hydrological program for the novice uses.SURE provides amount of available water throughrainfall that help in the design of control structuresrequired to reduce soil erosion. SURE also maintainsinformation about different land use patterns, differenttreatment patterns, soil type, different zones and stationsetc. This will help user for location specific estimationof surface runoff. It will generate reports for zones andstations, curve number and rational method accordingto user query.

The overall design of the system can be regarded asthree-layered architecture consisting of Client SideInterface Layer, Server Side Application Layer andDatabase Layer. There is provision to insert and updatethe information.On-line help is provided for bothadministrator and user. SURE will be implemented asa network-based system so that information is availableon-line.

Guide: Dr. PK Malhotra

viii) Mali Snehal Sukhadev

Development of decision support system forsprinkler irrigation system (SISD)

SISD is a Web-based Decision Support System to assistthe user in designing sprinkler irrigation system. SISDhas online report generation module to provide thelayout of area to be irrigated per day, specifications ofsprinkler irrigation system etc. even in the printableformats.

The software has one level of authentication i.e.administrator. Administrator has the privilege toadd, modify or delete information from the database.Users are free to get information using this software.Users can ask questions regarding any informationor about the software to the concerned experts by

sending an e-mail; this facility is included in the softwareitself.

SISD is developed using ASP.NET. Database part isdeveloped using SQL Server 2000.

Guide: Dr. RC Goyal

CERTIFICATE COURSE

Senior Certificate Course in Agricultural Statisticsand Computing: 7 participants

The institute continued to conduct Senior CertificateCourse in Agricultural Statistics and Computing,organized for the benefit of research workers engagedin handling statistical data collection, processing,interpretation and employed in research Institute of theCouncil, State Agricultural Universities and StateGovernment Departments, etc. and foreign countriesincluding SAARC countries with the main aim to trainthe participants in the use of latest statistical techniquesas well as use of computers and software packages.The course is comprised of two independent modulesof three months duration each. The main topics coveredunder the course include Statistical Methods and OfficialAgricultural Statistics, Use of Computers in AgriculturalResearch, Sampling Techniques, Econometrics andForecasting Techniques, Design of Experiments andStatistical Genetics.

During the period the course was organised during 06July 2009 to 26 December 2009 (Module–I: 06 July 2009to 26 September 2009 and Module–II: 12 October 2009

59


to 26 December 2009). Two officers participated inModule–I only, one officer participated in Module–II onlyand four officers participated in both the modules.

NATIONAL/INTERNATIONAL TRAINING PROGRAMMES

Programme under Centre of Advanced FacultyTraining

A twenty one days training programme on RecentAdvances in Web Technologies for InformationManagement in Agriculture was organized during 16February - 08 March 2010. Fourteen participants fromICAR Institutes and State Agricultural Universitiesattended the training programme. Ms. Anu Sharma wasthe Course Director and Sh. SB Lal was Co-CourseDirector of the training programme. This training wasorganized to provide knowledge in designing anddevelopment web applications and services usingMicrosoft .NET technology with advanced scriptinglanguage like Javascript, Cascading Style Sheets andAJAX.

databases, sequence alignments, genome browsers,SNPs, comparative genomics, machine learningapproaches, HMMs, proteomics, QTLs, markerassisted selection, analysis of molecular variance(AMOVA), whole genome association (WGA) andbioinformatics software and tools. A total of 25participants from ICAR institutes / SAUs representing13 states, cutting across different disciplines likeMolecular Biology & Biotechnology, Biochemistry,Breeding & Genetics, Computer Application, Statisticsand Microbiology, participated in the Winter School.Dr. B.C. Barah, Director, NCAP was the Chief Guestfor the inaugural session and Dr. Arvind Kumar, DeputyDirector General (Education), ICAR was the ChiefGuest for the valedictory session. Dr. A.R. Rao wasthe Course Director for the Winter School.

International Training Programmes

● An International training programme on ExperimentalDesigns and Data Analysis for the CAC Staff atTashkent was organized by Dr. Rajender Parsad asCourse Director during 01-05 June 2009 while hewas invited as Consultant Biometrician withComputer and Biometrics Services Unit, ICARDA,Syria. Sh. Khaled–EI–Shamma from ICARDA,Syria acted as Course Co-Director. There were 8participants in this training programme who wereresearch staff of International Water ManagementInstitute, International Potato Center andInternational Center for Agricultural Research in DryAreas at Tashkent Office. The course material wasdistributed to the participants in the form of E-manual.

Inaugural function of Training Programme on ‘Recent Advances inWeb Technologies for Information Management in Agriculture’

Summer/Winter School Organized

21 days Winter School on Bioinformatics and StatisticalGenomics was organised during 17 November–07 December 2009. The main objective was to trainindividuals at the interface of genomic, computationaland statistical sciences. The course was structured ina series of modules on preliminaries, introduction toLAMP technology, bioinformatics and statisticalgenomics, covering important topics on biological

Valedictory function of Winter School on ‘Bioinformaticsand Statistical Genomics’

60


A participant receiving the certificate from Chief Guest duringValedictory Function of Training Programme on

‘Data Analysis with Statistical Tools’

Institute, during 06-25 November 2009. Dr. Anil Raiwas the Course Director of the training programme.There were 08 participants from China, Ethiopia,Pakistan, Sudan, Syria and Nigeria.

Other Training Programmes

● A training programme on Data Analysis withStatistical Tools sponsored by Central StatisticalOrganization, Ministry of Statistics and ProgrammeImplementation, Government of India was organizedfor 23 ISS Probationers of XXIX batch during 13April–08 May 2009. The training programme wasinaugurated by Dr. MM Pandey, DDG (Engg.), ICAR.The training programme aimed at familiarizing theparticipants with the advances in data analyticaltechniques for drawing statistically valid inferencesfrom data and to acquaint the participants with theuse of statistical packages for data analysis andprovide a hands on experience. Entire coursecontents were structured in the following broadheadings viz. Computer Usage and StatisticalSoftware Packages; Statistical Methods andStatistical Inference; Design of Experiments;Multivariate Analytical Techniques; StatisticalModelling and Forecasting Techniques; SampleSurveys and Other Useful Statistical Techniques suchas Spatial Statistical Analysis, Remote Sensing andGIS, Data Mining, Artificial Neural Networks, etc. Thecourse material was distributed to the participants inthe beginning of the training programme in the formof reference manual in two volumes. Dr. Pronab Sen,Chief Statistician and Secretary, Ministry of Statisticsand Programme Implementation, Government of

A view of International Training Programme on‘Experimental Designs and Data Analysis’ at Tashkent

● An International training Programme on Advancesin Design and Analysis of Experiments at ICARDA,Aleppo Syria was organized by Dr. Rajender Parsadas Course Director during 08-19 November 2009while he was invited as Consultant with its Computerand Biometrics Services Unit. Sh. Khaled-El-Shamma from ICARDA, Syria acted as CourseCo-Director. The training programme was attendedby 15 participants from National AgriculturalResearch Systems of Iraq, Iran, Azerbaijan, Sudan,Jordan, Uzbekistasn, Lybia and Syria. The coursematerial was distributed to the participants in the formof E-manual.

● An International Training Programme on Applicationsof Remote Sensing and GIS in Agricultural Surveyssponsored by Afro Asian Rural DevelopmentOrganization (AARDO) was organized at the

International Training Programme on ‘Applications of RemoteSensing and GIS in Agricultural Development’ is in progress

61


India was the Chief Guest in the Valedictory Function.He distributed the certificates to the participants alongwith a copy of E-manual. Dr. Rajender Parsad wasthe Course Director and Dr. Krishan Lal was theCourse Co-Director for this training programme.

● A refresher course on Applications of InformationTechnology in Statistical Computing and DataDissemination Techniques for in-service ISS officersand senior officers of State Governments/UT for CSOwas organised at the Institute during 26-30 October2009. Dr. R.C. Goyal was the Course Director forthe training program. 13 participants attended thetraining programme.

and Dr. Hukum Chandra was the CourseCo- Director of the programme. The topics coveredin the training programme were Importanceand problem of small area estimation, differentapproaches used in small area estimation,small area estimation under mixed model, smallarea estimation using NSSO data and use of Rpackage. 25 participants attended the trainingprogramme.

● A refresher training course on ResearchMethodology for Official Statistics sponsored byCSO, Ministry of Statistics and ProgrammeImplementation, Govt. of India for twelve IndianStatistical Service (ISS) officers and statisticalpersonnel was organized during 01-06 February2010. Some of the topics covered were Analysis ofcomplex surveys, Models in survey sampling,Imputation techniques, Variance estimationtechniques, Small area estimation techniques,Applications of remote sensing and GIS in surveysampling and analysis of survey data using SPSS,SAS, R and SSDA softwares etc. Dr. UC Sud wasCourse Director and Dr. Tauqueer Ahmad wasCo-Course Director for this training course.

Inaugural function of Refresher Course on ‘Application ofInformation Technology in Statistical Computing

and Data Dissemination Techniques’

● A refresher training programme on Small AreaEstimation for the Indian Statistical Services andother senior officers of States/Union Territories, wasorganized during 18-22 January 2010. The coursewas sponsored by Central Statistical Organization,Ministry of Statistics & Programme Implementation,Govt of India. Dr. UC Sud was the Course Director

Valedictory function of Refresher Training Programme on‘Small Area Estimation’

Director, IASRI welcoming the Chief Guest duringvaledictory function of Refresher Training Programme

on ‘Research Methodology for Official Statistics’

● Two days computer training on the topics MS Word,MS Excel and Role of IT in the Functioningof Finance Division was organised during16-17 February 2010 under “Special trainingprogramme on financial matters” for the officials ofICAR Hqrs.’. 25 participants attended the trainingprogramme.

● A refresher training programme on AgriculturalStatistical System in India, for 14 Statistical

62


FACULTY MEMBERS OF P.G. SCHOOL, IARI INCOMPUTER APPLICATION

S. Name Year ofNo. induction

1. Dr. SD Sharma, ADG (HRD) 19962. Dr. PK Malhotra, Professor (Computer Application) 19913. Dr. RC Goyal, Principal Scientist 19954. Dr. VK Mahajan, Principal Scientist 19965. Sh. Harnam Singh Sikarwar, Scientist (SG) 19976. Md. Samir Farooqi, Scientist 20017. Dr.(Smt.) Alka Arora, Scientist 20018. Smt. Shashi Dahiya, Scientist 20019. Smt. Sangeeta Ahuja, Scientist 2002

10. Dr. Sudeep Marwaha, Scientist 200211. Sh. KK Chaturvedi, Scientist 200212. Sh. SN Islam, Scientist 200413. Sh. SB Lal, Scientist 200414. Smt. Anshu Bharadwaj, Scientist 200415. Smt. Anu Sharma, Scientist 200416. Smt. Rajni Jain, Sr. Scientist (at NCAP) 2007

FACULTY MEMBERS OF P.G. SCHOOL, IARI INAGRICULTURAL STATISTICS

S. Name Year ofNo. induction

1. Dr. VK Bhatia, Director and 1987Professor (Agricultural Statistics)

2. Dr. VK Gupta, National Professor 19843. Dr. Prajneshu, Principal Scientist 19844. Sh. SD Wahi, Principal Scientist 19875. Dr. Ranjana Agrawal, Principal Scientist 19886. Dr. UC Sud, Principal Scientist 19957. Dr. KK Tyagi, Principal Scientist 19958. Dr. Rajender Parsad, Principal Scientist 19959. Dr. Anil Rai, Principal Scientist 1995

10. Dr. Seema Jaggi, Senior Scientist 199511. Dr. Chandrahas, Principal Scientist 199612. Dr. PK Batra, Principal Scientist 199613. Dr. Aloke Lahiri, Senior Scientist 199814. Dr. Amit Kumar Vasisht, Principal Scientist 199815. Dr. Lalmohan Bhar, Senior Scientist 199816. Dr. Amrit Kumar Paul, Senior Scientist 199817. Dr. Tauqueer Ahmad, Senior Scientist 199818. Dr. AR Rao, Senior Scientist 199819. Dr. Ramasubramanian V, Senior Scientist 1999

20. Dr. Girish Kumar Jha, Senior Scientist (at IARI) 199921. Dr. Cini Varghese, Senior Scientist 200022. Dr. Prachi Misra Sahoo, Scientist 200223. Dr. RL Sapra, Principal Scientist (at IARI) 200224. Dr. Krishan Lal, Principal Scientist 200325. Dr. Hukum Chandra, Scientist 200326. Sh. Amrender Kumar, Scientist 200327. Md. Wasi Alam, Scientist 200328. Dr. Prawin Arya, Scientist 200329. Dr. Himadri Ghosh, Senior Scientist 200430. Dr. Anil Kumar, Scientist 2010

Personnel of States/UTs/PSUs of Ministry ofStatistics & Programme Implementation,Government of India was organised during 15-19March 2010. It was funded by Central StatisticalOrganisation (CSO), Ministry of Statistics &Programme Implementation, Government of India.Brief Outline/Course Curriculum of the programmewere System of collection of agricultural statisticsin India, Cost of cultivation of principal crops in India,Land use and area statistics, Agricultural prices,wages and market intelligence, Agricultural census,Irrigation statistics, Crop forecasting and cropestimation and Animal husbandry statistics. Dr. KKTyagi was the Course Director and Dr. AK Guptawas the Course Co-Director of the programme.

During the Inaugural Session Sh. SK Das, DirectorGeneral, CSO was the Chief Guest. In the ValedictorySession, Dr. BBPS Goel, Former Director, IASRI wasthe Chief Guest and Dr. VK Gupta, National Professor,ICAR presided over the session.

Research FellowshipDuring 2009-10, 15 Ph.D. and 34 M.Sc. studentsreceived Research Fellowship. 13 Ph.D. studentsreceived IARI Scholarship @ Rs.10,500 /- p.m. inaddition to Rs.10,000/- per annum as the contingentgrant and 2 Ph.D. students received CSIR Fellowship@ Rs.12,000 /- p.m. in addition to Rs. 20,000/- perannum as the contingent grant.

13 M.Sc. students received ICAR Junior ResearchFellowship @ Rs. 8640/- p.m. besides Rs. 6000/-per annum as the contingent grant and 21 M.Sc. studentsreceived IARI Scholarship @ Rs. 7560/- p.m. besides Rs.6000/- per annum as the contingent grant.

A view of Valedictory Session of Refresher Training Programme onAgricultural Statistical System in India

63


COURSES TAUGHT DURING THE ACADEMIC YEAR 2008–09

Code Title Course Instructors

Trimester – IIIAgricultural Statistics

AS-103 Elementary Sampling & Non- Parametric Methods (2+1) KK Tyagi & Asha SaksenaAS-163 Statistical Inference (4+1) Rajender Parsad, Hukam Chand & LM BharAS-164 Design of Experiments – I (3+1) Seema Jaggi & VK GuptaAS-166 Statistical Genetics – I (3+1) VK BhatiaAS-302 Advanced Design of Experiments – II (2+1) PK Batra & Krishan LalAS-304 Advanced Sample Survey – II (2+1) UC Sud & Hukum ChandraAS-307 Forecasting Techniques (1+1) Chandrahas & Ramasubramanian VAS-370 Recent Advances in the Field of Specialisation (1+0) VK GuptaAS-299 Seminar (1+0) Seema Jaggi

Computer Application

CA-131 Data Base Management System (2+2) RC Goyal, Sudeep Marwaha & Anu SharmaCA-132 Data Structures and Algorithms (2+1) KK ChaturvediCA-134 Modeling and Simulation (2+1) PK Malthotra & Anshu BhardwajCA-135 Computer Networks (2+1) SN Islam & Alka AroraCA-299 Seminar (1+0) Anu Sharma

COURSES TAUGHT DURING THE ACADEMIC YEAR 2009–10

Code Title Course Instructors

Agricultural StatisticsTrimester – I

AS-101 Elementary Statistical Methods (2+1) KK Tyagi & AK GuptaAS-150 Mathematical Methods – I (4+0) Cini Varghese & Himadri GhoshAS-160 Probability Theory (2+0) PK Batra & Anil KumarAS-161 Statistical Methods – I (2+1) Seema Jaggi & Ramasubramanian VAS-167 Applied Multivariate Analysis (2+1) Ranjana Agrawal & AR RaoAs-168 Econometrics (2+1) AK Vasisht & Prawin AryaAS-169 Planning of Surveys / Experiments (2+1) KK Tyagi & Aloke LahiriAS-200 Design of Experiments – II (1+1) Rajender Parsad & Cini VargheseAS-201 Sampling Techniques – II (1+1) Tauqeer Ahmad & Prachi Misra SahooAS-202 Statistical Genetics – II (1+1) SD Wahi & AK PaulAS-203 Regression Analysis (1+1) LM Bhar & Ramasubramanian VAS-204 Linear Models (2+0) Krishan Lal & VK GuptaAS-206 Optimization Techniques (1+1) UC Sud & PrajneshuAS-299 Seminar (1+0) Anil KumarAS-370 Recent Advances in the Field of Specialization (1+0) UC Sud

Trimester – IIAS-102 Elementary Design of Experiments (2+1) Aloke Lahiri & DK SehgalAS-151 Mathematical Methods in Statistics – II (4+0) NK Sharma, Anil Kumar & Cini VargheseAS-162 Statistical Methods – II (2+1) Seema Jaggi & Ramasubramanian VAS-165 Sampling Techniques – I (3+1) Tauqueer Ahmad & Prachi Mishra SahooAS-170 Statistical Modeling (2+1) PrajneshuAS-171 Bioinformatics – I (3+1) AR Rao, Hukum Chandra & KV BhattAS-205 Advanced Statistical Inference (1+1) Krishan Lal & UC SudAS-207 Stochastic Processes (3+0) Himadri GhoshAS-301 Advanced Design of Experiments – I (2+1) LM Bhar & VK GuptaAS-303 Advanced Sample Survey – I (2+1) Hukum Chandra & Anil Rai

Computer ApplicationTrimester – I

CA-100 Introduction to Computer Application (1+1) VH GuptaCA-111 Computer Organization and Architecture (3+0) Sudeep Marwaha & Alka AroraCA-112 Fundamentals of Computer Programming in C (2+1) KK Chaturvedi & Md S FarooqiCA-114 Mathematical Foundations in Computer Application (4+0) PK Batra, NK Sharma & HS SikarwarCA-211 Compiler Construction (2+1) SB LalCA-212 Computer Graphics (2+1) Pal Singh & Sangeeta AhujaCA-213 Artificial Intelligence (2+1) Rajni Jain & Sudeep MarwahCA-214 Internet Technologies & Applications (2+1) Alka Arora, Anu Sharma & SB LalCA-215 Software Engineering (2+0) Anu Sharma & Rajni JainCA-299 Seminar (1+0) Anu Sharma

Trimester – IICA-101 Computer Fundamentals & Programming (3+1) Pal Singh & SN IslamCA-121 Object Oriented Programming & Design (2+1) Sangeeta AhujaCA-122 Operating System (2+1) HO AgarwalCA-123 Numerical Analysis (2+1) HS SikarwarCA-124 System Analysis & Design (2+1) RC GoyalCA-221 Data Warehousing and Data Mining (2+1) Anil Rai & Rajni JainCA-224 GIS and Remote Sensing Techniques (2+1) Prachi Misra Sahoo & Md S FarooqiCA-225 Data Analysis in Agriculture (1+2) VK MahajanCA-299 Seminar (1+0) Anu Sharma & Shashi Dahiya

Note: Figures in the parentheses indicate the number of credits (Lectures + Practicals)

AWARDS

● Dr. Hukum Chandra received Cochran-Hansen Prize2009 from International Association of SurveyStatisticians.

● Dr. AK Vasisht received the Best Research PaperAward for the paper entitled “An analysis of volatilityof agricultural prices - A case study of maize” in thenational level Workshop cum Seminar on “IndianCommodity Market Derivatives & Risk Management -The Road Ahead” held at Pondicherry University,Puducherry during 11-12 September 2009.

● Dr. Himadri Ghosh received Mrs. Bhargavi andProfessor CR Rao Award for Best Poster Presentationon “Application of statistical learning theory for fittingmultimodal distribution to rainfall data” in theInternational Conference on Frontiers of Interfacebetween Statistics and Sciences held at C.R. RaoAdvanced Institute of Mathematics, Statistics andComputer Science (AIMSCS), University of Hyderabad,Hyderabad during 30 December 2009 to 02 January2010.

● Dr. AK Gupta received III prize for the research paperentitled “Estimation of area, production and productivityof flowers” for oral presentation during the NationalDr. Hukum Chandra receiving Cochran-Hansen Prize

Awards and Recognitions

66


Symposium on “Lifestyle Floriculture: Challenges andOpportunities” held at Dr.YS Parmar University ofHorticulture and Forestry, Nauni, Solan (HP) on 20March 2010.

● Expert System on Wheat Crop Mangement for bridgingthe gap between experts and farmers by providingknowledge based redressal information, receivedManthan Award South Asia 2009 for best e-contentand best e-learning solution. The project was the onlywinner from India, out of 380 nominations from sevencountries. The details of award are available athttp://www.manthanaward.org/section_synopsis.asp?id=190&pno=2

RECOGNITION

Dr. VK Bhatia

● Chief Guest of the Winter School on Decision Makingin Agriculture using Data Mining on 27 October 2009at NCAP, New Delhi.

● Chief Guest of the National workshop on ApplicableStatistics organised by Department of Statistics, MDUniversity, Rohtak on 28 March 2010.

Dr. VK Gupta

63rd Annual Conference of ISAS held at Departmentof Statistics, Mathematics and Computer Application,Rajendra Agricultural University, Samastipur, Pusa,Bihar during 03-05 December 2009

● Chaired, Dr. VG Panse Memorial lecture delivered byDr. BK Sinha, Visiting Professor, Indian StatisticalInstitute, Kolkata on A Reflection on the Choice ofCovariates in Agricultural Experiments.

● Chaired, session of Society’s Research Work during2009 on Statistical Evaluation of Variation in Socio-Economic Development in the States of Eastern Regionpresented by Sh. SC Rai.

XII Annual Conference of Society of Statistics,Computer and Applications held at Department ofStatisics, Shiksha Bhawan, Vishva Bharti,Shantiniketan, West Bengal during 24-26 February2010

● Chaired the session of Keynote Address on Statisticsfor Assessment of Climate Change delivered byDr. MN Das.

● Chaired the presentations during the symposium onStatistics in Studying the Impact of Climate Change.

Dr. Rajender Parsad

● Invited as Consultant with the Computer andBiometrics Services Unit, ICARDA, Syria during01-05 June 2009 and 08-19 November 2009 forconducting International Training Programme onExperimental Designs.

● Chairman, contributed paper session during XII AnnualConference of Society for Statistics, Computer andApplications held at Department of Statistics, SikshaBhavana, Visva Bharati during 23-25 February2010.

● Chairman, invited talk during National Workshopon Applicable Statistics held at Department of

● MkW- jatuk vxzoky dks Hkkjr ljdkj] lwpuk ,oa izlkj.k eaa=kky;ds izdk'ku foHkkx }kjk vk;ksftr Hkkjrasnq gfj'pUnz iqjLdkj ;kstukds varxZr oSKkfud ys[kksa dh iqLrd (ikaMqfyfi) ¶foKku esa rkd>k¡d¸ ds fy;s 29 ekpZ 2010 dks cky ,oa fd'kksj lkfgR; oxZ esa

izFke iqjLdkj (la;qDr) feyk A

● The Division of Computer Application participated inKrishi Vigyan Mela held during 04-06 March 2010 atIARI, New Delhi. The stall was decorated with postersof various web-based applications and stand alonesoftware developed at the Institute to disseminate theknowledge to visitors and farmers. The “Expert Systemon Wheat Crop Management” was shown to farmersthrough touch screen computers and laptops. By virtueof this IASRI received a “Praise-Reward for ExcellentPerformance” under ICAR Institute Category.

Expert System on Wheat Crop Mangement Team withManthan Award South Asia

67


Statistics, M.D. University, Rohtak during 28-30 March2010.

● Discussant in the technical session on Introductionto Mixture Experiments: Standard Models andEstimability during the Dissemination Workshop onMixture Experiments: Theory and Applications heldat BCKV, Kalyani during 21-22 December 2009.

Dr. Anil Rai

● Advisor for Third Census of Handlooms and Issue ofPhoto ID Card to Weavers conducted by NCAER,New Delhi.

Dr. Aloke Lahiri

● Chaired a contributed paper session on Statistics inAgriculture at the XII Annual Conference of Society forStatistics, Computer and Applications at Departmentof Statistics, Siksha Bhavana, Visva Bharati during24-26 February 2010.

Dr. Anil Kumar

● Nominated as Member of Board of Studies for theDiscipline of Statistics of Kumaun.

● Acted as a judge in the poster session of SymposiumIV on Socio-Economics and Marketing of theInternational Buffalo Conference on OptimizingBuffalo Productivity through Conventional and NovalTechnologies at NASC Complex, New Delhi on03 February 2010.

Offices in Professional Societies/Research Journals

Aligarh Journal of Statistics

Dr. Tauqueer Ahmad Member, Editorial Board

Annals of Agricultural Research

Dr. Cini Varghese Member, Editorial Board

Bureau of Indian Standards, New Delhi

Dr. VK Gupta Member, Management andSystems Division Council

Dr. VK Bhatia Member, Management andSystems Division Council

Dr. Rajender Parsad Member, Management andSystems Division Council

Computer Society of India

Dr. PK Malhotra Member, ManagingCommittee

Dr. Alka Arora Member, ManagingCommittee

Department of Educational Measurement andEvaluation of National Council of EducationalResearch and Training

Dr. Rajender Parsad Nominated Member ofAdvisory Board

Farming Systems Research and DevelopmentAssociation

Dr. Anil Kumar Joint SecretaryMember, Editorial Board

Forum for Interdisciplinary Mathematics

Dr. VK Gupta Vice-PresidentDr. Rajender Parsad Joint Secretary

Indian Journal of Applied Statistics

Dr. Prajneshu Member, Editorial Board

Indian Society of Agricultural Marketing

Dr. AK Vasisht Member, Executive Council

Indian Society of Agricultural Statistics

Dr. VK Gupta Vice PresidentChair Editor, JISAS

Dr. VK Bhatia SecretaryAssociate Editor, JISAS

Dr. Rajender Parsad Joint SecretaryAssociate Editor, JISAS

Dr. Prajneshu Associate Editor, JISAS

Dr. PK Malhotra Joint SecretaryAssociate Editor, JISAS

Dr. AK Vasisht Member, Executive Council

Dr. UC Sud Member, Executive CouncilAssociate Editor, JISAS

Dr. VK Mahajan Member, Executive Council

Dr. Hukum Chandra Member, Executive Council

Institute of Applied Statistics and DevelopmentStudies

Dr. VK Gupta Member, Governing Body

Dr. VK Bhatia Member, Governing Body

Dr. Prajneshu Member, Governing Body

Dr. Rajender Parsad Member, Governing Body

International Indian Statistical Association - INDIAJoint Statistical Meeting (IISA-INDIA JSM) 2000 Trust

Dr. VK Bhatia President

68


International Statistical Institute, Netherlands

Dr. VK Gupta Elected MemberDr. Rajender Parsad Elected Member

International Journal of Agricultural and StatisticalScience

Dr. Anil Kumar Member, Editorial Board

Journal of Statistical Planning and Inference

Dr. VK Gupta Associate Editor

Journal of Statistical Theory and Practice

Dr. VK Gupta Associate Editor

Dr. Prajneshu Associate Editor

Ministry of Statistics & Programme Implementation

Dr. VK Bhatia Member, EmpoweredCommittee for Awards andFellowship for Outstanding andMeritorious Research Work inStatistics

Dr. VK Gupta Member, ScreeningCommittee for Awards andFellowship for Outstanding andMeritorious Research Work inStatistics

National Centre of Agricultural Economics and PolicyResearch, New Delhi

Dr. VK Gupta Member, InstituteManagement Committee

National Council of Applied Economic Research(NCAER), New Delhi

Dr. Anil Rai Member, Advisory Committee

Pusa AgriScience, Journal of IARI, PG School

Dr. Rajender Parsad Member, Editorial Board

Society of Statistics, Computer and Applications

Dr. VK Gupta Executive President

Dr. VK Bhatia Vice PresidentMember, Editorial Board

Dr. Rajender Parsad Secretary

Dr. Aloke Lahiri Joint Secretary

Dr. LM Bhar Joint Secretary

Swadeshi Science Movement of Delhi

Dr. Sushila Kaul Member, Executive CouncilMember, Editorial Board

S. Title Collaborative/ Date of Start Date of Completion No. Funding Agency

1. Planning, designing and analysis of experiments Project Co-ordinator (STCR), 01 March 2007 31 March 2010relating to AICRP on Soil Test Crop Response Indian Institute of Soil Science,(STCR) correlation Bhopal

2. Planning, designing and analysis of experiments Project Directorate of Farming 01 April 2007 31 March 2012planned ON-STATION under PDFSR System Research, Modipuram

3. Planning, designing and analysis of ON-FARM Project Directorate of Farming 01 April 2007 31 March 2012experiments under PDFSR System Research, Modipuram

4. Planning, designing and analysis of data relating Project Coordinator (LTFE) 01 April 2007 31 March 2012to experiments conducted under AICRP on LTFE IISS, Bhopal

5. Developing remote sensing based methodology SAC, Ahmedabad and 01 October 2007 30 September 2010for collecting agricultural statistics in Meghalaya NESAC, Shillong

6. Development of forecasting module for podfly, Indian Institute of Pulses 01 July 2007 30 June 2012Melanagromyza obtusa Malloch in late pigeonpea Research, Kanpur

7. Computational analysis of SNPs at functional NRC on Plant Biotechnology, 01 September 2007 11 January 2010elements of rice genome New Delhi

8. Strengthening, refining and implementation of DWR, Karnal/IARI, New Delhi 25 August 2007 24 February 2010expert system on wheat crop management

Linkages and Collaboration in India and Abroadincluding Outside Funded Projects

70

Linkages and Collaboration

9. Study on status and projection estimates of Central Institute of Agricultural 01 March 2008 31 March 2010agricultural implements and machinery Engineering, Bhopal

10. Weather based models for forecasting potato Department of Agricultural Statistics 01 November 2007 30 April 2009yield in Uttar Pradesh & Crop Insurance, Directorate of

Agriculture, Lucknow, U.P.

11. Expert system on seed spices NRCSS, Ajmer 01 February 2009 31 July 2010

12. Expert system for maize crop Directorate of Maize Research, 01 April 2009 30 September 2010New Delhi

13. Experimental designs for agricultural research AP-Cess Fund, ICAR 01 January 2008 31 December 2009involving sequences of treatments

14. Visioning, Policy Analysis and Gender (V-PAGe) - NCAP, New Delhi 01 June 2007 31 May 2012Sub-Programme II : Technology forecasting NAARM, Hyderabad

(NAIP Funded)

15. Visioning, Policy Analysis and Gender (V-PAGe) NCAP, New Delhi; IARI, New Delhi; 01 June 2007 31 May 2012Sub-Programme III : Policy analysis and market NAARM, Hyderabad; NRCWA,intelligence Bhubaneshwar; Yes Bank,

Agri-Watch (NAIP Funded)

16. Risk assessment and insurance products for NCAP, New Delhi 01 October 2008 31 March 2012agriculture (NAIP Funded)

17. Bioprospecting of genes and allele frequency for NRCPB, New Delhi 04 May 2009 31 March 2012abiotic stress tolerance (NAIP Funded)

18. Strengthening statistical computing for NARS NDRI, Karnal; IVRI, Izatnagar; 20 April 2009 31 March 2012MPUA&T, Udaipur; DWM,Bhubaneshwar; ICAR RC NEHR,Barapani; UAS, Bangalore;NAARM, Hydrabad; CIFE,Mumbai (NAIP Funded)

19. Stochastic process modelling and forecasting DST, New Delhi 01 March 2008 28 February 2011through discrete non-linear time series approach

20. Whole Genome Association (WGA) analysis UDSC, NII, Delhi University, 29 September 2008 28 September 2013in common complex diseases: An Indian initiative AIIMS, DMC

(DBT Funded)

21. Study to investigate the causes of variation Ministry of Agriculture, 01 October 2006 15 May 2009between official and trade estimates of cotton New Delhiproduction

22. Sampling methodology for estimation of meat Ministry of Agriculture, 01 May 2009 30 April 2011production in Meghalaya Department of Animal Husbandry,

Dairying & Fisheries, New Delhi

23. Evaluation of rationalization of minor irrigation Ministry of Water Resources, 25 July 2009 23 December 2010statistics (RMIS) scheme New Delhi

24. Estimation of slum and slum like population National Building Organisation, 01 October 2009 31 January 2010in India Ministry of Housing and Urban

Poverty Alleviation, New Delhi

25. Prioritization of rainfed area in the country CRIDA, Hyderabad and National 01 January 2010 31 October 2010Agricultural Rainfed Authority,Ministry of Agriculture, New Delhi

S. Title Collaborative/ Date of Start Date of Completion No. Funding Agency

Research Papers

1. Abeynayake, NR and Jaggi, Seema (2009). Areview of block designs with neighbour effects. SriLankan J. Appl. Statist., 10, 85-103.

2. Arnab, R and Sud, UC (2009). A note on varianceestimation of ratio estimate in two phase sampling.Model Asst. Statist. Appl., 5(1), 51-60.

3. Arora, Alka, Upadhyaya, Shuchita, Jain, Rajni(2009). Post processing of clusters for patterndiscovery: Rough set approach. J. Ind. Soc. Agril.Statist., 63(2), 181-188.

4. Behera, SK, Paul, AK and Wahi, SD (2010).Estimation of heritability of mastitis disease usingANOVA method. IUP J. Genet. Evol., 3(1), 24-29.

5. Bhardwaj, SP and Vasisht, AK (2009). Price volatilityand integration in spot and future markets. Ind. J.Agril. Mktg., 23(1), 46-57.

6. Bhardwaj, SP and Vasisht, AK (2009). Strategicmeasures to meet market challenges in thechanging scenario of liberalization. Ind. J. Agril.Mktg., 23(3), 42-54.

7. Chandra, H and Chambers, R (2009). Multipurposeweighting for small area estimation. J. OfficialStatist., 25(3), 379 – 385.

8. Choudhary, SK, Rao, AR, Wahi, SD andPrabhakaran, VT (2009). Performance ofsimultaneous selection index against missingobservations in genotype X environment data.ICFAI University J. Genet. Evol., 2(4), 36-42.

9. dqekj] izeksn] dqekj] vfuy] rksej] vkj ,l ,oa flag] jfoUnz(2008)- LVsfVfLVdy boSy;w,'ku vkWiQ fMiQjsaV jkbZl oSjk;hfV~lcslM ØkWIk lhDoSal Fkzw buVSalhiQhds'ku ,s.M MkbojlhfiQds'ku_Hkkjrh; Ñf"k vuqla/ku if=kdk] 23(2), 81-90.

10. dqekj] vfuy] dqekj] izeksn] flag] jfoUnz ,oa rksej] vkj ,l(2008)- vlSLeSaV vkWiQ lLVsuscy uSV fjVuZ bu iyZfeySV&OghV_Hkkjrh; Ñf"k vuqla/ku if=kdk] 23(2), 73-80.

11. Ghosh, H, Paul, RK and Prajneshu (2010).Functional coefficient autoregressive nonlineartime-series model for forecasting Indian lacexport data. Model Asst. Statist. Appl., 5(1),101-108.

List of Publications

72


12. Ghosh, Himadri, Paul, RK and Prajneshu (2010).Nonlinear time series modeling and forecasting forperiodic and ARCH effects. J. Statist. Theo. Prac.,4(1), 27-44.

13. Gupta, VK, Bhar, LM, Parsad, Rajender and Kole,Basudev (2009). Efficient unbalanced multi-levelsupersaturated designs. Kageyama Special Issueof J. Statist. Appl., Journal of the Forum forInterdisciplinary Mathematics, 4(2&3), 443-445.

14. Gupta, VK, Singh, Poonam, Kole, Basudev, Parsad,Rajender (2009). Construction of efficientunbalanced mixed-level supersaturated designs.Statist. Probab. Lett., 79(5), 2359-2366.

15. Iquebal, MA, Prajneshu and Ghosh, Himadri (2009).Application of genetic algorithm optimizationtechnique for fitting non-linear Richards growthmodel. Ind. J. Agric. Sci., 79, 399-401.

16. Jaggi, Seema, Gill, AS, Varghese, Cini, Sharma,VK and Singh, NP (2009). Impact assessment ofagroforestry system on yield of associated barley(Hordeum vulgare) and gram (Cicer arietinum)crops. Current Adv. Agril. Sci., 1(2),101-105.

17. Jain, R, Minz, S and Ramasubramanian V (2009).Machine learning for forewarning crop diseases.J. Ind. Soc. Agril. Statist., 63(1), 97-107.

18. Jain, Rajni, Arora, Alka and Raju, SS (2009). A noveladoption index of selected agricultural technologies:Linkages with infrastructure and productivity. Agric.Eco. Res. Rev., 22, 109-120.

19. Kaul, Sushila and Ram, Ghasi (2009). Anassessment of impact of climate change on riceproduction in India. Agril. Situation India, 65(6), 413-415.

20. Kumar, Amit, Gandhi, RS and Paul, AK (2009).Genetic evaluation of lifetime traits in sahiwal cattle.Ind. J. Dairy Sci., 62(1), 31-34.

21. Kumar, Pramod, Kaur, Rajinder and Tomar, RS(2007). Statistical assessment of cycles of differentcrop rotations. Asia Pacific J. Environ. Dev., 14(2),55-68.

22. Maheswaran, Manjunath, Prasanna, Radha, Nain,Lata, Dureja, Prem, Singh, Rajinder, Kumar, Arun,Jaggi, Seema and Kaushik, Brahma D (2010).Biocontrol potential of cyanobacterial metabolitesagainst damping off disease caused by Pythiumaphanidermatum in solaneous vegetables. Archivesof Phytopath. Plant Nutrition, 43(7), 666-677.

23. Narain, P, Sharma, SD, Rai, SC and Bhatia, VK(2009). Inter district variation of socio-economicdevelopment in Andhra Pradesh. J. Ind. Soc. Agril.Statist., 63(1), 35-42.

24. Narain, Prem, Bhatia, VK and Rai, SC (2009).Evaluation of variation in socio-economicdevelopment in the states of eastern region. J. Ind.Soc. Agril. Statist., 63(3), 227-235.

25. Panwar, Sanjeev, Sharma, SC, Kumar, Anil andKaul, Sushila (2009). State-wise analysis of onionproduction in India using non-linear approach. Agril.Situation India, 65(1), 689-698.

26. Parsad, Rajender, Gupta, VK, Kumar, Jitendra andShakil, NA (2008). Significance of statistical toolsfor agrochemical research. Pest. Res. J., 20(2A),8-17.

27. Parsad, Rajender, Nandi, PK, Bhar, LM and Gupta,VK (2008). Outliers in multi-response experiments.J. Statist. Appl., 6(1&2), 275-292.

28. Paul, AK, Kundu, MG, Singh, S and Singh, Pal(2009). Heritability of growth curve parameters ofpigs. Ind. J. Anim. Sci., 79(7), 716-719.

29. Paul, AK, Kundu, MG, Singh, S and Singh, Pal(2009). Some aspect of efficiency of early selectionin pigs. Ind. J. Anim. Sci., 79(7), 729-731.

30. Paul, RK, Prajneshu and Ghosh, Himadri (2009).GARCH nonlinear time-series analysis for modelingand forecasting of India’s volatile spices export data.J. Ind. Soc. Agril. Statist., 63(2), 123-131.

31. Paul, S, Sethi, IC and Arora, Alka (2009). Decisionsupport system for nutrient management in crops.J. Ind. Soc. Agril. Statist., 63(1), 91-96.

32. Prabhakaran, VT and Rao, AR (2008). A newapproach to the estimation of variance of sampleheritability from full-sib analysis. J. Ind. Soc. Agril.Statist., 62(3), 208-213.

33. Raju, BMK, Bhatia, VK and Bhar, LM (2009).Assessing stability of crop varieties with incompletedata. J. Ind. Soc. Agril. Statist., 63(2), 139-150.

34. Sarika, Jaggi, Seema and Sharma, VK (2009).Second order response surface model withneighbour effects. Comm. Statist.- Theory Methods,38, 1393–1403.

35. Sarkar, Susheel Kumar, Lal, K and Jha, GK (2009).Non-linear growth models for pigs. Ind. Vete. J.,86, 796-799.

73


36. Sarkar, Susheel Kumar, Lal, Krishan, Parsad,Rajender and Gupta, VK (2009). Generation oflinear trend free designs for factorial experiments.J. Ind. Soc. Agril. Statist., 63(2), 165-174.

37. Sharma, Anu, Varghese, Cini and Rao, AR (2009).Software for the analysis of repeated measurementsdesigns. Ind. J. Anim. Sci., 79(4), 445-448.

38. Singh, DK, Rajput, TBS, Sikarwar, HS, Sahoo, RNand Ahmad, T (2006). Performance of subsurfacedrip irrigation system with line source of waterapplication in Okra field. J. Agril. Engg., 43(3),23-26.

39. Singh, Okendro N, Wahi, SD and Paul, AK (2010).Performance evaluation of bootstrap strategies onthe estimate of standard error of heritability by half-sib method. Ind. J. Anim. Sci., 80(1), 81-84.

40. Singh, Okendro N and Paul, AK (2010). Fitting ofallometric model with expected-value parametersfor different species of snow trout from Jhelum river,Kashmir. Ind. J. Anim. Sci., 80(1), 85-88.

41. Singh, Okendro N, Alam, Wasi, Paul, AK and Kumar,Surinder (2009). Length-weight relationship andgrowth pattern of Tor putitora (Hamilton) undermonoculture and polyculture systems: A case study.J. Ind. Soc. Agril. Statist., 63(1), 85-90.

42. Singh, Okendro N, Joshi, CB and Paul, AK (2009).Non-linear statistical models on estimation ofmaximum size of Tor putitora (Hamilton) indifferent aquatic environments. Ind. J. Fish., 56(2),103-106.

43. Singh, Surendra, Bhar, LM, Paul, AK andShivaramane, N (2009). Modeling for growth patternin cross breeding cattle along with auto-correlation.J. Ind. Soc. Agril. Statist., 63(2), 159-164.

44. Sivaramane, N, Singh, DR and Arya, Prawin (2009).An econometric analysis of household demand ofmajor vegetables in India. Ind. J. Agric. Mktg., 23(1),66-76.

45. Sood, Pankaj, Nanda, Amarjeet Singh, Singh,Narinder, Javed, Mohammed and Parsad, Rajender(2009). Effect of lameness on follicular dynamics incrossbred cows. Veterinasrski Arhiv., 79(2),131-141.

46. Behera, Subrat Keshori, Paul, AK, Wahi, SD andSingh, Pal (2010). Estimation of heritability ofmastitis disease using ANOVA method. ICFAIUniversity J. Genet. Evol., 3, 24-29.

47. Sud, UC, Bathla, HVL, Muralidharan, K, Mathur, DC,Thamban, C and Sairam, CV (2009). Estimatingcost of production of coconut in a region.J. Plantation Crops, 37(3), 201-205.

48. Dash, Sukanta, Wahi, SD and Rao, AR (2009). Anempirical investigation on classical clusteringmethods. ICFAI University J. Genet. Evol., 2,74-79.

49. Sunilkumar, G and Prajneshu (2009). Waveletmethodology for jump detection in time-series data.J. Statist. Appl., 4(4), 657-667.

50. Tomar, RS, Kumar, Pramod and Dixit, SC (2008).Statistical Investigation on production, economicand energy potential of crop sequences. NewBotanist, 35, 169-181.

51. Upadhyaya, Shuchita , Arora, Alka and Jain, Rajni(2009). Reduct driven pattern extraction fromclusters. Int. J. Comp. Intell. Sys., 2(1), 10-16.

52. Varghese, Cini, Dwivedi, Lokesh and Jaggi, Seema(2009). Factorial change over designs for twonon-interacting factors. J. Statist. Theo. Appl., 8(3),311-323.

53. Vasisht, AK and Bhardwaj, SP (2009). Pricedynamics of agricultural commodity futures and itsimpact on demand supply situation of agriculturalcommodities. Ind. J. Agril. Mktg., 23(3), 72-82.

54. Visakhi, P (2009). Consortium for e-Resources inagriculture ( CeRA). DESIDOC J. Lib. Info. Tech.,29(5), 24-30.

55. Wahi, SD, Dash, Sukanta and Rao, AR (2009).An empirical investigation on classical clusteringmethods. ICFAI University J. Genet. Evol., 2,75-78.

56. Yadav, Dinesh Kumar, Singh, Gurmej, Jain, Anand,Singh, Surendra and Paul, AK (2009). Fitting ofgrowth models and evaluation of marwari sheepunder field conditions. Ind. J. Anim. Sci., 79,1242-1244.

57. Chandra, H (2009). Estimation of small areaproportions under unit level spatial models. J. Ind.Soc. Agril. Statist., 63(3), 267-276.

58. Chhikara, Raj S and Sud, UC (2009). Estimation ofpopulation and domain totals under two-phasesampling in the presence of non-response. J. Ind.Soc. Agril. Statist., 63(3), 297-304.

59. Gupta, AK, Bathla, HVL, Sud, UC and Tyagi, KK(2009). Methodology for estimation of production

74


of flowers on the basis of market arrivals. J. Ind.Soc. Agril. Statist., 63(3), 259-266.

60. Jeeva, JC, Khasim, DI, Srinath, K, Unnithan, GR,Rao, MT, Murthy, KLN, Bathla, HVL and Ahmad, T(2006). Harvest losses at various resources ofinland fisheries. Fishery Tech., 43(2), 218-223.

61. Jeeva, JC, Khasim, DI, Srinath, K, Unnithan, GR,Murthy, KLN, Rao, MT, Bathla, HVL and Ahmad, T(2007). Post harvest losses at various marketingchannels in inland fisheries sector. Fishery Tech.,44(2), 213-220.

Popular Articles

● dqekj] vfuy ,oa ckuk] vkj-,l-(2009)- i'kqikyu ,oa Hkkjrh;vFkZO;oLFkk % ,d utj esa] vkbZ-oh-vkj-vkbZ++- Lekfjdk A

● vxzoky] jatuk (2009)- dEI;wVj dh dgkuh mlh dh t+qckuh]Kku xaxk A

● vxzoky] jatuk] 'kekZ] dqynhi] tks'kh] gjh'k ,oa ukSfV;kydqeqfnuh (2009)- Ñf"k vkSj fdlku] Ñf"k lwpuk ,oa izdk'kufuns'kky;] Hkk-Ñ-v-i- }kjk izdkf'kr ifj"kn~ ds dfeZ;ksa dh Ñf"klaca/h dforkvksa ds laxzg Lkaiknu A

● Gupta, VK and Parsad, Rajender (2009). Blockdesigns for cropping systems research. NAASNews, 8(2), 3-7.

Book Chapters

● Parsad, Rajender, Handa, BR and Deepika (2009).Additional applications of multivariate techniques.Block 8 (Unit 24: Principal Component Analysis; Unit25: Factor Analysis; Unit 26: Cannonical Correlationand Unit 27: Conjoint Analysis) MMAC-023:Probability and Statistics (8 credits) for M.Sc. In:Mathematics with Applications to ComputerScience, IGNOU, New Delhi.

● Parsad, Rajender, Crossa, Jose, Gupta, VK, Gupta,Raj, K, Ladha, JK, Anitha, Raman K (2009).Statistical tools for farmers’ participatory trials forconservation agriculture. In: Integrated Cropand Resource Management in the Rice-WheatSystem of South Asia, Eds. J.K. Ladha, OlafErenstein, O. Erenstein and B. Hardy. Los Baños(Philippines): International Rice Research Institute,279-296.

● Bhardwaj, SP and Vasisht, AK (2010). Pricediscovery in commodity markets – A case study ofgram. Indian Commodity Markets (Derivatives and

Risk Management). Serials Publications, NewDelhi, 224-234.

● Vasisht, AK and Bhardwaj, SP (2010). An analysisof volatility of agricultural prices: A case study ofmaize. Indian Commodity Markets (Derivatives andRisk Management), Serials Publications, New Delhi,175-187.

● Kumar, Ashok (2010). Role of micro credit andfinancial institutions in agricultural and ruraldevelopment. In: Emerging Trends in WatershedManagement, Ed. R.P. Yadav et al., Satish SerialPublishing House, New Delhi.

● Kumar, Ashok and Singh, DR (2009). Nutritionalstatus of Indian rural households. In: Food Securityand Sustainability in India, Ed. G.S. Kainth, GuruArjan Dev Institute of Development Studies Society,Amritsar, 337-350.

Project Reports

● Ahmad, T, Bathla, HVL, Rai, A, Sahoo, PM, Gupta,AK, Jain, VK and Mhadgut, DV (2009). Study toinvestigate the causes of variation between officialand trade estimates of cotton production. ProjectReport, IASRI, New Delhi.

● Bhardwaj, SP, Kumar, Ashok, Kumar, Anil andKumar, Rajendra (2009). Impact of micronutrientson crop productivity and returns. Project Report,IASRI, New Delhi.

● Bhatia, VK, Sud, UC, Mathur, DC, Chandra, H andLal, SB (2010). Evaluation of rationalization of minorirrigation statistics (RMIS) Scheme. Project Report.IASRI, New Delhi.

● Chandra, H, Bathla, HVL and Sud, UC (2010). Smallarea estimation for zero-inflated data. Project ReportNo. IASRI/P.R.-02/2010, IASRI, New Delhi.

● Gupta, AK, Sud, UC and Mathur, DC (2009). Pilotstudy to develop sampling methodology forestimation of production of mushroom. ProjectReport, IASRI, New Delhi.

● Kaul, Sushila and Bhardwaj, SP (2009). Aneconometrics study of women empowermentthrough dairying in selected districts of Haryana.Project Report, IASRI, New Delhi.

● Mehta, SC, Pal, Satya and Kumar, Vinod. Weatherbased models for forecasting potato yield in UttarPradesh. Project Report No. IASRI/P.R.-01/2010,IASRI, New Delhi.

75


● Rai, A, Chandra, H and Bhatia, VK (2010).Estimation of slum population in India. ProjectReport, IASRI, New Delhi.

● Rao, AR, Sharma, Anu, Lal, SB and Mohapatra,T (2010). Computational analysis of SNPs atfunctional elements of rice genome. Project Report,IASRI, New Delhi.

● Saksena, Asha, Prajneshu and Ghosh, Himadri(2009). A Statistical study of rainfall distribution andrainfall based crop insurance. Project Report, IASRI,New Delhi.

● Sethi, IC and Wahi SD (2009). Statistical packagefor animal breeding 2 (SPAB2). Project Report,IASRI, New Delhi.

● Sud, UC, Bathla, HVL, Khatri, RS, Mahajan, VK,Mathur, DC and Chandra, Hukum (2009). Pilot studyon small area crop estimation approach for cropyield estimates at the gram panchayat level. ProjectReport, IASRI, New Delhi.

● Wahi, SD and Rao, AR (2010). Empiricalinvestigations on estimation of genetic correlation.Project Report, IASRI, New Delhi.

Technical Bulletin● A technical bullet in, IASRI. . . an Era of

Excellence 1959-2009 brought out as a part ofGolden Jubilee celebrations of the Institute:

- Gupta, VK, Bhatia, VK and Parsad, Rajender.Indian Agricultural Statist ics ResearchInstitute: A Profile, 1-10.

- Parsad, Rajender and Gupta, VK. A Profileof Design of Experiments at IASRI, 19-34.

- Parsad, Rajender, Jaggi, Seema, Gupta, VK,Varghese, Cini and Lal, Krishan. Glimpsesof Basic Research in Design of Experimentsat IASRI, 35-54.

- Chandrahas and Agrawal, Ranjana. Pre-harvest Crop Production ForecastMethodologies: IASRI Studies, 55-66.

- Mehta, SC, Agrawal, Ranjana and Kumar,Amrender. Forewarning Crop Pests andDiseases: IASRI Methodologies, 67-78.

- Rai, Anil, Sahoo, Prachi Misra and Ahmad,Tauqueer. Geo-informatics in AgriculturalResearch and Development: An IASRIPerspective, 79-88.

- Sud, UC, Sahoo, Prachi Misra, Chandra,Hukum, Ahmad, Tauqueer and Bindal, Vijay.Glimpses of Basic Research in SampleSurvey at IASRI, 89-100.

- Ahmad, Tauqueer, Sud, UC, Sahoo, PrachiMisra, Chandra, Hukum and Bindal, Vijay.Achievements in Applied Research in SampleSurvey at IASRI, 101-110.

- Kumar, Ashok, Singh, DR, Vasisht, AK,Sivaramane, N, Arya, Prawin and Kaul,Sushila. Assessment of Food andNutri t ional Security and Impact ofTechnologies, 111-116.

- Bhardwaj, SP, Vasisht, AK and Arya, Prawin.Modelling for Risk and Uncertainty, ResourceUse Efficiency and Agricultural Marketing,117-126.

- Prajneshu and Ghosh, Himadri. Five Decadesof Research in Statistical Modelling: AnOverview, 127-138.

- Rao, AR, Wahi, SD and Bhatia, VK. StatisticalApplications in Breeding and Genetics,139-160.

- Malhotra, PK and Goyal, RC. InformationSystems and Software Development at IASRI:An Overview, 161-184.

Release of 'IASRI... an Era of Excellence'at the Annual Day Function

76


- Jaggi, Seema, Bhatia, VK and Malhotra, PK.Teaching and Training Activities at IASRI,185-190.

- Visakhi, P. Modernized Library InformationSystem of IASRI, 191-195.

● Parsad, Rajender and Gupta, VK (2009). DesignResources Server. IASRI, New Delhi.

● Parsad, Rajender (2009). Agricultural StatisticsTerminology. Chapter 8 in Agronomic Terminology,5th revised Edition, Eds. A.R. Sharma andB. Gangaih, Indian Society of Agronomy,New Delhi.

● Rai, Anil, Chaturvedi, KK, Ramasubramanian, Vand Bhatia, VK (2009). Information andCommunication Technology for Accelerated Growthin Agriculture. Technical Series IASRI/NAIP/VPAGe/01/09, IASRI, New Delhi.

● Ramasubramanian, V, Kumar, A, Bhatia, VK andPal, S (2009). Forecasting Future TechnologicalNeeds for Rice in India. Technical Series IASRI/NAIP/VPAGe/02/09, IASRI, New Delhi.

● Sud, UC, Tyagi, KK, Singh,Jagbir, Jain, VK andGupta, AK (2009). Agricultural Research Data Book2009. ICAR, New Delhi.

Reference Manuals

● Goyal, RC, Chaturvedi, KK, Lal, SB, Singh, Pratapand Pathak, GM (2009). Applications of InformationTechnology in Statistical Computing and DataDissemination Techniques. IASRI, New Delhi.

● Parsad, Rajender (2009). Data Analysis withStatistical Tools. Vol. I and Vol. II. IASRI, New Delhi.E-manual also prepared.

● Parsad, Rajender, Lal, Krishan and Varghese,Cini (2010). Data Analysis with Statistical Packages.Vol. I and Vol. II. IASRI, New Delhi. E-manual alsoprepared.

● Rai, Anil, Sahoo, PM, Farooqui, MS, Chaturvedi,KK, Singh, Pratap and Pathak, GM (2009).Applications of Remote Sensing and GIS inAgriculture Survey. IASRI, New Delhi. Practicalmanual also prepared.

● Sharma, Anu, Lal, SB, Farooqui, MS, Chaturvedi,KK, Lal, SB, Singh, Pratap and Pathak, GM(2009). Recent Advances in Web Technology forInformation Dissemination in Agriculture. IASRI,New Delhi.

Pamphlet Published

● Bhatia, VK, Ramasubramanian, V, Rai, Anil andChaturvedi, KK (2009). Future Technological Needsin Remote Sensing and GIS for Accelerating Growthin Agriculture. IASRI, New Delhi.

● Bhatia, VK, Ramasubramanian, V, Rai, Anil,Chaturvedi, KK, Kumar Amrender and Pal, Satya(2009). Future Technological Needs in Genetics andPlant Breeding for Sustainable Agriculture. IASRI,New Delhi.

● Bhatia, VK, Ramasubramanian, V, Rai, Anil,Chaturvedi, KK, Kumar Amrender and Pal Satya(2010). Forecasting Technological Needs forRainfed Agriculture in India. IASRI, New Delhi.

Workshop Series

● Proceedings of the Fifteenth National Conferenceof Agricultural Research Statisticians held at BirsaAgricultural University, Kanke, Ranchi, Jharkhand

− Parsad, Rajender and Gupta, VK. AgriculturalStatistics Research: Current Status and FutureChallenges.

− Goyal, RC. Priorities in Computer Applicationsfor Agricultural Research – A Review.

− Prajneshu, Ghosh, Himadri and Jaggi, Seema.Some Priorities for Post-Graduate Teaching inAgricultural Statistics.

− Malhotra, PK. Teaching and Training inComputer Application in the NARS – Priorities.

● Dahiya, Shashi, Goyal, RC, Chaturvedi, KK,Bhardwaj, Anshu, Jaggi, Seema and Varghese, Cini(2009). Sensitation workshop on "Contentmanagement for e-learning systems usingMOODLE", Workshop Series, IASRI Publication.

● Islam, SN, Agarwal, Hari Om, Farooqi, Mohd.Samir, Chaturvedi, Krishna Kumar, Sikarwar,Harnam Singh, Singh, Randhir, Sharma, AK,Sharma, RK, Shoran, Jag, Gupta, RK, Sharma,JP, Sharma, Kirti, Rai, RK, Dhar, Shiva and Sabir,Naved. Workshop Document for Training andDissemination Workshop held under the projectStrengthening, Refining and Implementation ofExpert System on Wheat Crop Management.

● Proceedings of the Workshop on Forecasting FutureTechnological Needs for Rice in India. Eds.Ramasubramanian V, Amrender Kumar, VK Bhatiaand Satya Pal.

77


Other Periodical Publications

● Annual Report of the Institute, 2008-09

● IASRI News (published quarterly)

lkaf[;dh&foe'kZ 2009&10] vad&5 esa çdkf'kr ys[k

● fot; dqekj HkkfV;k A laLFkku dh Lo.kZ t;arh ;k=kk & dqN egRoiw.kZva'k] 17&19 A

● Ñ".k dkUr R;kxh] fo".kq gjh xqIrk ,oa Å"kk tSu A laLFkku ds

dhfrZLrEHk % çksiQslj çse ukjk;.k] 1&4 A

● v:.k dqekj JhokLro] mes'k pUnz lwn] gqdqe pUnz ,oa fot;fcUny A y?kq {ks=k vkdyu & jk"Vªh; çfrn'kZ losZ{k.k vk¡dM+ksa dk

vuqç;ksx] 20&26 A

● Ñ".k dkUr R;kxh] v'kksd dqekj xqIrk] fot; fcUny ,oa eku flagA

iQlYk dVkbZ ijh{k.k% ç;ksx&fof/] 27&31 A● lar nkl okgh] vkRekdqjh jkekÑ".k jko ,oa fot; iky flagA

ikjaifjd >aqM cukus dh fof/;ksa ij ,d vkuqHkfod vUos"k.k] 32&34A● nhid dqekj lgxy ,oa mes'k pUnz cUnwuhA moZjdksa ds nh?kZdkyhu

mi;ksx dk i+Qlyksa dh mit ,oa e`nk ij izHkko] 35&39 A● lqjsUnz flag] vfer dqekj of'k"B ,oa ve`r dqekj ikWy A Hkkjrh;

uLy ,oa ladfjr xk;ksa esa fodkl dk vè;;u ,oa ewY;kadu] 40&43A● vuq 'kekZ] 'kf'k Hkw"k.k yky ,oa fot; dqekj egktu A losZ{k.k

vkWadM+ksa ds fo'ys"k.k gsrq lkWÝ+Vos;j&,l-,l-Mh-,-] 44&48 A● ih- fo'kk[kh ,oa fot; fcUny A ikB~; vknrksa ij baVjusV dk

izHkko&Hkkjrh; Ñf"k vuqla/ku laLFkku ekun fo'ofo|ky; ds lanHkZesa] 49&54 A

Advisory services for researchers in NARS werepursued rigorously; ten training programmes wereconducted as consultancy (details given in Chapter 6)and two research studies were undertaken inconsultancy mode.

Advisory Services Provided● Dr. Deo Pandey, Scientist (Plant Breeding),

Department of Plant Breeding & Genetics,CSKHPKV, PalampurAdvised on the analysis of data pertaining to anexperiment conducted to evaluate 48 varieties ofrice using an α-design with parameters v = 48,b = 18, r = 3, k = 8. The data were collected on 17characters namely days to 50% flowering, days tomaturity, plant height at maturity(cm), total tillers/plant at maturity, effective tillers/plant at maturity,panicle length, spikelets/panicle, grains/panicle,grain yield/plant(g), 1000-grain weight(g), protiencontent(%), amylase content(%), gel consistency(mm), grain length, grain breadth, length breadth

ratio and gelatinization temperature. He wasadvised on analysis of variance, pairwisecomparison of genotypes, estimation of genotypicvariances and genotypic correlation, estimation ofheritability coefficient, genetic advance, divergenceanalysis, path analysis and phenotypic correlations.

● Dr. R Madhusudhana, Senior Scientist (PlantBreeding), MAS Lab, Project Directorate ofSorghum Research, Rajendranagar, Hyderabad

Advised on the analysis of data pertaining to anexperiment conducted with 175 RILs in two rabiand two kharif seasons in three replications.

● Sh. OV Ramana, Technical Officer at NationalResearch Centre on Sorghum, Hyderabad

Advised on how to perform principal componentanalysis, cluster analysis, using SPSS. DesignResources server was also demonstrated to him.The working of SPAR 2.0 was also explained tohim.

Consultancy and Advisory Services

80


● Dr. Shiv Datt, Senior Scientist (Genetics),Regional Research Station, Pali, Central AridZone Research Institute, Jodhpur

Advised on generation of randomized layout of anaugmented randomized complete block design for35 test and 3 check entries in 6 blocks.

● Chanchal Pramanik, M.Sc. (AgriculturalStatistics) student, Department of Statistics &Mathematics, Acharya N.G. Ranga AgriculturalUniversity, Rajendranagar, Hyderabad

Advised on generation of the randomized layoutof a square lattice design with 196 treatments in 3replications. He was also advised on the steps ofanalysis of data using the link Resolvable BlockDesign on the page “Analysis of Data” availableon the Design Resources Server.

● Dr. Subhadra Singh, Senior Scientist,Department of Genetics, CCS HAU, Hisar

Advised on the use of α-design with parametersv = 105, b = 30, r = 2, k = 7 for the experimentconducted to evaluate 105 RILs of wheat crop.

● Dr. Anupma, Senior Scientist, Division ofAgricultural Chemicals, IARI, New Delhi

Advised on the use of a fractional factorial plan in72 runs arranged in 4 blocks each of size 18 for a33×56 factorial experiment pertaining to preparationof super absorbent composites with maximumwater absorption characteristics and enhancedstability and moisture absorption behaviour in plantgrowth media with an aim to achieve maximum andfast rate of absorbency utilizing minimum possibleconcentration of monomer, crosslinker and alkali.

The various factors along with their levels are:

Factor Number of Levels

Nature of alkali (A) 3Duration of alkali exposure (B) 3Temperature of reaction (C) 3Concentration of alkali (D) 5Backbone: Clay ratio (E) 5Monomer concentrations (F) 5Crosslinker concentration (G) 5Initiator concentration (H) 5Volume of water (I) 5

The suggested fractional factorial plan is

Block -1

A B C D E F G H I0 0 0 0 0 0 0 0 01 1 1 4 4 4 4 4 42 2 2 2 2 2 2 2 20 1 1 3 1 2 2 0 21 2 2 1 2 3 0 4 32 0 0 2 3 1 4 2 10 2 1 2 4 0 1 2 31 0 2 3 2 4 2 3 12 1 0 1 0 2 3 1 20 1 2 2 3 1 1 3 21 2 0 0 1 2 2 1 32 0 1 4 2 3 3 2 10 0 0 3 2 0 4 1 21 1 1 1 3 4 2 2 02 2 2 2 1 2 0 3 40 0 2 4 4 2 1 2 01 1 0 2 2 3 2 0 42 2 1 0 0 1 3 4 2

Block 2

0 2 0 1 4 1 3 3 41 0 1 2 2 2 1 1 22 1 2 3 0 3 2 2 00 2 1 2 3 0 2 4 11 0 2 0 1 4 3 2 22 1 0 4 2 2 1 0 30 1 2 2 2 1 0 1 01 2 0 0 3 2 4 2 42 0 1 4 1 3 2 3 20 2 0 1 2 4 2 2 21 0 1 2 3 2 3 0 02 1 2 3 1 0 1 4 40 1 1 0 2 2 0 2 11 2 2 4 0 0 4 3 22 0 0 2 4 4 2 1 30 0 2 1 0 2 2 4 11 1 0 2 4 3 0 2 22 2 1 3 2 1 4 0 3

Block 3

0 0 2 4 3 2 2 1 41 1 0 2 1 0 3 2 22 2 1 0 2 4 1 3 00 1 1 3 2 2 3 2 41 2 2 1 3 3 1 0 22 0 0 2 1 1 2 4 0

81


0 2 0 4 2 1 2 2 21 0 1 2 0 2 0 3 32 1 2 0 4 3 4 1 10 1 2 2 2 4 3 4 31 2 0 3 0 2 1 2 12 0 1 1 4 0 2 0 20 2 1 2 0 3 2 1 41 0 2 3 4 1 0 2 22 1 0 1 2 2 4 3 00 2 0 4 1 4 0 0 11 0 1 2 2 2 4 4 22 1 2 0 3 0 2 2 3

Block 4

0 0 2 1 1 2 4 2 31 1 0 2 2 0 2 3 12 2 1 3 3 4 0 1 20 0 0 0 2 3 1 4 21 1 1 4 0 1 2 2 32 2 2 2 4 2 3 0 10 1 2 2 0 4 4 0 21 2 0 3 4 2 2 4 02 0 1 1 2 0 0 2 40 2 1 2 1 3 4 2 01 0 2 0 2 1 2 0 42 1 0 4 3 2 0 4 20 1 1 0 4 2 2 3 21 2 2 4 2 0 3 1 02 0 0 2 0 4 1 2 40 0 0 3 3 3 3 3 31 1 1 1 1 1 1 1 12 2 2 2 2 2 2 2 2

● Dr. Sunil Jha, Senior Scientist, Division of PostHarvest Technology, IARI, New Delhi

Advised on the analysis of data pertaining to anexperiment conducted to study the firmness of 8hybrid mango cultivars at different storage days(first day to 15 days at unequal intervals). Theexperiment was conducted using 3 replications.Due to unequal days interval, the data were non-orthogonal with three classifications. The data wereanalyzed using three way classified data. In theanalysis hybrids, storage days and their interactionwere found to be significant.

● Ph.D. (Animal Genetics and Breeding) studentfrom NDRI, KarnalAdvised on fitting of Multiphasic Logistic Functionon milk yield of Karanfries cows over time period.The steps for fitting the function using SAS werealso explained.

● Two collaborative studies namely (i) Survey ofagricultural accidents for the year 2004-05 in a largesample of villages selected on the basis of statisticalconsideration with AICRP on ESA (Ergonomics &Safety in Agriculture) and (ii) Assessment of postharvest losses of crops/commodities with AICRPon PHT have been undertaken.

Projects undertaken in Consultancy Mode● “Evaluation of rationalization of minor irrigation

statistics scheme”, funded by the Ministry of WaterResources, Govt of India. The items of data beingcollected in the scheme were examined and anassessment of data quality was made. Further,the suggestions for improvements in methodologyand infrastructure developed, were made. Thedraft report of the study has been finalized andsubmitted to the funding agency. The commentsreceived on the draft report have also beenincorporated and report re-submitted to thefunding agency. A presentation on the details ofevaluation was made to the Ministry of WaterResources, Govt. of India.

● “Estimation of urban slum population in the countryand capacity building”, funded by the Ministryof Housing and Urban Poverty Alleviation,Government of India. Under this project state wisemodels have been developed for estimation ofreasonable estimates of urban slum population ofcities/ towns based on 2001 census. These modelsare based on information from important censusvariables after their transformation to a new set ofindependent explanatory variables. In case ofsmaller states multilevel model was fitted afterincorporation of state effect in the model. Further,projections of the slum population in different yearswere obtained based on the basis of populationprojections of urban sector of each state afterincorporation of estimated correction factor for slumpopulation.

Quinquennial Review Team (QRT)

A Quinquennial Review Team (QRT) was constitutedby the Director General, Indian Council of AgriculturalResearch (ICAR), New Delhi to review the work doneby the Institute for the period 2001-05. The QRT reportof the Institute for the period 2001-05 has been approvedby the Council and Council’s comments and plan ofaction for implementation were received and actiontaken report on the recommendations of the QRT wassent to the Council.

Research Advisory Committee (RAC)

The composition of Joint Research Advisory Committee(RAC) of the Indian Agricultural Statistics ResearchInstitute (IASRI) and National Centre for AgriculturalEconomics and Policy Research (NCAP) constituted fora period of three years w.e.f. 29 January 2007 is asfollows:

1. Dr. PV Shenoi ChairmanFormer Special Secretary, (DAC)

Shantiprem, 20-C, First Main RoadRaj Mahal Villa ExtensionStage-II, Block-I, Bangalore-560 094

2. Dr. SS Acharya MemberHonorary Professor33, Shahi Complex, Sector -11Udaipur-313 002 (Rajasthan)

3. Dr. Rahul Mukerjee MemberProfessorIndian Institute of ManagementJoka Diamond Harbour RoadP.O. Alipur, Kolkata-700 027 (W.B.)

4. Dr. AK Nigam MemberA-2/605, Shoba Aqua MarineBellander, Outer Ring RoadBangalore-560 037

5. Dr. AP Gore MemberBakul, 40 Empress Garden View SocietySopan Baug, Pune-411 001

QRT, RAC, Management Committee and IRC

84


6. Dr. SM Jharwal MemberChairmanNational Pharmaceutical PricingAuthority, Department of Chemicals &Petrochemicals, Ministry of Chemicals &Fertilizers, Govt. of India, 3rd FloorYMCA Culture Centre Building1, Jai Singh Road, New Delhi-110 001

7. Dr. Rajeeva L Karandikar MemberProfessorChennai Mathematical InstitutePlot H 1, CIPCOT IT Park, Padur P.O.Siruseri-603 103 (Tamil Nadu)

8. Prof. VK Bhatia Member SecretaryDirectorIndian Agricultural Statistics ResearchInstitute (IASRI)Library Avenue, Pusa CampusNew Delhi-110 012

9. Dr. Ramesh Chand MemberDirectorNational Centre for Agricultural Economicsand Policy Research (NCAP)Library Avenue, Pusa CampusNew Delhi-110 012

10. Dr. Lal Krishna MemberAssistant Director General (ESM)Indian Council of Agricultural ResearchKrishi Bhawan, New Delhi-110 114

The 11th meeting of the Research Advisory Committeeof IASRI and 3rd meeting of the Joint Research AdvisoryCommittee (RAC) of IASRI and NCAP was held on16 January 2010 under the Chairmanship of Dr. PVShenoi, former Special Secretary, Ministry of Agricultureand Co-operation, New Delhi.

The meeting was attended by all the members exceptDr. Rahul Mukerjee, Dr. SM Jharwal, Dr. Rajeeva LKarandikar and Dr. Lal Krishna. Dr. VK Gupta, NationalProfessor, ICAR, Dr. Ramesh Chand, NationalProfessor, ICAR, HDs from IASRI and PrincipalScientists from NCAP also attended the meeting asspecial invitees.

Dr. VK Bhatia, Director, IASRI presented theachievements, functions, and future research programsof IASRI. The details of the training and teachingactivities of IASRI were also presented by him.

Dr. BC Barah, Acting Director, NCAP presented theachievements, functions, impact and future researchprograms of NCAP. He also presented new policyinitiatives undertaken by NCAP.

After these presentations, Chairman made openingremarks. He invited the suggestions from all themembers on presentations made on the researchachievements and future programs of both the Institutesand after discussions, the following actionable pointsemerged:

1. Both IASRI and NCAP should involve themselvesin macro-studies having national importance. Microstudies should only be taken up for developingmethodologies.

2. Both IASRI and NCAP should concentrate on thebasic research in the problems arising from the realapplications in agricultural research and also onnovel applications of statistical, econometric andinformatics tools. These Institutes should not involvethemselves in data generation or providingestimates as there are several other governmentagencies for performing these tasks.

A view of 11th meeting of the Research Advisory Committee

85


3. IASRI should continue rigorously pursuing theefforts in applications of Design of Experiments inNational Agricultural Research System.

4. The research efforts in small area estimation maybe strengthened.

5. Both IASRI and NCAP should prepare the index onfood security, land degradation, etc. on macro levelfor state/country rather than district level indices.

6. IASRI should impart trainings only in the advancedlevel of statistical techniques and for basic principlesof statistical techniques, it is suggested to explorethe possibility of utilizing the strength available withdifferent SAUs and General Universities for itsoutreach activities such as sensitizing theagricultural researchers in the statistical techniquesand their potential applications in agriculturalsciences.

7. Vacant scientific positions at IASRI and NCAPshould be filled on priority basis and for thisconcerned authorities may be approached.

8. Combining the disciplines of Agricultural Statisticsand Computer Applications in ASRB Examinationswould affect the quality of research. The authoritiesin ASRB need to be informed urgently andrequested to take remedial measures on priority.

Institute Management Committee

The Director of the Institute, who is In-charge of theoverall management of the Institute, is assisted in thedischarge of his functions by the Institute ManagementCommittee (constituted by the Council) by providing abroad-based platform for decision making process byperiodically examining the progress of the Instituteactivities and by recommending suitable remedialmeasures for bottlenecks, if any. The present InstituteManagement Committee comprises of:

1. Prof. VK Bhatia ChairmanDirector, IASRI (ICAR)New Delhi-110 012

2. Director (Agriculture) MemberGovernment of Delhi, ITONew Delhi-110 001

3. Sh. VK Singh MemberDirector, Agriculture StatisticsGovernment of Uttar PradeshLucknow, Uttar Pradesh

4. Dr. HS Gupta MemberDirectorIARI, New Delhi-110 012

5. Prof. Devi Prasad Tripathi Non-Official MemberGeneral Secretary &Chief SpokesmanNational Congress PartyC-9/9782, Vasant KunjNew Delhi-110 070

6. Sh. Madhusudan Sathe Non-Official MemberYashodhan, 2071Vijay Nagar ColonyNear SP CollegePune-411 030

7. Finance and Accounts Officer MemberIARI, Pusa, New Delhi-110 012

8. Dr. PK Agarwal MemberNational Professor, ICARIARI, Pusa, New Delhi-110 012

9. Dr. Madhuban Gopal MemberNational FellowDepartment of ChemicalsIARI, New Delhi-110 012

10. Dr. RK Mahajan MemberPrincipal Scientist (Agril. Stat.)Division of Germplasm EvaluationNBPGR, Pusa, New Delhi-110 012

11. Dr. RL Sapra MemberPrincipal Scientist (Agril. Stat.)Division of GeneticsIARI, Pusa, New Delhi-110 012

12. Dr. SK Tandon MemberAssistant Director General (Engg.)KAB-II, ICAR, PusaNew Delhi-110 012

13. Head of Office Member SecretaryIASRI (ICAR)New Delhi-110 012

The 58th Meeting of the Insitute ManagementCommittee was held on 13 January 2010 under theChairmanship of Dr. V.K. Bhatia, Director, IASRI. Thefollowing agenda items were discussed:

● Confirmation of proceedings of the 57th meeting ofthe Management Committee held on 17 January2009.

86


● Review of action taken on recommendations of the57th meeting of the Management Committee heldon 17 January 2009.

● Significant research achievements with respect toProject Information and Management System ofICAR (PIMS-ICAR) and Expert System on WheatCrop Management were presented by the scientistsof the Institute.

● Proceedings of Institute Research Committeemeeting.

● Budget estimates for the year 2009-10 and actualexpenditure incurred upto 31 December 2009 inrespect of Plan/Non-plan of the Institute.

● Reconstitution of Institute Grievance Committee.

● To review the allotment rules of IASRI staff quarters.

● Any other item with the permission of the Chair.

morning of summer vacations so as to enable themto complete their respective degrees in stipulatedperiod.

Institute Research Committee

The Institute Research Committee (IRC) is an importantforum to guide the scientists in the formulation of newresearch projects and to review the progress of on-goingresearch projects periodically. It also monitors the followup action on the recommendations of the QuinquennialReview Team (QRT), Research Advisory Committee(RAC) in respect of technical programmes of theInstitute. Dr. V.K. Bhatia, Director is the Chairman andDr. Rajender Parsad, In-charge (RCMU) is the MemberSecretary of the IRC.

Two meetings of the Institute Research Committee (IRC)were held during 18–20 August 2009 and 19–20

Some specific recommendations with respect toresearch and teaching activities of the Institute were:

1. Members expressed their serious concern aboutthe large number of vacant scientific personnelpositions. They felt that necessary proposal maybe sent to the Council for recruitment andplacement of scientists at the Institute on prioritybasis so that research and teaching activities canbe carried out smoothly.

2. The declining number of students in M.Sc. andPh.D. in Agricultural Statistics and ComputerApplication was viewed seriously by all themembers and it was decided that AcademicCouncil, PG School, IARI may be approached toallow the students from Mathematical/StatisticalSciences to take remedial courses during early

February 2010. In the first meeting 05 new researchprojects were approved and progress of 46 (37 Institutefunded, 02 in collaboration with other Institutes, 06outside funded and 01 AP cess funded) ongoingresearch projects were discussed and 04 researchprojects were declared completed. In the secondmeeting one new research project was approved andprogress of 46 (35 Institute funded, 02 in collaborationwith other Institutes and 09 outside funded) ongoingresearch projects were reviewed and 11 researchprojects were declared completed.

Two meetings of the Institute Research Committee(special) were held on 06 July 2009 and 02 January2010 to discuss and modify the six monthlyachievements and targets fixed by the scientists of theInsitute before sending them to the Council.

58th meeting of the Management Committee is in progress A view of Institute Research Committee meeting

RESEARCH PAPERS PRESENTED

National Seminar on "Prioritization of Interventionsin Rainfed Areas for Sustainable Livelihoods" atNASC Complex, New Delhi during 23-24 April 2009

● Rai, Anil. Livelihood status of different agro-climaticzones in India.

Technical Session in the Coordination CommitteeMeeting of AICRP on FIM held at College ofAgricultural Engineering & Post Harvest Technology(CAEPHT), Central Agricultural University, Ranipool,Gangtok (Sikkim) during 04-06 May 2009

● Tyagi, KK. Status and projection estimates ofagricultural machinery and implements.

Group Meeting of STCR (AICRP) held atANGRAU, Hyderabad during 06-07 June 2009

● Lahiri, Aloke. Design and analysis ofSTCR experiments and layout of the newexperiment.

USDA-ERS Workshop at Washington DC during09-10 June 2009

● Vasisht, AK and Dahlgran, Roger A. Contractdesigns and trading bans on India’s futures contract.

SAE 2009 Conference on "Small Area Estimation"held at Elche, Spain during 29 June - 01 July 2009

● Chandra, Hukum. Small area estimation ofproportions in business surveys.

2nd National Conference on "Innovation in IndianScience Engineering and Technology" held atNPL, New Delhi during 17-19 July 2009● Kaul, Sushila. India’s economic reforms and

agriculture sector.● Kaul, Sushila. Historical review implementation and

benefits of ISO 9001 certification in different sectorsincluding agriculture.

Workshop on "Improvement of AgriculturalStatistics" held at NASC Complex organized by

Papers Presented and Participation of the Instituteat the Conferences/Workshops, Etc.

88

Papers Presented and Participation of the Institute at the Conferences/Workshops, Etc.

Directorate of Economics and Statistics during11-12 August 2009

● Ahmad, T. Causes of variation between officialand trade estimates of cotton production: Astatistical investigation.

● Sahoo, Prachi Misra. Remote sensing and GISbased methodology for crop acreage estimationin north eastern hilly regions.

20th Columbian Statistics Symposium by NationalUniversity of Columbia held at Coastal city of SantaMarta during 11-15 August 2010

● Chandra, Hukum. Small area estimation.

57th Session of International Statistical Institute(ISI 2009) Conference in association with theDepartment of Economics and Statistics atDurban, South Africa during 16-22 August 2009

● Chandra, Hukum and Chambers, R. Small areaestimation under transformation to linearity.

● Chambers, R, Chandra, H, Salvati, N andTzavidis, N. Outlier robust small area estimation.

Workshop on "Improvement of Statistical Systemin Kerala State" organized by Kerala StatePlanning Board in association with theDepartment of Economics and Statistics on 20August 2009

● Sud, UC. Small area estimation-Someapplications in India.

National Level Workshop cum Seminar on "IndianCommodity Market Derivatives and RiskManagement-The Road Ahead" held atPuducherry during 11-12 September 2009

● Bhardwaj, SP and Vasisht, AK. Price discoveryin commodity markets - A case study of gram.

● Vasisht, AK and Bhardwaj, SP. An analysis ofvolatility of agricultural prices – A case study ofmaize.

National Symposium on "Advances in Geo-Spatial Technologies with Special Emphasis onSustainable Rainfed Agriculture" and AnnualConvention of Indian Society of Remote Sensing(ISRS) 2009 held at Nagpur during 17-19September

● Kapoor, Nit ika and Sahoo, Prachi Misra.Extraction of information under cloud cover fromsatellite image using kriging.

● Kundu, Seema and Sahoo, Prachi Misra. Webbased mapping using ARCIMS.

Seminar on "Commodity Derivative Markets:Opportunities and Challenges" organized byTakshashila Academia of Economic ResearchLimited (TAER) and Institute of Studies in IndustrialDevelopment (ISID) held at New Delhi on 30 October2009

● Vasisht, AK. An econometric analysis of efficiencyof agricultural commodity futures market and pricediscovery.

23rd National Conference of Indian Society ofAgricultural Marketing held at CRIDA, Hyderabadduring 12-14 November 2009

● Bhardwaj, SP and Vasisht, AK. Strategic measuresto meet marketing challenges in the changingscenario of liberalisation.

● Bhardwaj, SP. Innovative models to reap marketincentives.

● Vasisht, AK and Bhardwaj, SP. Price dynamicsof agricultural commodity futures and its impacton demand-supply situation of agriculturalcommodities.

63rd Annual Conference of ISAS held at RAU, Pusa,Bihar during 03-05 December 2009

Technical Address

● Bhatia, VK. Growth of quantitative genetics andestimation of genetic parameters.

Invited Talks

● Bhatia, VK. Bio-informatics in agriculture.Symposium on Statistical and ComputationalGenomics.

● Parsad, Rajender, Gupta, VK and Sarkar, Ananta.Design and analysis of microarray experiments.Symposium on Statistical and ComputationalGenomics.

● Bhatia, VK. Modelling climate effects. Symposiumon Statistical and Informatics Perspectives ofClimate Change.

● Parsad, Rajender, Gupta, VK and Malhotra, RS.Experimental designs for mitigation and adaptationstrategies of climate change. Symposium onStatistical and Informatics Perspectives of ClimateChange.

89


● Rai, Anil, Chaturvedi, KK and Malhotra, PK. Spatio-temporal data mining for monitoring of climatechange. Symposium on Statistical and InformaticsPerspectives of Climate Change.

Contributed Papers

● Wahi, SD and Rao, AR. Some investigations onsampling variance of genetic correlation.

● Paul, AK, Singh, Mohan Das and Wahi, SD. Someinvestigation on the statistical properties ofgoodness of fit criteria of non-linear growth curvesthrough bootstrap technique.

● Arnab, R and Sud, UC. A note on varianceestimation of ratio estimator under two phasesampling.

● Singh, Jagbir. Estimation from independent subsamples of a population.

● Arya, Prawin, Vasisht, AK, Shivaramane, N andSingh, DR. Market investigation in coarse cerealsin India: A case of maize and jowar.

● Kaul, Sushila. Implications of global warming onagricultural production in India.

● Agrawal, Ranjana, Chandrahas and Kausav,Aditya. Use of discriminant function analysis forforecasting wheat yield.

● Ramasubramanian, V, Bhatia, VK, Kumar,Amrender, Pal, Satya and Premi, Sarvesh Kumar.Forecasting technological needs in genetics andplant breeding for sustainable agriculture.

Workshop of AICRP on LTFE held at IGKV, Raipurduring 06-08 December 2009● Sehgal, DK. Superimposition/bifurcation of

treatments in long term fertilizer experiments.

CSISA Experimental Platform Meeting held at ICAR-RCER Patna during 14-16 December 2009

Invited Talk● Parsad, Rajender. Designs of experiments with

emphasis on CSISA experimental platform.

International Conference on Artificial Intelligence(IICAI 09) held at Tumkur, Bangalore during 16-18December 2009

● Sudeep. Disease and pest identification in crops –A semantic web approach.

● Arora, Alka, Upadhyaya, Shuchita, Jain, Rajni.Approach for mining multiple patterns fromclusters.

Humanising Work and Work Environment 2009Conference held at Kolkata during 17-19 December2009

● Gite, LP, Tiwari, PS, Khadatkar, Abhijit (CIAE)Tyagi, KK, Bathla, HVL and Kher, KK. Farmmachinery accidents in Indian agriculture.

69th Annual Conference of ISAE held at GNDUniversity, Amritsar during 17-19 December 2009● Kaul, Sushila. Urbanization and its implications for

agriculture production.

International Conference-FSES, 2009 held at IIT,Kharagpur during 17-19 December 2009

● Vasisht, AK. On adoption pattern and factorsinfluencing the adoption of RCTs in Indo-Gangeticplains of India.

Dissemination Workshop on "Mixture Experiments:Theory and Applications" jointly organizedby Department of Statistics, Calcutta Universityand Department of Statistics, Kalyani University atBCKV, Kalyani during 21-22 December 2009

Invited Talks

● Batra, PK, Alam, N and Parsad, Rajender. Designsfor multi-factor mixture experiments.

● Parsad, Rajender and Gupta, VK. Design resourcesserver.

● Parsad, Rajender. Applications of experiments withmixtures methodology.

● Lal, Krishan and Gupta, VK. Efficient mixturedesigns with process variables in agriculture.

7th International Triennial Calcutta Symposium on"Probability & Statistics" held at the University ofCalcutta during 28-31 December 2009

● Chandra, H and Chambers R. Small area estimationfor skewed data in presence of zeros.

International Conference on "Frontiers of Interfacebetween Statistics and Sciences" held at C.R. RaoAIMSCS University of Hyderabad Campus,Hyderabad during 30 December 2009 to 02 January2010

● Ghosh, Himadri. Application of statistical learningtheory for fitting multimodal distribution to rainfalldata.

90


97th Session of Indian Science Congress held atTrivandrum, Kerala during 03-07 January 2010

● Agrawal, Ranjana, Chandrahas and Kaustav,Aditya. Use of discriminant function analysis forforecasting wheat yield.

● Varghese, Eldho, Jaggi, Seema and Varghese,Cini. Row-column designs balanced for nearestneighbours.

● Meher, Prabina Kumar, Rao, AR, Wahi, SD andJaggi, Namita. An empirical investigation ondetection of multivariate outliers in breeding data.

● Mehta, SC, Pal, Satya and Kumar, Vinod. Weatherbased models for forecasting potato yield in UttarPradesh.

International Conference on Statistics, Probability,Operations Research, Computer Science and AlliedAreas held at Andhra University, Visakhapatnamduring 04-08 January 2010

Invited Talks

● Bhatia, VK and Paul, AK. Genetics of stayability ofdairy cattle. Session on Recent Advances inStatistical Genetics.

● Gupta, VK, Kole, Basudev, Parsad, Rajender andBhar, LM. Efficient mixed level supersaturateddesigns. Session on Design of Experiments.

● Parsad, Rajender, Gupta, VK, Bhar, LM and SubrataK Behera. Block designs with factorial treatmentstructure for cropping systems research. Sessionon Design of Experiments.

● Prajneshu and Ghosh, Himadri. Statisticalmodelling. Session on Statistical Modeling.

Contributed Paper

● Ghosh, Himadri. Nonlinear parametric mixture time-series modelling.

International Applied Statistics Conference 2010 heldin Colombo, Sri Lanka during 08-09 January 2010

● Abeynayake, NR and Jaggi, Seema. A review ofblock designs with neighbour effects.

National Meet of Tractor and Agricultural MachineryManufacturers held at PAU Ludhiana during 16-17January 2010

● Tyagi, KK, Singh, Jagbir, Kher, KK, Jain, VK andSingh, Surendra. Status and projection estimatesof agricultural implements and machinery.

International Conference on "Optimization and itsApplication" held at Banaras Hindu University on17 February 2010

Invited Talk

● Prajneshu. Fuzzy regression models.

11th International Conference of the InternationalAcademy of Physical Sciences held at Universityof Allahabad on 20 February 2010

Invited Talk

● Prajneshu. Nonlinear time–series models.

XII Annual Conference of Society for Statistics,Computer and Applications held at Department ofStatistics, Siksha Bhavana, Visva Bharati during24-26 February 2010

Invited Talks

● Gupta, VK, Bhar, LM, Parsad, Rajender and Kole,Basudev. Efficient unbalanced mixed-levelsupersaturated designs.

● Gupta, VK, Kole, Basudev and Parsad, Rajender.Mixed level supersaturated designs.

● Parsad, Rajender, Gupta, VK and Malhotra, Raj S.Experimental designs for mitigation and adaptationstrategies of climate change. Symposium onStatistics for Studying the Impact of Climate Change.

Contributed Papers

● Bhowmik, Arpan, Ramasubramanian, V,Chandrahas and Kumar, Adarsh. Logisticregression for classification in agriculturalergonomics.

● Gupta, VK, Singh, Poonam, Kole, Basudev andParsad, Rajender. Addition of runs to asupersaturated design.

● Ramasubramanian, V, Bhatia, VK, Garg, KG,Kumar, Suresh, Kumar, Amrender and Kumari,Jyoti. Technological scenario in plant genetic andbreeding using scientometrics.

National Symposium on "Lifestyle Floriculture:Challenges and Opportunities" held at Dr. YSParmar University of Horticulture and Forestry,Nauni, Solan (HP) during 19-21 March 2010● Gupta, AK. Estimation of area, production and

productivity of flowers.

91


1st IFIP International Conference on "Bioinformatics"held at Sardar Vallabhbhai National Institute ofTechnology, Surat during 25-28 March 2010

● Bhardwaj, Ankush, Avanti, S, Pandey, Bharati andRao, AR. A functional elements SNPs informationsystem of rice genome.

● Saini, Vandna, Pandey, Bharati, Bhardwaj, Ankushand Rao, AR. In-silico analysis of splice sites of ricegenome.

National Workshop on "Applicable Statistics" heldat Department of Statistics, M.D. University, Rohtakduring 28-30 March 2010

Invited Talks

● Bhatia, VK. Application of statistics for growth ofquantitative genetics and estimation of geneticparameters.

● Prajneshu. Nonlinear statistical models and theirapplications.

● Parsad, Rajender. Applications of experiments withmixtures.

PARTICIPATION

● NAIP meeting at Krishi Anusandhan Bhawan-II, NewDelhi on 15 April 2009.

● Meeting of round table on Global Economic SlowDown and Indian Agriculture at IARI, New Delhi on24 April 2009.

● 10th ESRI India users conference on Geography inaction held at Noida, National Capital Region Delhiduring 28-29 April 2009.

● Global rice modeling initiative at IRRI organised bySoil Science Division, IRRI, Philippines at NCAP,New Delhi on 30 April 2009.

● 2nd Dayanatha Jha Memorial lecture on Emergingtrends in Indian agriculture: What we can learn fromthis?” delivered by Dr. Ashok Gulati, Director in Asia,IFPRI held at NCAP, New Delhi on 02 May 2009.

● Sensitization meeting regarding project onBioprospecting of genes and allele mining for abioticstress tolerance held at NASC Complex, New Delhiduring 05-06 May 2009.

● Coordination Committee meeting of AICRP on FIMat College of Agril. Engg. and Post HarvestTechnology (CAEPHT), Central Agril. University,Gangtok (Sikkim) during 04-06 May 2009.

● Second meeting of Prof. Vaidyanathan Committeeheld at NASC Complex, Pusa, New Delhi during05-06 May 2009.

● Meetings of Advisory Panel of Third census ofhandlooms and issues of photo identity cards toweavers and allied workers held at NCAER, NewDelhi on 12 and 14 May 2009.

● Discussion regarding National achievement surveysat different stages of school education under ServaShiksha Abhiyan (SSA) held at NCERT, New Delhion 20 May 2009.

● Meeting with Dr. P.K. Mohanty, Jt. Secy & MissionDirector, Jawahar Lal Nehru National UrbanRenewal Mission, Ministry of Housing & UrbanPoverty Alleviation on 27 May 2009.

● Meetings on Estimation of harvest and post harvestlosses held at CIPHET, Ludhiana on 09 April 2009and held at CTCRI, Trivandrum during 29-31 May2009.

● Meetings of the Empowered Committee forImplementation of the Scheme Awards &Fellowships and Outstanding and MeritoriousResearch Studies in Statistics at New Delhi on 03June, 10 September, 10 December 2009 and 04March 2010.

● Vichar Manch on Issue on the Balckburner bySmt. Shashi Mishra, Ex-Secretary, ICAR held atNASC Complex on 03 June 2009.

● Foundation Day of NAAS and lecture ofProf. Sukhdeo Throat, Chairman UGC onHigher Education and XI Plan Approachand Strategies at NASC Complex, New Delhi on04 - 05 June 2009.

● Meeting with Dr. Sanjay Sharma, Principal SystemAnalyst, NIC held at Krishi Bhawan, New Delhi on05 June 2009 to discuss village level census dataof East Khasi Hills districts of Meghalaya.

● Meeting under the Chairmanship of Economic andStatistical Adviser, DES held at Krishi Bhawan, NewDelhi on 10 June 2009 regarding the discussion ontesting of alternative methodology suggested byIASRI in a few states for estimation of area andproduction of horticultural crops besides otherhorticulture related issues.

● Application of Statistical Methods TechnicalCommittee meeting ISO/TC69 convened by

92


Department of Standards, Ministry of Science,Technology and Innovations, Government ofMalaysia at Kuala Lumpur, Malaysia during 13-19June 2009. India has represented in this Committeeas a Participating Member and as Member of IndianDelegate.

● Meetings regarding updation of tables in ARDB 2009with Sh. RC Sethi, Addl RGI at RGI Office on 16June 2009; with DDG (Engg.), ICAR on 25 June2009; with Dr. NPS Sirohi, Prof. Agril. Engg., IARI;Dr. KM Bajurbaruah, Dy. DG (Animal Sciences) on22 July 2009.

● International Conference on Climate change: Law,policy and governance held at India Habitat Centre,New Delhi on 19 June 2009.

● Meeting with Mr. Sanjay, Dy. Advisor (Stat), DES todiscuss the availability of crop cutting data at unitlevel, held at Shastri Bhawan, New Delhi on 24 June2009.

● Meeting of the sub-committee of National YouthReadership Study 2009 held at NCAER, New Delhion 26 June 2009.

● Meeting of Consortium Implementation Committeeof Risk assessment and insurance products foragriculture held at NCAP, New Delhi on 29 June2009.

● Director’s Meet with Deputy Director General(Agricultural Engineeringg) at ICAR, KrishiAnusandhan Bhawan-II, New Delhi on 15 July 2009.

● Inaugural Ceremony of Indian Council of AgriculturalResearch (ICAR) Foundation Day and Directors’conference at NASC Complex, New Delhi on16 July 2009.

● First meeting of the Standing Committee for 17th

Conference of Central and State StatisticalOrganizations (COCSSO) held at CSO, SardarPatel Bhawan, New Delhi on 23 July 2009.

● Meeting under the Chairmanship of Secretary,Ministry of Statistics & Programme Implementationto discuss the issues regarding Estimation of SlumPopulation in the Country at New Delhi on 23 July2009.

● Short term training program on Soft computing(SofCom’09) held at Center for Soft ComputingResearch, Indian Statistical Institute, Kolkata during27-31 July 2009.

● Meeting for the project on Sampling methodologyfor estimation of meat production in Meghalaya, withDirector (Animal Husbandry) and other official ofDirectorate of Animal Husbandry, Shillong,Meghalaya at Shillong during 28-29 July 2009 andwith Advisor (Statistics), Department of AnimalHusbandry, Dairying and Fisheries, Ministry ofAgriculture, Govt of India at DMS Complex,New Delhi on 16 April 2009.

● Workshop-cum-Brainstorming session on Remotesensing and GIS for accelerating growth inagricultural research and development held at IIRS,Dehradun on 31 July 2009.

● Discussions with concerned officials regarding studyon Evaluation of rationalization of minor irrigationstatistics scheme held at Hubli during 06-08 August2009.

● 15th meeting of Statistical Methods for Qualityand Reliability Sectional Committee MSD-3 inBureau of Indian Standards (BIS) at New Delhi on12 August 2009.

● Lecture on Collaboration and Partnership the Futureof Higher Education by Dr. Gordon Gee, Presidentof Ohio State University at NASC Complex, NewDelhi on 13 August 2009.

● Workshop on Information technology application inhorticultural crops held at CPRI, Shimla during24-25 August 2009.

● Meeting with Dr. Surendra Singh, ProjectCoordinator, AICRP on FIM, for reviewing theprogress of the project on Study on status andprojection estimates of agricultural implements andmachinery on 25 August 2009.

● Workshop on Study on assessment of future humancapital requirements in agriculture organized by theInstitute of Applied Manpower Research incollaboration with NAARM held at India HabitatCentre, New Delhi on 26 August 2009.

● Inaugural ceremony of launch of NAIP Consortiumon Strengthening of Digital Library and InformationManagement and NARS (e-granth) at NationalResearch Centre on Plant Biotechnology, New Delhion 27 August 2009.

● 48th All India Wheat and Barley Research Worker’sMeet held at IARI, New Delhi during 28-31 August2009.

93


● Fifth meeting of the panel for Basic StatisticalMethods (MSD 3/P-1) at New Delhi on 06September 2009.

● 2nd meeting of the Working Group for theConstruction of index numbers of area, productionand yield of agricultural crops held at Krishi Bhawanunder the chairmanship of ESA, Ministry ofAgriculture, Govt. of India on 17 September 2009.

● Meeting on Profile of Indian scientists in six majorscientific agencies under the Chairmanship of Sh.Rakesh Chetal, Advisor, DST held at IndiaInternational Centre (Annex), New Delhi on17 September 2009.

● 4th meeting of the Technical Committee on FASALheld at Krishi Bhawan under the chairmanship ofPrincipal Advisor, DES, Ministry of Agriculture,Govt. of India on 23 September 2009.

● Lecture on Reconstructing Indian Population Historyby Dr. Lalji Singh, Director, Centre for Cellular andMolecular Biology, Hyderabad at NASC, New Delhion 25 September 2009.

● Meeting on PERMISnet-II with Finance Advisor andhis staff, and Deputy Secretary (ICAR) held at KrishiBhawan on 05 October 2009.

● Meeting of the Ad-hoc Board of Studies inAgricultural Statistics of CCS University, Meerut on13 October 2009.

● First meeting of the Advisory Committee onRecruitment of Official Statisticians through IndianStatistical Service (ISS) and Subordinate StatisticalService (SSS) held at Ministry of Statistics andPIanning, National Academy of StatisticalAdministration, Greater Noida, U.P. on 14 October2009.

● First CAC meeting of ICAR-NAIP funded Networkproject on bioprospecting of genes and allele miningfor abiotic stress tolerance at NASC Complex, NewDelhi on 21 October 2009.

● Monitoring Committee meeting of CeRA sponsoredby National Agricultural Innovation Project, ICAR,New Delhi held at CIBA, Chennai on 21 October2009.

● Brainstorming session on Agricultural wastemanagement convened by Dr. NSL Srivastava, JointDirector, SPRERI, Gujarat held at NASC Complex,New Delhi during 23-24 October 2009.

● Winter School as a Chief Guest, on Decision makingin agriculture using data mining held at NationalCentre for Agricultural Economics & PolicyResearch (NCAP), New Delhi on 27 October 2009.

● Meeting of Mid-Term Review (MTR) of theDepartment of Agricultural Research & Education(DARE)/ICAR for the 11th Five Year Plan at IARI,New Delhi on 28 October 2009.

● 61th meeting of MSD 3:3 held at New Delhi on12 November 2009.

● Workshop on Sampling design and methodology toassess the socio-economic conditions of fishers andfish farmers in India held at Central Institute ofBrackishwater Aquaculture (CIBA) Chennai during12-14 November 2009.

● Training programme on IT-based decision supportsystems for multi-media content development heldat NAARM, Hyderabad during 17-27 November2009.

● HLCC meeting held at Chandigarh under theChairmanship of Principal Secretary to Govt. ofHaryana, Agriculture Department, Chandigarh on20 November 2009.

● Workshop of Networking of agricultural economistunder V-PAGe held at TNAU, Coimbatore on21 November 2009.

● Workshop on Achieving food security in India:Improving competition, markets and the efficiencyof supply chains held at Hotel Claridges, New Delhion 24 November 2009.

● Meeting to discuss the issues related to upgradationof Automatic Weather Station (AWS) and AutomaticRain Gauges Stations (ARGs) for expansion ofWeather Based Crop Insurance Scheme (WBCIS)under the chairmanship of Secretary (Agriculture &Cooperation) at Krishi Bhawan, New Delhi on25 November 2009.

● Meeting with Advisor, DES, Ministry of Agricultureto discuss technical & financial aspects of the projecton Study to develop an alternative methodology forestimation of cotton production held at KrishiBhavan, New Delhi on 27 January 2010.

● 19th Group Workers meeting of AICRP (STF) heldat BSKKV, Dapoli during 14-17 December 2009.

● Meeting of Technical Committee of Direction (TCD)for improvement of Animal Husbandry and Dairying

94


Statistics at Orissa, Bhubaneshwar during 17-19December 2009.

● Workshop-cum-Training Programme onBioinformatics applications in crop science held atIARI during 21-23 December 2009.

● Inaugural function of Platinum Jubilee Symposiumand 74th Annual Convention of Indian Society of SoilSciences at Dr. B.P. Pal Auditorium, IARI, New Delhion 22 December 2009.

● 81st Annual General Meeting of the ICAR Societyat NASC, New Delhi-110012 on 23 December2009.

● 379th meeting of the Academic Council at IARI,New Delhi on 24 December 2009 .

● PMAC Review Meeting for NAIP project V-PAGeheld at NCAP, New Delhi on 30 December 2009.

● 5th workshop of AICRP on Ergonomics and safetyin agriculture (ESA) held at DBSKKV, Dapoli(Maharashtra) during 06-08 January 2010.

● Short term training programme on Knowledgediscovery in data bases: Data, Information andKnowledge (DInK’10) held at Center for SoftComputing Research, Indian Statistical Institute,Kolkata during 11-15 January 2010.

● Global Meet on Green Revolution II held at HotelLalit, New Delhi during 08-09 February 2009.

● National conference on Futures of commodityfutures market held at Hotel La Meridian, New Delhion 09 February 2010.

● 48th Convocation of IARI on 13 February 2010.

● Training programme on Technical and Administrativesupport for consortia based research in agricultureheld at NAARM, Hyderabad during 22-27 February2010.

● Seminar by Kenneth M Quinn, President, Councilof Advisors of the WFP held at NASC Complex,New Delhi on 24 February 2010.

● Seminar on Climate change - Role of cooperativesheld at NCUI, New Delhi on 25 February 2010.

● Seminar on The Union Budget 2010-11: Reformand development perspectives organised byNCAER,CPR, ICRIER,IDF & NIPFP held atShangri-La Hotel, New Delhi on 06 March 2010.

● Training programme on Climate change,environmental sustainability and agricultural

development held at IARI, New Delhi during 09-29March 2010.

● ICAR Zonal Technology Management & BusinessPlanning and Development meeting–cum–workshop, 2009-10 North Zone held at IARI,New Delhi during 19-20 March 2010.

● Workshop-cum-Brainstorming session on Futuretechnological needs for rainfed agriculture in Indiaheld at CRIDA, Hyderabad on 19 March 2010.

● Workshop on ICT initiatives of the NAIP with specialreference to the uniformity guidelines for ICARwebsites held at NBPGR, New Delhi on 19 March2010.

● 33rd meeting of HLCC organized by Board ofRevenue for Rajasthan, Ajmer held at Jaipur on 22March 2010.

● Review meeting of Visioning, Policy Analysis andGender (V-PAGe) at NCAP, New Delhi on 26 March2010.

● Workshop on Risk assessment in agriculture heldat TNAU, Coimbatore during 26-30 March 2010.

Related to Professional Societies● Editorial Board meeting of Annals of Agricultural

Research, the Journal of the Indian Society ofAgricultural Sciences at Division of Agronomy, IARI,New Delhi.

● Executive Council meetings of Indian Society ofAgricultural Sciences at KAB II of ASRB, New Delhi.

● An Executive Council meeting of Indian Society ofAgricultural Statistics.

● Executive Council meetings of the Society ofStatistics, Computers and Applications.

● Governing Body meeting of the Institute of AppliedStatistics and Development Studies, Lucknow.

Trainings

● Sh. S.N. Islam participated in Training Programmeon Entrepreneurship Development underSustainable Farming System held at ICARResearch Complex for NEH Region, Sikkim Centre,Tadong, Gangtok during 25 May-14 June 2009 .

● Mohd. Samir Farooqi participated in TrainingProgramme on Procurement Related Matters andFinancial Management under NAIP held at NASCComplex during 12-13 August 2009.

95


● Sh. VH Gupta participated in the Winter School onDecision Making in Agriculture using Data Miningorganized at NCAP, New Delhi during 27 October-16 November 2009.

● Dr. PK Malhotra attended the Special TrainingProgramme for Vigilance Officers of ICAR Institutesorganised at IISR, Calicut during 22-24 February2010.

● Ms. Alka Arora and Ms. Shashi Dahiya attendedHands-on Training and Orientation Program heldon Drupal at DIPA, ICAR, New Delhi during 9-12March 2010.

Invited Lectures Delivered at Other Organisations

Dr. VK Bhatia● A lecture on Functions and activities of IASRI during

a workshop for four faculty members from Universityof Foreign Trade, Hanoi, Vietnam with fundingfrom Swiss Agency for Development andCo-operation Bern (IDC) on 23 April 2009.

● A lecture on Statistical genomics and estimation ofgenetics parameters under a Continuing Educa-tion Programme on Biostatistical Methods for LifeSciences at Defence Institute of Physiology andAllied Sciences (DIPAS), Defence Research andDevelopment Organization (DRDO), Delhi during14 -18 September 2009.

● A lecture on Sampling design and methodology toassess the socio-economic conditions of fishersand fish farmers in India at Central Institute ofBrackishwater Aquaculture, Chennai during 12-14November 2009.

Dr. Rajender Parsad

● An invited lecture on Statistical designing andanalytical techniques for varietal trials to theparticipants of the training programme in the areaof Vegetable Variety Development and Evaluationfor the officials of Ministry of Agriculture, Iraqsponsored by Food & Agriculture Organization ofUnited Nations held at Division of VegetableScience, IARI, New Delhi during 15 September -14 October 2009.

● Four invited lectures on Design of experiments andDesign resources server to the participants of thetraining programme on Statistical Analysis andInterpretation of Agroforestry Experimental Data

organized under the aegis of All India Co-ordinatedResearch Project on Agro-forestry at NationalResearch Centre for Agroforestry, Jhansi during 11-13 February 2010.

● An invited lecture on Multivariate techniques: Anoverview to the participants of the trainingprogramme on Climate Change, EnvironmentalSustainability and Agricultural Developmentorganized under the aegis of Centre of AdvancedFaculty Training at Division of AgriculturalEconomics, IARI, New Delhi during 09-29 March2010.

● 15 lectures on Introduction to statistical concepts,Tests of significance based on t, χ2 and F-tests,GenStat: An overview, Analysis of variance,Correlation and regression, Fundamentals ofdesign of experiments, Completely randomizeddesigns, Randomized complete block designs andLatin square designs, Designs for factorialexperiments, Split and strip plot designs, Responsesurface designs and Designs for Eeperiments withmixtures, Design resources server, Analysis ofcovariance, Diagnostics and remedial measuresin designed experiments, Multivariate tecnhiques:An overview to the participants of the trainingprogramme on Experimental Designs and DataAnalysis organized for the CAC Staff at ICARDA,Tashkent during 01-05 June 2009.

● 34 lectures on Introduction to statistical concepts,Tests of significance based on t, χ2 and F-tests,GenStat: An overview, Analysis of variance,Correlation, Regression, Fundamentals of designsof experiments, Completely randomized designsand Randomized complete block designs, Row-column designs, Designs for factorial experiments,Split plot designs, Strip plot designs, Resolvableblock designs, Augmented designs, Designs forexperiments with mixtures, Design resourcesserver, Analysis of covariance, Diagnostics andremedial measures in designed experiments, Non-parametric tests, Analysis of muti-environment trialsdata, GGE biplot presentation, Multivariate analysisof variance, Principal component analysis, Clusteranalysis, etc. to the participants of an Internationaltraining programme on Advances in Design andAnalysis of Experiments held at ICARDA, AleppoSyria during 08-19 November 2009.

96


Dr. UC Sud

● Two lectures on Properties of estimator andestimation of non responses in training programmeson Sample Surveys and Organization of LargeScale Sample Surveys held at National Academyof Statistical Administration (NASA) organized byNASA, CSO, Ministry of Statistics and ProgrammeImplementation, Greater Noida during 07-18December 2009 and 08-19 March 2010.

Dr. KK Tyagi● A lecture on Different aspect of sampling to the

participants of a Methodological TrainingProgramme on Impact Assessment of ImprovedAgricultural Technologies organized at NCAP, NewDelhi during 26-28 August 2009.

Sh. OP Khanduri● A lecture on Agricultural Field Experiments

Information System to the participants of theTraining Programme on Farming Systems held atDivision of Agronomy, IARI, New Delhi.

Dr. Anil Rai● A lectures in a Refresher Training Course on SPSS

for Senior ISS officers from 22-26 March 2010held at Ministry of Statistics and ProgrammeImplementation, New Delhi.

Dr. Seema Jaggi● A lecture on Application of Excel and SPSS package

for data analysis to the participants of the SummerSchool on Tools and Techniques for Planning,Monitoring, Evaluation and Impact Assessment ofExtension Programmes held at Division ofAgricultural Extension, IARI, New Delhi during21 July-10 August 2009.

● A lecture on Design of experiments for life sciencesand Illustration of analysis through SPSS to theparticipants of Training Programme on BiostatisticalMethods for Life Sciences under ContinuingEducation Programme held at Defence Institute ofPhysiology and Allied Sciences (DIPAS), DefenceResearch and Development Organization (DRDO),Delhi during 14-18 September 2009.

● Two lectures on Statistical methods for microbiologyand SPSS for analysis of experimental data to theparticipants of the Winter School organized byDivision of Microbiology, IARI, New Delhi during17 November 07-December 2009.

● Three lectures on Testing of hypothesis, SPSS: Anoverview and Statistical designs for fieldexperiments to the participants of the TrainingProgramme on Methodological Advances inExtension Research held at Division of AgriculturalExtension, IARI, New Delhi during 05-25 February2010.

● Two lectures on Experimental designs forpsychological research and Testing of hypothesisto the participants of the Training Programme onApplication of Statistics in Research undercontinuing Education Programme held at DefenceInstitute of Psychological Research (DIPR),Defence Research and Development Organization(DRDO), Delhi during 15-19 February 2010.

● Two lectures on SPSS for regression analysis tothe participants of Refresher Training Programmeon SPSS for ISS officers and senior officers of thestates/UTs organized by Ministry of Statistics andProgramme Implementation, Government of Indiaduring 22-26 March 2010.

Dr. Ashok Kumar

● Two lectures on Economic surplus model and Yieldgap analysis to the participants of the trainingprogramme on Methodological Advances inExtension Research held at the Division ofAgricultural Extension, IARI, New Delhi during05-25 February 2010.

● One lecture on Consumer, producer and economicsurplus models and its application in agriculture tothe participants of a Training Programme on ClimateChange, Environmental Sustainability andAgricultural Development organised at IARI, NewDelhi during 09-29 March 2010.

Dr. AR Rao

● A lecture on Multivariate analysis for life sciencesto the participants of training programme onBiostatistical Methods for Life Sciences underContinuing Education Programme held at DefenceInstitute of Physiology and Allied Sciences (DIPAS),Defence Research and Development Organization(DRDO), Delhi during 14-18 September, 2009.

● A lecture on Test plot design and statistical analysisfor vegetable research trial to the participants of thetraining programme in the area of Vegetable VarietyDevelopment and Evaluation for the officials ofMinistry of Agriculture, Iraq sponsored by Food &

97


Agriculture Organization of United Nations held atDivision of Vegetable Science, IARI, New Delhiduring September 15 - October 14, 2009.

● A lecture on Overview of Bioinformatics andPotential application of data mining in Bioinformaticsin a winter school on Decision making in agricultureusing data mining during 27 October–16 November2009 at NCAP, New Delhi.

● A lecture on Statistical approaches in molecular cropbreeding to the participants of Winter School onMolecular marker-assisted crop breeding: principles,methods and applications held at Genetics division,IARI, New Delhi on 18 January 2010.

● A lecture on Statistical genomics in cropimprovement to the participants of the trainingprogramme Molecular marker assisted breeding forcrop improvement held at Division of Genetics, IARIon 23 February, 2010.

● A lecture on Principal components and factoranalysis to the participants of the trainingprogramme on Application of Statistics in Researchunder continuing Education Programme held atDefence Institute of Psychological Research(DIPR), Defence Research and DevelopmentOrganization (DRDO), Delhi during 15-19 February,2010.

● A lecture on Multivariate Analysis for ExtensionResearch to the participants of the trainingprogramme on Methodological Advances inExtension Research held under the aegis of Centreof Advanced Faculty Training at Division ofAgricultural Extension, IARI, New Delhi during05-25 February, 2010.

● A lecture on Multivariate and factor analysis to theparticipants of refresher training programme onSPSS for ISS officers and senior officers of thestates/UTs organized by Ministry of Statistics andProgramme Implementation, Government of Indiaduring 22-26 March, 2010.

Dr. Prachi Misra Sahoo● A lecture on Remote sensing for crop acreage and

production estimation in hilly region in a WinterSchool on Remote Sensing with Special Emphasison Hyperspectral Remote Sensing held at IARI,New Delhi during 30 March-23 April 2009.

● Two lectures on Least square analysis and Timeseries analysis for Post Graduate Course in Remote

Sensing and GIS in the Centre for Space Scienceand Technology Education in Asia and the Pacific(CSSTEAP) affiliated to United Nations held atIndian Institute of Remote Sensing (IIRS),Dehradun.

Dr. Cini Varghese

● A lecture on Cross over designs and Designs forbioequivalence trials to the participants of TrainingProgramme on Biostatistical Methods for LifeSciences under Continuing Education Programmeheld at Defence Institute of Physiology and AlliedSciences (DIPAS), Defence Research andDevelopment Organization (DRDO), Delhi during14 -18 September 2009.

● A lectures on Application of MS-Excel for dataanalysis to the participants of the Summer Schoolon Tools and Techniques for Planning, Monitoring,Evaluation and Impact Assessment of ExtensionProgrammes held at Division of AgriculturalExtension, IARI, New Delhi during 21 July -10August 2009.

● A lecture on Test plot designs and statistical analysisof data under vegetable trials for InternationalTrainings of Food and Agricultural Organization atHorticulture Division, IARI, New Delhi on 25September 2009.

● Two lectures on Application of MS excel for dataanalysis to the participants of the TrainingProgramme on Methodological Advances inExtension Research held at Division of AgriculturalExtension, IARI, New Delhi during 5-25 February2010.

● Three lectures on Probabilty distributions, Changeover designs and designs for bioequivalence trialsand Data analysis using SPSS to the participantsof the Training Programme on Application ofStatistics in Research under continuing EducationProgramme held at Defence Institute ofPsychological Research (DIPR), Defence Researchand Development Organization (DRDO), Delhiduring 15-19 February 2010.

Dr. Sudeep

● A lecture on MySql server in the Workshop-cum-Training Programe organized under AgroWebproject at DIPA, New Delhi on 11 March 2010.

98


Mohd. Samir Farooqi

● A lecture on Statistical procedures in IPM underPG-Course Principles and Practices of IPM PATH-123 held at NCIPM on 15 October 2009 .

● A lecture on An overview of SPSS in the CASTraining on Climate Change EnvironmentalSustainability and Agricultural Development held atEconomics Division of IARI on 16 March 2010.

Dr. Tauqueer Ahmad● Two lectures on Designing of questionnaires/

schedules and Planning and execution of samplesurveys for four faculty members of VietnamUniversity of Foreign Trade as part of the trainingprogramme organized by IIFT held at Indian Instituteof Foreign Trade (IIFT), New Delhi on 09 May 2009.

● Two lectures on Variance estimation-I and Varianceestimation-II in Training Programmes on SampleSurveys and Organization of Large Scale SampleSurveys held at National Academy of StatisticalAdministration (NASA) organized by NASA, CSO,Ministry of Statistics and ProgrammeImplementation, Greater Noida during 07-18December 2009 and 08-19 March 2010.

Sh. N Sivaramne

● A lecture on Econometric techniques held atNational Power Training Institute, Faridabad on9 February 2010.

● Two lectures on Project analysis techniques andProbit and Tobit regression models held at Divisionof Agricultural Extension, IARI during 18-22February 2010.

Sh. Amrender Kumar

● A lecture on Classificatory techniques including LDAand Bayesian approach in a Winter School onDecision Making in Agriculture using Data Miningheld at NCAP, New Delhi during 27 October–16November 2009 .

Dr. Ramasubramanian V

● A lecture on Price forecasting: Statistical methodswith emphasis on time-series modeling held atNational Institute of Agricultural Marketing, Jaipuron 25 September 2009.

Sh. KK Chaturvedi● A lecture on Development of Decision Support

System using .Net framework in a Workshop-cum-

Training on Risk Assessment in Agriculture held atTNAU, Coimbatore during 26-30 March 2010.

VISIT ABROAD

Dr. VK Bhatia

● Visited as a participating member and as memberof Indian Delegate of Technical Committee onApplication of Statistical Methods (ISO/TC69Technical Committee meeting) convened byDepartment of Standards, Ministry of Science,Technology and Innovations, Government ofMalaysia at Kuala Lumpur, Malaysia during 13-19June 2009.

● Visited Tunisia, Africa to participate in theConference on Implementing the Strategy forImproving Agricultural Statistics in Africa during 01-05 February 2010.

Dr. AK Vasisht

● Visited University of Arizona, Tucson, USA on aStudy Visit on Futures Trading in AgriculturalCommodities during 25 March- 24 May 2009.

Dr. Rajender Parsad

● Invited as Consultant with the Computer andBiometrics Services Unit, ICARDA, Syria- To conduct a training programme on

Experimental Designs and Data Analysis forCAC Staff at Tashkent during 01–05 June 2009.

- To conduct a two week training programme onAdvances in Design and Analysis ofExperiments for the participants from NationalAgricultural Research Systems of Iraq, Iran,Azerbaijan, Sudan, Jordan, Uzbekistasn, Lybiaand Syria during 08–19 November 2009.

Dr. Hukum Chandra

● Deputed to attend SAE 2009 - Small AreaEstimation, 2009 Conference held at Elche, Spainduring 29 June - 01 July 2009.

● Deputed to attend ISI 2009 - 57th Session of theInternational Statistical Institute Conference held atDurban, South Africa during 16 – 22 August 2009.

Radio Talk/TV Interview

● MkW- jatuk vxzoky us 02-04-2009 dks vkdk'kok.kh ds jk"Vªh;pSuy ij izkphu Hkkjrh; xf.krK vk;ZHkê ij jsfM;ks okrkZizlkfjr dh A

Workshops organised as part of Golden Jubileecelebrations of the Institute● A workshop was organised on Design of

Experiments on 29 April 2009. Dr. Rajender Parsadwas the Convener and Dr. Krishan Lal was theCo-convener of the workshop. The workshop wasinaugurated by Dr. AK Singh, DDG (NRM) andDr. MM Pandey, DDG (Engg.), Indian Council ofAgricultural Research (ICAR) was the Guest ofHonour for the Inaugural session. Dr. A. Subba Rao,Director, IISS Bhopal; Dr. AK Dixit, Head, Divisionof Agricultural Chemicals, IARI, New Delhi;Dr. Madhuban Gopal, National Fellow, Division ofAgricultural Chemicals, IARI, participated in theworkshop along with other eminent statisticians andexperimenters from ICAR Institutes and SAUs.Dr. HS Gaur, Dean and Joint Director, Education,IARI, New Delhi Chaired the Valedictory sessionand delivered the Valedictory Address. Followingrecommendations were emerged:

1. The utility of efficient and appropriate designsfor the objectives of the study should bedisseminated in a language that can be easilyunderstood by the experimenters so that theycan take advantage of the research in designof experiments, which in turn would help themin better understanding and then adoption. Thiswould help them make agricultural researchglobally competitive.

2. Travel workshops should be organized as anoutreach activity of the Institute, at different ICARInstitutes and SAUs for a better dissemination ofresearch in Design of Experiments.

3. The participants appreciated the efforts put indeveloping the Web Resources for E-leaning andE-dissemination and advisory, particularly theDesign Resources Server and suggested that therigorous efforts should be put in to make DesignResources Server to reach to every scientist inNARS, particularly through mobile workshops.

Workshops, Conferences, Meetings, Seminarsand Annual Day Organized

100

Workshops, Conferences, Meetings, Seminars and Annual Day Organized

4. Brainstorming sessions and one-two daysworkshops should be organized on thematicareas cutting across the various Subject MatterDivision (SMDs) of ICAR so as to improve thequality of agricultural research.

5. The participants appreciated the efforts madein developing several information systems. Itwas suggested that with the help of variousDDGs of different SMDs of ICAR, efforts shouldbe made for continuously updating the systemsonline so as to harness the benefits of theseefforts. It was also suggested that weather dataand soil data may be superimposed on theseinformation systems and develop specificrecommendations as per the specifications. Therecommendations should not be broad basedand should be realistic.

6. The innovative research findings should beproperly publicized by reporting in ICARNewsletter and ICAR Reporter, etc.

1. The small area estimates are being appliedwithout understanding the estimates or theirlimitations, so it is always advisable to take careof this point before using the estimates. Thereshould be debate between statisticiansproducing the estimates and people generatingthe auxiliary data.

2. For the benefit of SAE practitioners the materialof this workshop should be uploaded on IASRIwebsite.

3. IASRI is a leading Institute in the country forconducting research in the area of SAE. IASRIshould make efforts so that the SAE techniquesare applied by the implementing agencies morefrequently.

4. Institute should conduct such trainings/workshops for some discipline specific groupmore frequently.

5. Research efforts are needed to generateestimates at small area level for derivedparameters.

6. There is a need to make a bridge between,IASRI, National Sample Survey Organization(NSSO), Central Statistical Organization (CSO)and Registrar General of India (RGI) etc. sothat researched data producer and data userscan come together.

● A Workshop was organised on Applications of smallarea estimation techniques on 18 May 2009.Dr. UC Sud was the Convener and Dr. HukumChandra was the Co-Convener of the workshop.Dr. Padam Singh, Former Member NationalStatistical Commission, Government of India wasthe Chairman of the inaugural session. Dr. PranobSen, Secretary, (Ministry of Statistics andProgramme Implementation) and Chief Statisticianof India was the Chief Guest and Dr. MM Pandey,DDG Engineering, ICAR was the Guest of Honourfor the workshop. The following recommendationsemerged on the basis of deliberations in theworkshop:

● A Workshop on Expert systems in agriculture wasorganized on 12 June 2009. Agricultural scientistsin NARS who are the domain experts and thecomputer scientists involved in developing expertsystems attended the workshop. Dr. Sudeep wasthe Convener for the workshop. Dr. Kiran D. Kokate,

Inaugural function of Workshop on ‘Design of Experiments’

Inaugural function of Workshop on‘Application of Small Area Estimation Techniques’

101


DDG (Extension), ICAR inaugurated the workshop.He emphasized on the use of knowledge drivensystems in general and expert systems in particularfor knowledge dissemination to the farmers. Hecited many examples wherein expert systems areused by farmers for solving their problems. Dr. PKMalhotra presented the attempts made by IASRIin this area. Dr. Sudeep presented the majorobjectives of the workshop and demonstrated theJava based Expert Systems at IASRI. The teamfrom IIT, Kanpur demonstrated the Agropedia portaldeveloped under the NAIP project and discussedits various functionalities. Mr. KK Chaturvedidiscussed the functionalities of Expert System onWheat Crop Management. Dr. Rajni Jain and Mrs.Alka Arora presented the use of data miningapproach to build rules for solving problems inagriculture. Other participants from DRRHyderabad, CPRI Shimla, VPKAS Almora alsoexplained their work in the area of expert systems.

Following are the recommendations from theworkshop:

● Web based Expert Systems have a potentialto become the effective extension tools forknowledge dissemination from scientists tofarmers.

● In order to increase its usage by farmers thistechnology should be publicized among thefarmers.

● Organizations within ICAR and outside shouldjoin hands to provide farmer centered contentsfor the expert systems.

● IASRI being the central institute can providethe expert system technology to other domain

institutes for developing expert systems in theirrespective domains.

● A Workshop on Remote sensing and GIS fordecision support in agriculture was organised on 18June 2009. Dr. Anil Rai was the Convener of theworkshop. Dr. AK Singh, DDG (NRM), ICARinaugurated the workshop.

● A Workshop on Statistical and computational issuesin Genomics was organized on 22 June 2009.A total of 22 participants cutting across differentdisciplines in Agriculture from ICAR Institutes andSAUs have participated in the workshop. Dr. AR Raowas the Convener of this workshop. Dr. MM Pandey,DDG (Engineering), ICAR inaugurated theworkshop.

Dr. Kiran Kokate receiving the memento from Dr. VK Bhatia at theinaugural function of the Workshop on ‘Expert Systems in Agriculture

Inaugural function of Workshop on‘Remote Sensing and GIS for Decision Support in Agriculture’

Inaugural function of Workshop on‘Statistical and Computational Issues in Genomics’

Workshops organised under Research Projects● A training cum workshop for the project

“Strengthening, Refining and Implementation of

102


Expert System on Wheat Crop Management” wasorganized in collaboration with Directorate of WheatResearch(DWR), Karnal; Indian AgriculturalResearch Institute (IARI), New Delhi and NationalCenter for Integrated Pest Management, New Delhiat DWR, Karnal during 12-13 May 2009. Altogether80 people including extension specialists, farmers,extension workers, officials from Department ofAgriculture and KVKs, Scientists from DWR, NDRIand specialists from CCSHAU participated in theworkshop. The workshop details were highlightedin six Hindi Newspapers.

● Brainstorming session on Future TechnologicalNeeds in Genetics and Plant Breeding forSustainable Agriculture was organised on 15 May2009 under V-Page project at Division of Geneticsand Plant Breeding, IARI, New Delhi. Dr.Ramasubramanian V acted as as Coordinator forthe workshop.

● A workshop on Remote sensing and GIS foraccelerated growth of agricultural research anddevelopment was organised on 29 July 2009 atIndian Institute of Remote sensing Deheradun underV-PAGe project. Dr. Anil Rai acted as as Coordinatorfor the workshop.

● Personnel Management Information SystemNetwork (PERMISnet-II) was implemented for ICAR.Launching workshop of the system was organizedon 22 July 2009 at NASC Complex. Workshop wasattended by 192 personnel, which include personnelfrom Council, nodal officers from ICAR institutes andIASRI personnel. System was released by Sh. AnilKumar Upadhyay, Special Secretary (DARE) &

Travel Workshops organised as Outreach Activityof the Institute

● Three travel workshops on Experimental Designswere organized in collaboration with ANGRAU,Hyderabad for sensitizing the scientists andstudents of ANGRAU on the Advances in Design ofExperiments and Analysis of Experimental Data.Dr. Rajender Parsad from IASRI co-ordinated thesetravel workshops. The first workshop was organizedat ANGRAU, Hyderabad during 16-17 June 2009.This workshop was attended by 93 participants. Thesecond workshop was organized at RARS, Tirupatiduring 05-06 October 2009 and attended by 92participants. The third workshop was organized atRARS, Ankapalle on January 06, 2010. Sixty

Secretary, ICAR. Overview of the system waspresented in the workshop. PERMISnet-II isenhanced version of PERMISnet, and is developedusing .NET framework. System has been designedand developed with different access rights fordifferent types of users, which include managers atCouncil level, nodal officers at institutes, individualpersonnel and general users. System containsinformation on personal and professional parametersof ICAR employees along with details on cadrestrength and institutional parameters.

● A one day workshop on Evaluation ofRationalization of Minor Irrigation Statistics Schemewas Organised at NAAS, NASC Complex, NewDelhi on 17 November 2009. Dr. UC Sud was theConvener of the workshop.

A view of launch of PERMISnet II

A view of Workshop on‘Evaluation of Rationalization of Minor Irrigation Statistics Scheme’

103


The participants also felt that in future programmes,separate homogeneous groups according to thedisciplines should be formed and examples fromdisciplines pertaining to that group should beincluded for a given group. The travel workshopswere widely covered in news papers.

● laLFkku }kjk ¶Hkkjr esa iQly vkdyu losZ{k.k¸ fo"k; ijfnukad 07 uoEcj] 2009 dks ,d&fnolh; dk;Z'kkyk dkvk;kstu fd;k x;kA bl dk;Z'kkyk ds vk;kstu esa Mk- mes'kpUnz lwn us la;kstd rFkk Mk- Ñ".k dkUr R;kxh us lg&la;kstdds :i esa dk;Z fd;kA ;g dk;Z'kkyk nks rduhdh l=kksa esavk;ksftr dh xbZ%

rduhdh l=k&1(i) Hkkjr esa iQly vkdyu losZ{k.k&n`f"Vikr(ii) iQly vkdyu losZ{k.k&vkadM+ksa dh xq.koRrk(iii) iQly mRiknu vkdyu&orZeku ifjn`';

rduhdh l=k&2(i) iQly dVkbZ iz;ksx dh fof/(ii) lqnwj laosnu i¼fr ,oa HkkSxksfyd lwpuk ra=k }kjk iQly

{ks=kiQy dk vkdyu(iii) iQly vkdyu losZ{k.k & mRrj izns'k jkT; ds vuqHko(iv) y?kq {ks=k Lrj ij iQly mit vkdyu

participants from North Coastal Zone, West GodavariZone and High Altitude Zone attended this workshop.During these workshops, views of the participantswere also taken on statistical problems encounteredby them during their experimentation. The majorissues that came up were:

(i) How to compare two watersheds of 100ha eachwith untreated and treated water sheds?

(ii) How to compare 2 treatments like organicfarming and existing farming practices using non-replicated field scale experiments with large plotsize?

(iii) How to design experiments for drip and sprinklerirrigation systems?

(iv) How to handle large variation in both directionsof experimental plots due to soil depth, elevationunder rainfed conditions?

(v) How to analyze the data from on-farm trialsconducted over years?

(v) How to take samples for estimation of yield perhectare from large plots in experiments oncultivator’s fields?

(vi) How to handle large variation in both directionsof experimental plots due to soil depth, elevationunder rainfed conditions? and

(vii) How to handle the variability within plots?

A view of Travel Workshop on ‘Design of Experiments’

Hkkjr esa iQly vkdyu losZ{k.k

dk;Z'kkyk dh eq[; vuq'kalk,¡(1) iQly iSnkokj ds vkdyu ds fy, jkT; ljdkjksa }kjk

vk;ksftr iQly dVkbZ ijh{k.kksa (lh-lh-bZ-) dh la[;kc<+ jgh gS] ftlls vk¡dM+ksa dh xq.koRrk ij foijhr izHkkoiM+ jgk gS A vr% iQly dVkbZ ijh{k.kksa (lh-lh-bZ-) dhla[;k dks de djus ds iz;kl djus pkfg,A blds fy,ftyk Lrj ls de Lrj ij vFkkZr lkeqnkf;d fodkl[kaM@xzke iapk;r Lrj ij y?kq {ks=k vkdyu rduhdksa dkiz;ksx fd;k tkuk pkfg, A

(2) Ñf"k ea=kky; }kjk iQly mRiknu ds fy, viukbZ tkusokyh fof/ ds LFkku ij mfpr lkaf[;dh; rduhdksa dkiz;ksx djds ,d mn~ns';kRed fof/ dk iz;ksx djus dhvko';drk gS A

104


● Symposium on Statistical and InformaticsPerspectives of Climate Change was organisedduring 63rd Annual Conference of ISAS at RajendraAgricultural University, Samastipur, Bihar during 03-05 December 2009 Dr. PK Malhotra was theConvener for the Symposium.

● Symposium on Statistical and ComputationalGenomics was organised on 03 December 2009during 63rd Annual Conference of Indian Society ofAgricultural Statistics held at Department of Statistics,Mathematics and Computer Application, RajendraAgricultural University, Samastipur, Pusa, Bihar.Dr. Rajender Parsad and Dr. BM Prasanna were theConveners for the Symposium.

● During International Conference on Statistics,Probability, Operations Research, ComputerScience and Allied Areas held at Andhra University,Visakhapatnam from 04-08 January 2010, followingsessions of Special Invited Talks were organized.

- Design of Experiments (Conveners:Dr. Rajender Parsad and Dr. Sudhir Gupta)

- Small Area Estimation (Convener:Dr. Hukum Chandra and Co-Convener: Dr. UCSud)

- Recent Advances in Sample Surveys(Convener: Dr. U.C. Sud and Co-Convener:Dr. Hukum Chandra)

- Statistical Modelling (Convener: Dr. Prajneshuand Co-Convener: Dr. Himadri Ghosh)

- Recent Advances in Statistical Genetics(Convener: Dr. VK Bhatia and Co-Convener:Dr. AK Paul)

● A symposium on Statistics for Studying the Impactof Climate Change was organized on 25 February2010 during XII Annual Conference of Society forStatistics, Computer and Applications at Departmentof Statistics, Siksha Bhavana, Visva Bharati during23-25 February 2010. Dr. Rajender Parsad andDr. Kashinath Chatterjee were the Conveners forthe Symposium.

● A workshop on Orthogonal arrays and mixtureexperiments was organized during 15-17 March2010 by Dr. VK Gupta, ICAR National Professorjointly with Dr. Rajender Parsad. The main speakerswere from IASRI, New Delhi and the discussantswere from Indian Statistical Institute, Kolkata; IndianStatistical Institute, Delhi; Kolkata University, KalyaniUniversity and IARI, New Delhi. The basic purpose

(3) iQly dVkbZ losZ{k.k ds lapkyu ds vUrxZr] vukt dsmRiknu ds lkFk&lkFk iQly vo'ks"kksa ds mRiknu dks Hkhekik tkuk pkfg, ,oa

(4) igkM+h@mRrj iwohZ igkM+h jkT;ksa esa] tgk¡ T;knkrj {ks=k nqxZegSa] ogk¡ HkkSxksfyd lwpuk ra=k (th-vkbZ-,l-) midj.kksa dslkFk lwnwj laosnu rduhdksa dk iz;ksx djds iQly {ks=kvkdyu fd;s tkus pkfg,asa A

Other Symposia/Workshops

● A half day session of lectures and visit to libraryand GIS & Remote Sensing Lab was organised on23 April 2009 for 4 faculty members of VietnamUniversity of Foreign Trade as part of the trainingprogramme organized by Indian Institute of ForeignTrade, New Delhi. The lectures were delivered onCrop Acreage and Production Estimation, Overviewof Sampling Techniques and Determination ofSample Size.

● Brainstorming Sessions on Establishment of Centreof Agricultural Bioinformatics were organised:- Under the Chairmanship of Dr. HP Singh,

DDG (Horticulture), Dr. MM Pandey, DDG(Engineering) and Dr. KD Kokate, DDG(Extension), ICAR and other experts in the fieldof biotechnology and bioinformatics alsoparticipated on 26 August 2009 at IASRI, NewDelhi.

- Under the Chairmanship of Dr. Mangala Rai,Secretary, DARE & Director General, ICAR,with other experts in the field of biotechnologyand bioinformatics New Delhi on 22September 2009 at NASC, New Delhi.

Dr. Mangala Rai, Secretary, DARE and Director General, ICARaddressing the participants of Brain Storming Session on

‘Establishment of Centre of Agricultural Bioinformatics’

105


of the workshop was to bring leading statisticiansand stake holders together so as to enable todisseminate the recent research findings onorthogonal arrays and mixture experiments into theresearch in agricultural sciences so as to help toimprove the quality of agricultural research. It alsoaimed to create a school of researchers who canundertake basic research in Design of Experimentsand their applications in agricultural sciences so asto improve the status of experimentation inagricultural research.

The introductory session was chaired by Shri SKDas, Director General, CSO, New Delhi. Dr. VKBhatia, Director, IASRI, Dr. Bikas Sinha, Professor,ISI, Kolkata and Former Member, National StatisticalCommission, Dr. Aloke Dey, INSA Senior Scientist,New Delhi gave their introductory remarks. Dr. VKGupta talked about the purpose and coverage ofthe workshop.

It was unanimously felt by all the participants thatsuch workshops are quite useful and should beorganized regularly. These workshops are helpfulin developing the subject and the capabilities ofthe scientists. The main advantages of suchdisseminations are that there is a judicious mix oftheory and application, particularly applications inagriculture. It was also felt that the scope of theworkshop may be enlarged by including morestatisticians active in the topic of research.

● A Hindi workshop on ‘Karyalaya ke karya mainsanganak ka prayog’ was also organized on 29March 2010 for Technical/Administrative staff of theInstitute.

SeminarsSalient outcomes from the completed research projectsundertaken in different aspects of Agricultural Statisticsand Computer Application were presented in theseminars organized regularly at the Institute. Openseminars were also organized for new research projectsproposals. Outline of Research Work (ORW) seminars,Course seminars and Thesis seminars were deliveredby the students of M.Sc. and Ph.D., AgriculturalStatistics and M.Sc., Computer Application.

During the period under report, a total of 94 seminartalks were delivered. Out of these, 67 were studentseminars, 18 by scientists of the Institute and 09 byguest speakers as follows:

Guest Seminars as a part of the celebrations forthe Golden Jubilee Year of the Institute● Dr. VK Sharma, Emeritus Scientist, ICAR.

Prediction in seemingly unrelated regressionmodels on 27 May 2009.

● Dr. Murari Singh, Professor Department ofMathematics and Statistics Concordia University,Canada. Spatial-Temporal error structured forlentil yield in suplimental irrigation trials on 16 June2009.

● Dr. KC Raut, Former Scientist, IASRI, New Delhi.My experiences in IASRI on 30 June 2009.

Other Guest Seminars● Dr. RC Agarwal, Principal Scientist NBPGR. Indian

IT act 2000 and cyber security on 20 May 2009.● Dr. PK Gupta, Emeritus Professor, Ch. Charan,

Singh University, Meerut. Advances in quantitativegenetics on 23 November 2009.

A view of Workshop on‘Orthogonal Arrays and Mixture Experiments’

Dr. Murari Singh receiving the Memento fromDr. Prajneshu at the Golden Jubilee Seminar

106


● Prof. Prem Narain, Former Director, IASRI.Quantitative genetics in modern era on 30November 2009.

● Dr. Ramanna V. Davuluri, Director, ComutationalBiology, The Vista Cancer Centre,The VistaInstitute, (USA). Bio-informatics & computationalbiology in post genomics era on 18 January 2010.

● Dr. Sat Gupta, Professor of Statistics, NorthCarolina,(USA). Usefulness of two steps optimalrandomised response model on 20 January2010.

● Dr. Bikas Sinha, Former Member, NationalStatistical Commission. Data integration techniqueson 17 March 2010.

ANNUAL DAY CELEBRATIONSThe Annual Day of the Institute was celebrated on 02July 2009 in which Dr. Madan Mohan Pandey, DDG(Engg.), ICAR was the Chief Guest. Dr. Anil KumarSingh, DDG (NRM), ICAR delivered the NehruMemorial Lecture entitled Bridging the Statistical Divide.

Dr. VK Bhatia, Director addressing the participants of 63rd Courseof ISEC during their Study Visit to the Institute

Nehru Memorial Gold Medal for the year 2005-08was awarded to Sh. Sanjay Kumar Prasad, M.Sc.(Agricultural Statistics) student.

A view of tree plantation by Dr. AK Singh DDG (NRM), ICAR atAnnual Day Function

Annual Report of the Institute and PAYBITAXPackage Ver 1.0 were released on the Annual Day.As a part of Golden Jubilee Celebrations of theInstitute a publication entitled IASRI... an Era ofExcellence consisting of messages from leaders inAgricultural Science, Statistical Science and otherwell wishers along with 17 articles on various topicswas also released by the Chief Guest.

Chief Guest awarding Nehru Memorial Gold Medal to the beststudent of M.Sc. (Agricultural Statistics)

Study Visit

● One day Study Visit was organized on 13 October2009 at Institute on Functions and Activities ofInstitute for the participants of 63rd regular course ofInternational Statistical Education Centre (ISEC),Kolkata on Official Statistics and RelatedMethodology conducted by National Academy ofStatistical Administration (NASA) from 05 Octoberto 13 November 2009.

The participants were from seven countries.Dr. Seema Jaggi was facilitator for this visit.

INDIANDr. Mangala RaiSecretary, DARE & Director General, ICARNew Delhi

Dr. SP TiwariDDG (Education), ICAR, New Delhi

Dr. HP SinghDDG (Horticulture), ICAR, New Delhi

Dr. AK SinghDDG (NRM), ICAR, New Delhi

Dr. MM PandeyDDG (Engineering), ICAR, New Delhi

Dr. KD KokateDDG (Extension), ICAR, New Delhi

Dr. Arvind KumarDDG (Education), ICAR, New Delhi

Dr. Pronab SenChief Statistician and SecretaryMinistry of Statistics andProgramme ImplementationGovernment of India

Dr. PV ShenoiFormer Special Secretary (DAC)Shantiprem, 20-C, First Main RoadRaj Mahal Villa ExtensionStage-II, Block-I, Bangalore

Dr. Bikas Kumar SinhaFormer Member, National Statistical Commission andProfessor, Indian Statistical Institute, Kolkata

Dr. AP GoreMember, National Statistical Commission, Bakul40 Empress Garden View Society Sopan Baug, Pune

Dr. Padam SinghFormer Additional Director GeneralICMR, New Delhi

Sh. SK DasDirector General,Central Statistical Organisation, New Delhi

Dr. SS AcharyaFormer Chairman, CACP, Govt. of India33, Shahi Complex,Sector - 11, Udaipur, Rajasthan

Distinguished Visitors

108

Distinguished Visitors

Dr. AK NigamExecutive PresidentIASDS, A-2/605, Shobha Aqua MarineBellander, Outer Ring Road, Bangalore

Dr. Aloke DeyINSA, Senior ScientistIndian Statistical Institute, New Delhi

Dr. PK GuptaEmeritus ProfessorCh. Charan Singh University, Meerut, UP

Dr. PK AgrawalICAR National ProfessorIARI, New Delhi

Dr. A Subba RaoDirector, IISS, Bhopal

Prof. Prem NarainFormer Director, IASRI, New Delhi

Dr. BBPS GoelFormer Director, IASRI, New Delhi

Dr. SD SharmaADG (HRD-I), Education Division, ICAR, New Delhi

Dr. AK SrivastavaFormer Joint Director, IASRI, New Delhi

Dr. SK TandonADG (Engineering), ICAR, New Delhi

Dr. HS GaurDean and Joint Director (Education), IARI, New Delhi

Sh. AK SrivastavaDDG (FOD), NSSO, Faridabad

Dr. BB SinghDDG (FOD), Allahabad

Sh. VK SinghDirector, Department of Agriculture, UP

Sh. Rajiv LochanAdvisor, Directorate of Economics & StatisticsMinistry of AgricultureKrishi Bhawan, New Delhi

Dr. S.M. JharwalPrincipal Advisor, DAC, Ministry of AgricultureKrishi Bhawan, New Delhi

Dr. Vidya DharDDG & Agriculture Census CommissionerGovernment of India, New Delhi

Prof. MC AgrawalProfessor(Statistics),Department of StatisticsUniversity of Delhi, New Delhi

Sh RC RayEconomic and Statistical AdvisorDirectorate of Economics and StatisticsMinistry of Agriculture, Krishi Bhawan, New Delhi

Sh. AK MathurAdviser (Statistics),Department of Animal HusbandryDairying and Fisheries, Ministry of AgricultureKrishi Bhawan, New Delhi

Dr. TBS RajputProject Director, Water Technology CentreIARI, New Delhi

Dr. GM BhoopathyDDG, Central Statistical Organisation, New Delhi

Dr. Ramesh ChandDirector, NCAP, New Delhi

FOREIGN

Prof. JN SrivastavaCNS Research, Professor (Emeritus)Colorado State University, USA

Dr. Sat GuptaProfessor of Statistics, North Carolina, USA

Dr. Murari SinghProfessorDepartment of Mathematics and StatisticsConcordia University, Canada

Dr. Ramanna V DavuluriDirector, Comutational BiologyThe Vista Cancer CentreThe Vista Institute, USA

Dr. A David MarshallDeputy Director, Statistics Division, FAO, Rome

Dr. Naman KeitaSenior Statistician, Statistics DivisionFAO, Rome

Prof. Rohan RajapakseExecutive DierctorSri Lanka Council for Agricultural Research PolicySri Lanka

Mr. Ranjith WijethilakeSecretary,Ministry of Agriculture Development andAgrarian Service, Sri Lanka

Dr. KNG PushpkumaraScientist,Sri Lanka Council for Agricultural Research PolicySri Lanka

Indian Agricultural Statistics Research Institute (IASRI)consists of Scientific, Technical and Administrativepersonnel headed by the Director. The Heads of differentDivisions/ In-Charge of Cells and other officers at managerialpositions during 01 April 2009 to 31 March 2010 are:

DirectorDr. VK Bhatia

ICAR National ProfessorDr. VK Gupta

Head, Division of BiometricsDr. Prajneshu

Head, Division of Forecasting TechniquesDr. (Mrs.) Ranjana Agrawal

Head, Division of Computer ApplicationsDr. PK Malhotra

Head, Division of Design of ExperimentsDr. PK Batra (upto 28 April 2009) (Actg.)Dr. Rajender Parsad (w.e.f. 29 April 2009 AN)

Head, Division of Sample SurveyDr. UC Sud

Head, Division of EconometricsDr. AK Vasisht (upto 02 March 2010 FN)Dr. SP Bharadwaj (w.e.f. 02 March 2010 AN) (Actg.)

Professor (Agricultural Statistics)Dr. VK Bhatia

Professor (Computer Application)Dr. PK Malhotra

In-charge, Research Coordination andManagement Unit and Member Secretary, IRCDr. VK Mahajan (upto 06 June 2009)Dr. Rajender Parsad (w.e.f. 11 June 2009)

IASRI Personnel

110

IASRI Personnel

Warden, Sukhatme HostelDr. Krishan Lal (upto 01 September 2009)Dr. (Mrs.) Ranjana Agrawal (w.e.f. 02 September 2009)

Vigilance OfficerDr. PK Malhotra

Welfare OfficerDr. PK Batra

In-charge, National Agricultural Science MuseumShri RP Jain (upto 27 March 2010)Dr. (Mrs.) Sushila Kaul (w.e.f. 28 March 2010)

LibrarianDr. (Mrs.) P Visakhi

Officer on Special DutySh. AK Chaturvedi (upto 31 December 2009)

Chief Administrative Officer and Head of OfficeCapt. Mehar Singh

Finance and Accounts OfficerSh. Krishan Kumar

Liaison OfficerDr. Jagbir Singh

Public Information OfficerSh. AK Chaturvedi (upto 31 December 2009)Sh. Nika Ram (w.e.f. 01 January 2010)

National Agricultural Science Museum

The National Agricultural Science Museum (NASM),situated at NASC Complex, Dev Prakash Shastri Marg,Opposite Dasghara Village, Pusa Campus, New Delhicame into existence during 2004 and was inauguratedby H.E. Hon’ble President of India, Dr. A.P.J. AbdulKalam on 03 November, 2004.

The NASM is looked after by a Central ManagementCommittee constituted at the ICAR Headquarter leveland is comprised of:

Dr. MM Pandey Deputy Director General Chairman(Engg.)

Dr. P Chandra Assistant Director General Member(PE)

Sh. VP Kothiyal Director (Works) Member

Sh. Rabindra Patra Director (Finance) Member

Sh. PK Jain Under Secretary (GAC) Member

Dr. VK Bhatia Director, IASRI MemberSecretary

Any Other Relevant Information

A Sub-Management Committee under theChairmanship of Director, IASRI has also beenconstituted and is comprised of:

Dr. VK Bhatia Director Chairman

Dr. PK Malhotra Head (CA) Member

Dr.(Mrs.) Ranjana Agrawal Head (FT) Member

Dr. RC Goyal Pr. Scientist & MemberNodal Officer (Till 28.02.2010)

Sh. RP Jain Scientist & Member SecretaryIn-charge (Till 29.03.2010)

Dr. Sushila Kaul Scientist & Member SecretaryIn-charge (From 30.03.2010)

Capt. Mehar Singh CAO Member

Sh. Krishan Kumar F&AO Member

Under the guidance of this Committee, the day-to-dayactivities of the Museum, relating to up-keepand maintenance, are looked after by the ScientistIncharge, technical and administrative staff of IASRI,New Delhi.


112

Interesting information on agriculture-for farmers,agriculture students, college and school children as wellas general public is available. The exhibits in themuseum are a combination of electronics, computerhardware/software, mechanical devices, art andscience objects. Special feature of this Museum is toprovide complete knowledge on the agriculturalsubjects through audio, video, slides and computermedium using touch screen facility.

The Museum is open to visitors on all days from 10.30a.m. to 4.30 p.m. except Monday - the weekly holiday.It is NOT closed even for lunch break. This grandMuseum is fully air-conditioned. There is a nominalentry fee of Rs. 5 per head but the groups of studentsnominated by schools, colleges and farmers areexempted from entrance fee.

During the period under report many prominent personsvisited the Museum which included Hon’ble PrimeMinisters/Ministers of various countries, Head ofAgricultural/Research Departments, etc. Besides this,farmers belonging to different parts of India also visitedMuseum and gained vital knowledge from the exhibitsdisplayed in the Museum. In all 19,485 visitors visitedthe Museum and 3,914 tickets were sold. Thefunctioning of the Museum was appreciated by all thevisitors, especially by high dignitaries and foreigners.A team of Lok Sabha TV channel visited Museum forthe entire coverage of the Museum and Incharge,Museum was interviewed by the team and the samewas telecasted on its channel programme “SurkhiyonSe Pare” on 01 December 2009. Some of thedistinguished visitors are:

Australia Robert Bertrand Schwartz, Senior Manager,Plant Biosecurity

Colin Grant, Executive Manager Plant Division,Department of Agriculture, Fisheries and Forestry

Bangladesh MD Delowar Hossain, Chief Scientific Officer,Plant Pathology Division, BangladeshAgricultural Research Institute

Md. Hasanul Haque, Project Director, AgriculturalExtension Component (AEC), Department ofAgriculture Extension

Cambodia Hean Vanhan, Deputy Director General,General Directorate of Agriculture(GDA), Ministryof Agriculture, Forest and Fisheries (MAFF)

Nigin Chhay, Cambodia National IPMCoordinator & Chair, APPPC-IPM Committee,Phnom Penh, Department of Rice Crop (MAFF)

China Xia Jingyuan, Director General, National Agro-Technical Extension and Service Centre, Ministryof Agriculture

Fuxiang Wang, Director, Plant QuarantineDivision, National Agro-Technical Extension andService Centre, Ministry of Agriculture

Yang Puyun, Deputy Director, Pest ControlDivision, National Agro-Technical Extension andService Centre, Ministry of Agriculture

He Pengfei, Programme Official, GeneralAdministration of Quality Supervision, Inspectionand Quarantine (AQSIQ)

Lau Siu Ki Clive, Senior Agricultural Officer(Regulatory), Agriculture, Fisheries andConservation Department, Hong Kong, SpecialAdministrative Region

Huang Chao Yin, Forestry Bureau, Council ofAgriculture

Ethopia Tigistu Gebremeskel Abza, Ministry of Agriculture& Rural Development

FAO (Thailand) Johannes W Ketelaar, Chief Technical Adviser,FAO Inter-Country Programme for IPM andPesticide Risk Reduction in South and SouthEast Asia

Piao Yongfan, Senior Plant Protection Officer andSecretary of APPPC, FAO Regional Office forAsia and the Pacific Maliwan Mansion, Thailand

Nongyao Ruenglertpanya, Secretary, FAORegional Office for Asia and Pacific MaliwanMansion, Thailand

Prapin Lalitpat, Consultant, FAO Regional Officefor Asia and Pacific Maliwan Mansion

FAO/ROME Peter E Kenmore, Secretary IPPC and DeputyDirector, Plant Production and ProtectionDivision, Agriculture and Consumer ProtectionDepartment

Jean-Pierre Chiaradia-Bousquet, Senior LegalOfficer, LEGA

Georgia A team of Scientists (10-15 members) from theUniversity of Georgia

India Farookh Abdullah, Hon’ble Minister of New andRenewable Energy, Government of India

Indoensia Hari Priyono, Director General, IndonesianAgricultural Quarantine Agency, Ministry ofAgriculture

Suwanda, Director of Centre for PlantQuarantine, Indonesian Agency for AgriculturalQuarantine, Ministry of Agriculture

Soekirno, Director of Horticulture CropProtection, Ministry of Agriculture

Herdradjat N, Director of Estate CropsProtection, Ministry of Agriculture

Heru Wahyupraja, Head for Quarantine of ImportPlant, Centre for Plant Quarantine, Agency forAgricultural Quarantine, Ministry of Agriculture


113

Antarjo Dikin, Head of Division for Cooperationand Public Relation, Indonesian AgriculturalQuarantine Agency

Lao, PDR Siriphonh Phithaksoun, Deputy Directorof Plant Quarantine Division, Departmentof Agriculture, Ministry of Agriculture andForestry

Malaysia Suranthran Perissamy, Department of CropScience

Wan Normah Wan Ismail, Director, CropProtection & Plant Quarantine Division,Department of Agriculture

Yip Kin San, Principal Assistant Director,Enforcement and Plant Protection Section,Department of Agriculture

Fatimah Binti Md. Anwar, Principal AssistantDirector, Pesticieds Control Division

Michael Ranges Nyangob, Assistant Director ofAgriculture, Plant Quarantine Division

Ho Haw Leng, Principal Assistant Director, Importand Export Control Section, Crop Protection &Plant Quarantine Division

Chang Yeng Wai, Deputy Director, Legislation &International Affairs, MAQIS

Halimi Mahmud, Pesticied Control Division,Department of Agriculture, Ministry of Agricultureand Agro-Based Industry

Myanmar Phyu Phyu Lwin, Manager (SeniorEntomologist), Plant Protection Division,Myanmar Agriculture Service

Nepal Dinesh Pariyal, Principal Scientist

Suresh Kumar Shrestha, Sr. Scientist, NepalAgricultural Research Orgainization

Badri Bishal Karmacharya, Programme Director,Directorate of Plant Protection, Department ofAgriculture, Ministry of Agriculture and Co-operatives

New Zealand Tim Knox, Director Border Standards, MAFBiosecurity New Zealand, Ministry of Agricultureand Forestry

John Hedley, Principal Adviser, InternationalCoordination-Plants, Biosecurity New Zealand,Ministry of Agriculture and Forestry

Nigeria Vaatyough Hyacinth Mamfe, National SpaceResearch and Development Agency, FedralMinistry of Science and Technology

Zubair Ayodeji Opeyemi, National SpaceResearch and Development Agency

Pakistan Tasneem Ahmad, Adviser & Director General,Department of Plant Protection, Ministry of Food& Agriculture, Governement of Pakistan

Azam Khan, Department of Plant Protection,Malir Halt

Papua New Jeffrey Waki, PNG National AgriculturalGuinea Research Institute

Philippines Larry R Lacson, Chief, Plant Quarantine Service,Bureau of Plant Industry

Jesie Binamira, Philippine National IPMProgramme Officer & ASEAN IPM KnowledgeNetwork Director, Department of Agriculture

Republic of In-Tae-BAE, Director General, NationalKorea Plant Quarantine Service, Ministry of Food,

Agriculture, Forestry and Fisheries (MIFAFF)

Young-Tae-KIM, Deputy Director, BilateralNegotiation and Cooperation Division, MIFAFF

Young-Chul JEONG, Deputy Director,International Quarantine Cooperation Division,National Plant Quarantine Service, MIFAFF

Kyu-OCK YIM, Researcher, InternationalQuarantine Cooperation Division, National PlantQuarantine Service, MIFAFF

Sri Lanka Marvya Gunasena, Chairman, Sri Lanka Councilof Agricultural Research and Policy (CARP)

Panduka Weerasinghe, General Manager,CARP

RB Wijekoon, Director, CARP

Nirmala de Zoysa, Assistant Director, CARP,Enirisinghe Srimathie Chandrika Edirisinghe,Plant Genetic Resources Centre

Ranjith Wijethilake, Secretary, Ministry ofAgriculture Development and Agrarian Services

Rohan Rajapaske, Executive Director, CARP

KNG Pushpakumara, CARP and aSr. Scientist

K Piyasena, Deputy Director, Plant ProtectionService, Gannoruwa, Peradeniya

Sudan Saida Babeker Alzain, Range and PastureAdministration

Syria Sabah Abou Kalam, Planning and StatisticsDirectorate, Ministry of Agriculture & AgrarianReformsAla’o Moafak Al Theib, Ministry of Agriculture, AlBadia, Project Damascus

Taiwan Chen Shu, Division of Plant Germplasm, TaiwanAgricultural Research Institute

Tanzania H.E. Mizengo Kayanza Pinda (MP), PrimeMinister of the United Republic of Tanzaniaaccompanied with 30 Member Delegation

Thailand Udorn Unahawutti, Senior Expert on PlantQuarantine, Department of Agriculture

Walaikorn Rattanadechakul, Senior AgriculturalScientist, Plant Protection Research andDevelopment Office, Department of Agriculture

Tasanee Pradyabumrung, Senior StandardsOfficer, Office of Commodity and SystemStandards, National Bureau of AgriculturalCommodity and Food Standards, Ministry ofAgriculture and Cooperatives

Prateep Arayakittipong, Standards Officer, officeof Commodity and System Standards, NationalBureau of Agricultural Commodity and Food


114

IASRI News and Annual Report, etc. It also organizesNational Conferences of Agricultural ResearchStatisticians once in three years and conducts meetingsof Senior Officers (SOM) every month. The Unit alsoassists the Research Advisory Committee (RAC) andQuinquennial Review Team (QRT), ConsultancyProcessing Cell (CPC), Institute TechnologyManagement Committee (ITMC), Institute TechnologyManagement Unit (ITMU) and Planning Monitoring andEvaluation (PME) Cell. The unit is also responsible forcorrespondence with ICAR, ICAR Institutes, SAUs andother organizations in India and abroad. The otherfunctions of the Unit are: to examine the new researchproject proposals before these are considered by theInstitute Research Committee (IRC) in respect ofimportance of problem, its design and finalrequirements; to monitor the progress of on-goingresearch projects and to bring out half yearly monitoringprogress reports; to prepare annual action plan, activitymilestones, SFC memo, monthly targets and progressof the Institute, half yearly scientific targets andachievements, quarterly performance review, tomaintain the Research Project Files (RPF), combinedSFC memo of IASRI and NCAP, monthly progress ofidentified thrust areas and also their submission toICAR. The Unit also provides help in Art, Photographyand Reprographic Services. The unit also brings outquarterly newsletters, Annual Report of the Institute andother research and dissemination bulletins.

Consultancy Processing Cell (CPC)

As per the ICAR Rules and Guidelines for Training,Consultancy, Contract Research and Contract Services1997 a Consultancy Processing Cell (CPC) has beenfunctioning at the Institute since 16 August 1997. ThisCell was reconstituted w.e.f. 17 August 2009 with thefollowing composition:

Dr. Prajneshu, HD (Biometrics) ChairmanDr. PK Malhotra, HD (CA) MemberDr. Rajender Parsad, HD (DE) and MemberIncharge (RCMU)Chief Administrative Officer Memberand Head of OfficeFinance and Accounts Officer Member

Sh. PP Singh, Technical Officer Member Secretary

The functions of the Cell are:− To give broad guidelines for consultancy work− To bring out consultancy information system,

catalogues periodically

Standards, Ministry of Agriculture andCooperatives

Ratchanok Mikaew, Biotechnology Research andDevelopment Office, Department of Agriculture

Uganda Cyprian Ebong, Director, Quality Assurance

James Ogwant, Director, Crops ResourcesResearch Institute

John Ociti, Chief Accountant

George Maiteki, Director, Ngetta ZonalAgricultural Research and Development Centre

Japheth Magyembe, Co-ordinator, CompetitiveGrants Scheme

Regina Musaazi, Monitoring and EvaluationOfficer from National Agricultural ResearchOrganization (NARO)

Vietnam Dam Quoc Tru, Deputy Director General, PlantProtection Department (PPD)

Ngo Tien Dung, Coordinator Vietnam NationalIPM Programme, Plant Protection Department,Ministry of Agriculture and Rural Development

Zambia Stephen Wambulwa Muliokela, ExecutiveDirector, Golden Valley Agricultural ResearchTrust (GART)

Namukolo Mukutu, Chairman, Board of Trusteesof GART

Barry Coxe, Member, Board of Trustees of GART

Douglas Moono, Head, Research &Development, GART,

GS Pandey, Dairy Development Specialist,GART

Research Coordination and Management Unit(RCMU)

RCMU is responsible for documentation anddissemination of scientific output of the Institute through

A visit of an International delegation toNational Agricultural Science Museum


115

− To identify and prepare list of consultants in differentfields; the consultants could be retired Scientist/Officer of proven experience

− To prepare a roster of available human resourceson the basis of time schedule

− To identify team for specific consultancyassignments and periodic reviews of progress

− To prepare consultancy proposals as perprescribed flow chart

Nine consultancy trainings/ Five consultancy servicesreceived by Consultancy Processing Cell were finalizedand got approved.

Planning, Monitoring and Evaluation (PME) Cell

To facilitate all activities related to priority setting,monitoring and evaluation a Planning, Monitoring andEvaluation (PME) Cell is working at the Institute. ThisCell was reconstituted w.e.f. 16 September 2009 withthe following composition :

Dr. PK Malhotra, HD (CA) Nodal OfficerDr. Rajender Parsad, HD (DE) Memberand Incharge (RCMU)Dr. UC Sud, HD (SS) MemberDr. Ashok Kumar, Principal Scientist MemberDr. Dharm Raj Singh, Scientist MemberSh. Samir Farooqi, Scientist MemberSh. PP Singh, Technical Officer (T-7-8) Member Secretary

The terms of reference of the Cell are:− Sensitization of policy makers, managers,

scientists and others about the need for researchpriority assessment

− Prioritization of Institute’s programmes− Tracking of current resource allocations− Interface with ARIS, SREP, ATMA, IVLP, TAR and

KVK for research, extension education and otherservices

− Facilitate monitoring and evaluation of researchprojects of the Institute/SAU

− Participation in monitoring and evaluation (site-level) activities of NATP/NAIP

− Impact analysis, especially that of research andextension activities

Institute Technology Management Committee(ITMC)

As per the ‘ICAR Guidelines for Intellectual PropertyManagement and Technology Transfer/ Commercia-

lization’ a Institute Technology Management Committee(ITMC; short title for Institute Intellectual PropertyManagement and Technology Transfer/Commercia-lization Committee, IIPM&TCC) has been constitutedfor addressing Intellectual Property (IP) related mattersof the Institution as detailed in the ICAR Rules andGuidelines for Training, Consultancy, ContractResearch and Contract Services, 1997. Thecomposition of the ITMC is:

Dr. VK Bhatia Cha i rmanDirector, IASRI

Dr. Amit Kumar Vasisht (upto 02 March 2010 ) MemberHD (Econometrics), IASRI

Dr. Anil Rai MemberPrincipal Scientist, IASRI(Technical Expert–A Scientist of the Institute)

Dr. Seema Jaggi MemberSenior Scientist, IASRI(Technical Expert–A Scientist of the Institute)

Dr. Madhuban Gopal MemberPrincipal Scientist and National Fellow, IARI(IPR Expert–A Scientist from ICAR Institutein the Zone

Dr. Rajender Parsad, HD (DE) Memberand Incharge, RCMU, IASRI Secretary

A joint meeting of Institute Technology ManagementCommittee (ITMC) and Institute TechnologyManagement Unit (ITMU) was held on 27 January2010 to discuss the mode of expenditure and furtherrequirement for XI Plan Scheme “Intellectual PropertyManagement and Transfer/Commercialization ofAgricultural Technology Scheme (Up scaling of existingcomponents i.e. Intellectual Property Right (IPR) underICAR Headquarter Scheme on management oninformation services)”.

Institute Technology Management Unit (ITMU)

As per the ‘ICAR Guidelines for Intellectual PropertyManagement and Technology Transfer/ Commercia-lization’ an Institute Technology Management Unit(ITMU; short title for Intellectual Property Managementand Technology Transfer Commercialization Unit atInstitute level IPM&TTU) for management of its IP/Deemed IP and transfer/commercialization oftechnologies has been constituted for pursuing all IPprotection, maintenance and transfer/commercializationrelated matters at the institute level as per theseguidelines and any other administrative or policydecisions taken in the ICAR from time to time. This willseek any specific, case-to-case basis advice/


116

assistance from the Zonal Agro-TechnologyManagement Centres (ZTMCs) at the zonal level. Thecomposition of the ITMU is as given below:

Dr. Rajender Parsad Officer InchargeHD (DE), Incharge (RCMU)Dr. Tauqueer Ahmad, Senior Scientist Member

Sh. PP Singh, Technical Officer Member

Institute Joint Staff CouncilThe Institute has a Joint Staff Council (IJSC) to promoteharmonious relations and secure the best means ofco-operation between the Council/IASRI as employerand the general body of its employees in matters ofcommon concern for ensuring a high degree ofefficiency in the service. The Institute Joint Staff Councilof the Institute is:

Dr. VK Bhatia Director Chairman

Official-side Representatives

Dr. PK Malhotra HD (CA) MemberDr. Rajender Parsad HD (DE) and Member

Incharge RCMUDr. PK Batra Principal Scientist and Member

Welfare OfficerDr. KK Tyagi Principal Scientist MemberSh. Krishan Kumar F&AO (Ex-Officio) MemberHead of Office Member-

Secretary

Staff-side Representatives

Sh. Raj Pal SSSGr-II SecretarySh. DPS Mann Assistant MemberSh. MM Maurya Technical Officer MemberSh. Satya Pal Singh Technical Officer MemberSh. KB Sharma UDC Member

Sh. Ashok Kumar SSSGr-II Member

IASRI Employees Co-operative Thrift and CreditSociety Limited

The Society, registered with the Registrar, Co-operativeSocieties, Delhi Administration, Delhi continued itsactivities during 2009-10 in similar manner as duringthe past years by advancing regular and emergent loanto its members and looking after their welfare. Thesource of funds of the society is Share money (valueof each share is Rs. 50), compulsory deposit (Rs. 200per month from each member) and fixed deposits. Thepresent strength of members is 330. The ManagementCommittee of the Society for the period 2009-2012 isas follows:

Sh. UC Bandooni President

Miss Vijay Bindal Vice-President

Sh. Pratap Singh Secretary

Sh. Pradeep Kumar Treasurer

Mrs. VL Murthy Member

Mrs. Satinder Pal Member

Sh. Manoj Kumar Member

Sh. GM Pathak Member

Sh. Sudarshan Sharma Member

Sh. Parbhu Dayal Member

Sh. Rajnath Member

− The Society has advanced Rs. 93,19,400 ( RupeesNinety three lakh ninteen thousand four hundredonly) to its members as loan.

− An amount of Rs. 751 ( Rupees Seven hundredfifty one only) each was given as gift to memberson their retirement from the Institute.

− The financial help of Rs. 2000 ( Rupees twothousand only ) was extended from the memberwelfare fund of the society to Sh. K.P. Singh for hismedical treatment.

Institute Grievance Committee

The Grievance Committee of the Institute (constitutedas per ICAR rules) provides the employees a forum toventilate their grievances relating to official matters andfor taking remedial measures. The GrievanceCommittee of the Institute constituted for a period oftwo years w.e.f. October 2007 is as follows:

Official-side RepresentativeDr. VK Bhatia ChairmanDr. Prajneshu MemberSh. AK Chaturvedi MemberSh. Krishan Kumar MemberSh. Narender Kumar Member Secretary

Staff-side Representative

Sh. Pal Singh MemberSh. Vijay Pal Singh MemberSh. Basant Kumar Member

Sh. Charan Singh Member

Two meetings of the Grievance Committee of theInstitute were held on 26 June and 26 October 2009.The Grievance Committee of the Institute wasreconstituted with the approval of the ManagementCommittee of the Institute for a period of two years


117

w.e.f. 02 March 2010 as follows:

Official-side RepresentativeDr. VK Bhatia ChairmanDr. Ranjana Agrawal MemberCAO MemberF&AO MemberAAO (Admn. II) Member Secretary

Staff-side Representative

Sh. Pal Singh MemberSh. Vijay Pal Singh MemberSh. Chander Vallabh MemberSh. Charan Singh Member

ICAR Staff Welfare Fund SchemeThe employees of the Institute have constituted a ICARStaff Welfare Fund previously known as BenevolentFund from their own contributions to provide relief tothe families of the employees who die in harness andare left in an indigence condition. A gift of Rs. 600 isbeing given to each retiring employees of the Institute.During the year, a sum of Rs. 55258 was collected frommembers. Gifts of Rs. 9600 were distributed to sixteenretiring personnel of the Institute and a sum of Rs. 4800@ Rs 400 was given for the farewell of fourteen retiringpersonnel agreed for taking farewell. A relief ofRs. 20000 was provided to Sh. Janak Kumar beinginjured during ICAR Zonal Sports Meet.

The Committee of the Institute for ICAR Staff WelfareFund Scheme was reconstituted for a period of twoyears w.e.f. 07 November 2009 as follows:

Dr. PK Batra, Welfare Officer ChairmanChief Administartive Officer Vice-PresidentF&AO MemberSecretary, IJSC MemberDr.(Mrs.) Seema Jaggi MemberAAO (Admn.-II)) Member

Women Cell

A Women Cell has been set up at the Institute on27 January 2000. The cell functions for the welfare ofwomen in general. It caters to the issues pertaining tothe grievances of women employees. The presentcompositions of Women Cell is:

Dr. Ranjana Agrawal Principal Scientist & HD (FT) ChairpersonDr. Seema Jaggi Senior Scientist MemberMs. Vijay Bindal Technical Officer MemberSmt. Sushma Banati Senior PS MemberSmt. Sushma Gupta Asstt. Admn. Officer Convenor

Complaint Committee

A Complaint Committee has been set up at the Instituteon 18 August 2006 for the prevention of sexualharassment of women at work place. The presentcomposition of this committee is:

Dr. Ranjana Agrawal Principal Scientist Chairpersonand HD (FT)

Smt. Meera Mathur Technical Officer (CSIR) Member (3rd Party)Sh. SK Sublania MTO (T-9) MemberSmt. Satinder Pal Technical Officer Member

Sh. Fabian Minz UDC Member

Hostel ActivitiesThere are three well furnished hostels, viz. PanseHostel, Sukhatme Hostel and International TrainingHostel to cater the residential requirements of thetrainees and students of M.Sc., Ph.D. courses andSenior Certificate Course (SCC) at the Institute withinits premises. Officers and trainees of the various otherrefresher, short-term and ad-hoc training coursesorganised at the Institute are also provided residentialaccommodation at the Panse Hostel-cum-GuestHouse. Boarding and lodging arrangements are madeavailable for the guests who stay in Guest House fromdifferent Departments/Organisations. Ample facilities existfor the cultural activities and sports for the hostel inmates.

Sukhatme Hostel mess is run by the students on Co-operative basis. The general management of theSukhatme Hostel is vested with the Warden, who isassisted by the Prefect and other students. A GeneralBody meeting of IASRI hostel inmates was held on 28October 2009 under the Chairmanship of Dr. RanjanaAgrawal, Principal Scientist and Warden. For smoothfunctioning of the hostel activities, the ExecutiveCommittee members elected for the session 2009-10 are:

Prefect Ankur BiswasMess Secretary/Assistant Prefect Arpan BhowmikCultural Secretary Nishikant Taksande

& Sandip SadhuMaintenance Secretary Manoranjan DasCashier Arijit SahaHealth Secretary Debasish DuttaSports Secretary Rupam Kumar SarkarCommon Room Secretary AKM Samimul AlamComputer Lab Secretary Sandipan SamantaAuditors Mahondas Singh,

Hironmoy Das &Sudhir Srivastava

Mess Observers Committee Sankalpa Ojha,Sashi Shekhar &Mrityunjoy Mondal

Warden’s Nominee Eldho Varghese


118

On the eve of the Annual Day of the Institute on 02July 2009, a sports week was organised in SukhatmeHostel wherein students at IASRI participated in varioussports like table-tennis, badminton and musical chair,etc.

International Training Hostel

Newly built, International Training Hostel wasInaugurated by Hon’ble Dr. Mangala Rai, Secretary,DARE & Director General, ICAR on 09 July 2009.

Houses of the Institution and she is assisted bySh. Sunil Kumar.

Recreation and Welfare Club

The Institute has a Recreation and Welfare Club whichprovides facilities for indoor and outdoor games topromote social and friendly relations among themembers and general recreation and welfare of itsmembers. The club organises sport tournamentsannually at Institute level for different games/events. Thefunctioning of the Recreation and Welfare Club ismonitored by Institute Sports Committee and Sh V.K.Mishra is appointed as acting Secretary.

Sports Activities

For organizing different activities relating to sports meet,Institute Sports Committee has been constitutedas follows:

Dr. VK Bhatia PresidentDr. KK Tyagi Vice PresidentDr. PK Batra MemberCapt. Mehar Singh MemberSh. Arun Kumar Chaturvedi MemberSh. Krishan Kumar MemberSh. RS Tomar MemberSmt. Vijaya Laxmi MemberSh. DPS Mann MemberSh. RK Saini MemberSh. Amar Singh MemberSh. Rambhool MemberSh. KB Sharma MemberSh. Ashok Kumar MemberSh. MM Maurya MemberSh. Raj Kumar Verma MemberSh. Raj Pal MemberSmt. Satinder Pal MemberSh. VK Mishra Convenor

During the period under report the Institute SportsContingent participated in Inter-Zone Sports Meet 2009-10 organized by NDRI, Karnal during 12-15 December2009 and secured Championship Trophy in TableTennis (Team Events-Men). Institute also partcipatedin ICAR Zone II (Central Zone ) Inter-Institutional SportsMeet 2010 organized by NBSS&LUP, Nagpur during04-08 March 2010 and achieved Championship Trophyin Kabaddi and Table Tennis (Team Events-Men)Winner and Runner-up position in Chess (Men)-Individual event. Shri OP Khanduri was Chef-de-Mission.

Inauguration of International Training Hostel

Number of Floors : Two, Ground Floor andFirst Floor

Number of Rooms : 12Area of Ground Floor : 531 square metreArea of First Floor : 531 square metre

Available Amenities

Ground Floor : Office, Lounge,Common Room,Dinning Hall, Pantry,Kitchen, 4 Rooms,Caretaker Room

First Floor : 8 RoomsAmenities Available : Two Beds, Side Table,

Two Study Tables, TwoChairs, Dressing Table,Cupboard, Television,Air Conditioner,Geyser and Blower

A total of 617 Trainees/Guests from ICAR Instiutes,SAU’s/Officials from Central/State Governments/Private Organisations and Foreign Trainees fromvarious institutes were satyed at ITH and about 2362guests were stayed at Panse Guest House during theperiod. Smt. Sushma Banati is the Incharge of the Guest

120

Hkkjrh; Ñf"k vuqla/ku laLFkku dh lgk;d funs'kd (jktHkk"kk)]lqJh lhek pksiM+k us O;k[;ku fn;s rFkk vH;kl djok;k A blo"kZ dh r`rh; dk;Z'kkyk ¶Hkkjr esa iQ+ly vkdyu losZ{k.k¸fo"k; ij 07 uoEcj 2009 dks vk;ksftr dh x;h A bldk;Z'kkyk dk mn~?kkVu Hkkjr ljdkj] jlk;u ,oa moZjd ea=kky;]vkS"k/ fuekZ.k foHkkx] jk"Vªh; vkS"k/ ewY; fu/kZZj.k çkf/dj.k dsvè;{k] MkW- ,l-,e- >kjoky }kjk fd;k x;k A prqFkZ dk;Z'kkyk29 ekpZ 2010 dks ¶dk;kZy; ds dk;Z esa lax.kd dk ç;ksx¸fo"k; ij vk;ksftr dh x;hA

¶fgUnh ekfld çxfr fjiksVZ dk çi=k Hkjus rFkk çs"k.k ,oa vkorhjftLVjksa ds mfpr j[kj[kko¸ ds fy, laLFkku ds dfeZ;ksa ds fy,12 tuojh 2010 dks ,d çf'k{k.k dk;ZØe vk;ksftr fd;kx;k A

laLFkku esa dk;Zjr lHkh fgUnhrj Hkk"kh vf/dkfj;ksa@deZpkfj;ksaa }kjkfgUnh Kku lEcU/h izf'k{k.k iwjk fd;k tk pqdk gS A vkt rd dhfLFkfr ds vuqlkj] laLFkku esa vc dksbZ ,slk fgUnhrj Hkk"khvf/dkjh@deZpkjh 'ks"k ugha jg x;k gS ftls fgUnh Kku lEcU/hçf'k{k.k fn;k tkuk 'ks"k gks A blds vfrfjDr] ¶fgUnh f'k{k.k;kstuk¸ ds vUrxZr laLFkku esa fgUnh vk'kqfyfi ds çf'k{k.k dky{; Hkh laLFkku }kjk iwjk dj fy;k x;k gS rFkk dsoy nksuo&fu;qDr Vaddksa }kjk fgUnh f'k{k.k ;kstuk ds vUrxZr tuojh2010 esa vk;ksftr fgUnh Vad.k ijh{kk nh x;h gS A

laLFkku esa okf"kZd dk;ZØe esa fufgr y{;ksa dks iwjk djrs gq,laLFkku ds vf/dkfj;ksa@deZpkfj;ksa }kjk viuh vksj ls fy[ks tkusokys lHkh i=k rks fgUnh vFkok f}Hkk"kh :i esa fy[ks gh x;s lkFkgh] *d*] *[k* rFkk *x* {ks=kksa ls v¡xzst+h esa çkIr i=kksa ds mRrj Hkh'kr&çfr'kr fgUnh esa vFkok f}Hkk"kh :i esa fn;s x;s A ^d* rFkk^[k* {ks=kksa dh jkT; ljdkjksa ,oa muds dk;kZy;ksa vkSj x+Sj&ljdkjhO;fDr;ksa ds lkFk i=kkpkj 'kr&izfr'kr fgUnh esa vFkok vis{kkuqlkjf}Hkk"kh :i esa gh fd;k x;k A laLFkku ds fofHkUu oSKkfud çHkkxksarFkk ç'kklfud vuqHkkxksa }kjk vk;ksftr dh tkus okyh cSBdksa dhdk;Zlwph rFkk dk;Zo`Rr 'kr&çfr'kr fgUnh esa vFkok f}Hkk"kh :iesa tkjh fd;s x;s A

Hkkjr ljdkj] x`g ea=kky;] jktHkk"kk foHkkx }kjk tkjh okf"kZddk;ZØe ds vuqlkj viuk dk;Z 'kr&izfr'kr fgUnh esa djus dsfy, vkB vuqHkkxksa dks fofufnZ"V djus dk y{; laLFkku }kjkigys gh çkIr dj fy;k x;k gS A laLFkku esa viuk dk;Z'kr&çfr'kr fgUnh esa djus ds fy, nl vuqHkkx igys ls ghfofufnZ"V gSa A

ç'kklfud dk;Z ds vfrfjDr laLFkku esa oSKkfud çÑfr dsdk;ksZa esa Hkh fgUnh ds mi;ksx dks çksRlkfgr fd;k tkrk gS AoSKkfudksa us viuh ifj;kstuk fjiksVksZa ds lkjka'k f}Hkk"kh :i esafn;s] fo|kfFkZ;ksa }kjk vius 'kks/&çcU/ksa esa f}Hkk"kh :i esa lkjçLrqr fd;s x;sA oSKkfudksa ,oa rduhdh dfeZ;ksa }kjk fgUnh esa'kks/&i=k çdkf'kr fd;s x;s A laLFkku dh oSKkfud MkW- jatukvxzoky }kjk 02 vçSy 2009 dks vkdk'kok.kh ds jk"Vªh; pSuyij çkphu Hkkjrh; xf.krK ¶vk;ZHkV~V¸ ij jsfM;ks&okrkZ çLrqrdh x;h A laLFkku dh osclkbV f}Hkk"kh gS ftldks le;≤ ijv|ru fd;k x;k A

x`g ea=kky;] jktHkk"kk foHkkx }kjk tkjh rFkk ifjpkfyr fofHkUuudn iqjLdkj ;kstuk,¡ laLFkku esa ykxw gSa A laLFkku ds dfeZ;ksa usbu ;kstukvksa esa Hkkx fy;k A

laLFkku esa 01 ls 14 flrEcj 2009 ds nkSjku fgUnh i[kokM+s dkvk;kstu fd;k x;kA bl nkSjku vk;ksftr dk;ZØe@çfr;ksfxrk,¡bl çdkj gSa % dkO;&ikB] f'k{kd fnol] MkW- njksxk flag Le`frO;k[;ku] çHkkxh; py&'khYM] ç'u&eap] vUrk{kjh] okn&fookn]fgUnh Jqrys[k ,oa 'kCnkFkZ ys[ku çfr;ksfxrk (fgUnhrj Hkkf"k;ksads fy,)] fgUnh orZuh çfr;ksfxrk ,oa 'kks/&i=k&iksLVj&çn'kZuçfr;ksfxrk A 05 flrEcj 2009 dks f'k{kd fnol dk vk;kstufd;k x;k rFkk bl volj ij eq[; vfrfFk] MkW- ine flag thdks lEEkkfur fd;k x;k A 14 flrEcj 2009 dks fgUnh fnol dsvolj ij ¶MkW- njksxk flag Le`fr O;k[;kuekyk¸ dk 18ok¡O;k[;ku laLFkku ds iwoZ funs'kd] MkW- jek dkUr ik.Ms; }kjk¶tyok;q ifjorZu vkSj Hkkjrh; Ñf"k¸ fo"k; ij fn;k x;k AfgUnh i[kokM+s ds lekiu lekjksg ds volj ij lekjksg ds eq[;vfrfFk] Hkkjrh; Ñf"k vuqla/ku ifj"kn~ ds mi&egkfuns'kd (Ñf"kvfHk;kaf=kdh)] MkW- enu eksgu ik.Ms; }kjk liQy çfr;ksfx;ksa dksiqjLÑr fd;k x;k A

laLFkku }kjk fgUnh if=kdk] ¶lkaf[;dh&foe'kZ ds ik¡posa vaddk çdk'ku fd;k x;kA bl vad esa laLFkku ds dhfrZLrEHk]laLFkku dh Lo.kZ&Tk;URkh ;k=kk ds dqN va'k ,oa bl o"kZ fd;s x;svuqla/ku o vU; dk;ksZa ds laf{kIr fooj.k ds lkFk&lkFk Ñf"klkaf[;dh ,oa lax.kd vuqç;ksx ls lEcfU/r fofHkUu ys[kksa,oa 'kks/&i=kksa dks Hkh çLRkqRk fd;k x;k gS A laLFkku esa vk;ksftrMkW- njksxk flag Le`fr O;k[;kuekyk ds vUrxZr 18osa oSKkfudO;k[;ku dks vkefU=kr Kkuo/Zd ys[k ds :Ik esa bl if=kdk esalfEefyr fd;k x;k gS A vUr esa ikBdksa ds fYk, nSfud Lej.kh;lkaf[;dh; ,oa lax.kd vuqç;ksx ls lEcfU/r 'kCn&'krd fgUnho v¡xzst+h esa fn;k x;k gS A

DEVELOPMENT AND ANALYSIS OF EXPERIMENTAL DESIGNS FOR AGRICULTURAL SYSTEM RESEARCH

1. Designs for single factor and multi-factor experiments and their applications in agricultural systems research.(ICAR National Professor Scheme)VK Gupta

2. A statistical investigation on production, economic and energy potential of crop sequences in different agro-ecosystem.Anil Kumar

3. Planning, designing and analysis of experiments planned ON STATION under the Project Directorate of FarmingSystems Research.Anil Kumar, Aloke Lahiri, OP Khanduri

4. Planning, designing and analysis of ON FARM research experiments planned under Project Directorate of FarmingSystems Research.NK Sharma, PK Batra, OP Khanduri

5. Planning, designing and analysis of data relating to experiments conducted under AICRP on long-term fertilizerexperiments.DK Sehgal, Krishan Lal, SMG Saran, Shashi Dahiya

6. Planning, designing and analysis of experiments relating to AICRP on STCR.Aloke Lahiri, VK Gupta, A Subba Rao, Y Muralidharudu (IISS, Bhopal), Rajender Parsad, Abhishek Rathore(IISS, Bhopal).

7. Designs for mixture experiments in agriculture.Krishan Lal, VK Gupta, PK Batra, Lalmohan Bhar

8. Agricultural field experiments information system.PK Batra, OP Khanduri, DK Sehgal, Rajender Parsad, Sudeep

9. Experimental designs for agricultural research involving sequences of treatments. (Lal Bahadur Shastri YoungScientist Award Project).Cini Varghese, Seema Jaggi

10. Genaralized row-column designs for agriculture.Cini Varghese, Seema Jaggi

FORECASTING AND REMOTE SENSING TECHNIQUES AND STATISTICAL APPLICATIONS OF GIS INAGRICULTURAL SYSTEMS

11. Neural network based forecast modeling in crops.Amrender Kumar, Ramasubramanian V, Ranjana Agrawal

12. Stochastic process modeling and forecasting through discrete nonlinear time series approach.Himadri Ghosh, Prajneshu

Annexure

List of Approved On-going Research Projects


122

13. Use of discriminant function and principal component techniques for weather based crop yield forecast.Chandrahas, Ranjana Agrawal, SS Walia

14. Weather based models for forecasting potato yield in UP.SC Mehta, Satya Pal, Vinod Kumar, (Krishi Bhawan Lucknow)

15. Development of Forecasting module for podfly, Melanagromyza obtusa Malloch in late pigeonpea.SK Singh (IIPR, Kanpur), Ranjana Agrawal, Amrender Kumar

16. A study on editing and imputation using neural networks.Ramasubramanian V, Ranjana Agrawal, SB Lal

DEVELOPMENT OF TECHNIQUES FOR PLANNING AND EXECUTION OF SURVEYS AND ANALYSIS OF DATAINCLUDING ECONOMIC PROBLEMS OF CURRENT INTEREST

17. Developing remote sensing based methodology for collecting agricultural statistics in North-East hilly region.Prachi Misra Sahoo, Anil Rai, Tauqueer Ahmad, Samir Farooqi

18. Study on status and projection estimates of agricultural implements and machinery.KK Tyagi, Jagbir Singh, KK Kher, VK Jain, Surendra Singh (CIAE, Bhopal)

19. Evaluation of rationalization of minor irrigation statistics scheme (Ministry of Water Resources, Govt. of India).VK Bhatia, UC Sud, DC Mathur, Hukum Chandra, SB Lal

20. Small area estimation for zero inflated data.Hukum Chandra, HVL Bathla, UC Sud

21. Sampling methodology for estimation of meat production in Meghalaya (Department of Animal Husbandry, Dairying& Fisheries, Ministry of Agriculture, Govt. of India).Hukum Chandra, UC Sud, AK Gupta and DC Mathur

22. Impact of micronutrients on crop productivity and returns.SP Bhardwaj, Rajendra Kumar, Ashok Kumar, Anil Kumar

23. Estimation of extent of farming practices, resources and activities with energy use.Jagbir Singh, KK Tyagi, KK Kher, AK Gupta, VK Jain

24. Risk assessment and insurance products for agriculture (NAIP Component-I: Consortium Partner)

NCAP, New Delhi: PK Joshi, BC BarahIASRI, New Delhi: Anil Rai, PK Malhotra, KK Chaturvedi, Ramasubramanian V

25. An econometric analysis of groundwater markets in Indo-Gangetic Plains of India.DR Singh, AK Vasisht, Prawin Arya , Ashok Kumar, Mahender Singh

26. Visioning, Policy Analysis and Gender (V-PAGe) Sub-Prog. III: Policy analysis & market intelligence (NAIPComponent–I: Consortium Partner).VK Bhatia, AK Vasisht, DR Singh, Ashok Kumar, SP Bhardwaj, Prawin Arya, Sushila Kaul, Pratap Singh(NCAP, New Delhi), NP Singh (IARI, New Delhi), Anil Rai, KK Chaturvedi

27. Visioning Policy Analysis and Gender (V-PAGe) Sub-Prog. II: Technology forecasting (NAIP Component–I:Consortium Partner).VK Bhatia, Ranjana Agrawal, Ramasubramanian V, Amrender Kumar, Satya Pal, Anil Rai, KK Chaturvedi, GirishKumar Jha (IARI, New Delhi)

28. An econometric study of women empowerment through dairying in selected districts of Haryana.Sushila Kaul, SP Bhardwaj, Sanjeev Panwar


123

29. Econometric study of long-run effect of public investment in irrigation on food grains productivity.Ashok Kumar, SP Bhardwaj

MODELING AND SIMULATION TECHNIQUES IN BIOLOGICAL SYSTEMS30. A statistical study of rainfall distribution and rainfall insurance.

Asha Saksena, Prajneshu, Himadri Ghosh

31. Computational analysis of SNPs at functional elements of rice genome.AR Rao, Anu Sharma, SB Lal, Trilochan Mohapatra (NRCPB, New Delhi)

32. Empirical investigations on estimation of genetic correlation.SD Wahi, AR Rao

33. Whole Genome Association analysis in common complex diseases: An Indian initiative (DBT Fuded)BK Thelma (UDSC, New Delhi), Ramesh C. Juyal (NII, New Delhi), Sanjay Jain (DU, Delhi),AR Rao (IASRI, New Delhi), Ashok Kumar (AIIMS, New Delhi), Ajit Sood (DMC, Ludhiana)

34. Bioprospecting of genes and allele frequency for abiotic stress tolerance (NAIP Component-IV: Consortium Partner)NRCPB, New Delhi: T MohapatraIASRI, New Delhi: AR Rao, SB Lal, Sudeep

DEVELOPMENT OF INFORMATICS IN AGRICULTURAL RESEARCH

35. Web solutions for partially balanced incomplete block designs.Anu Sharma, Cini Varghese, Seema Jaggi

36. Statistical Package for Animal Breeding 2.1 (SPAB 2.1).IC Sethi, SD Wahi

37. Knowledge data warehouse for agricultural research.Anil Rai, PK Malhotra, Seema Jaggi, KK Chaturvedi, Prachi Misra Sahoo, Mohd. Samir Farooqi

38. Strengthening, refining and implementation of expert system on wheat crop management.

SN Islam, HO Agarwal, Mohd. Samir Farooqi, KK Chaturvedi, HS Sikarwar

39. Decision support system for manpower planning – PERMISnet.Alka Arora, Balbir Singh, Samir Farooqi, Shashi Dahiya, Anil Rai

40. Intranet solutions for PG School, IARI.Sudeep, Hari Om Agarwal, Pal Singh

41. Machine learning approach for data mining.Anshu Bharadwaj, Shashi Dahiya, Rajni Jain (NCAP, New Delhi).

42. An eLearning solutions for agricultural education using MOODLE.Shashi Dahiya, Anshu Bharadwaj, KK Chaturvedi, Seema Jaggi, Cini Varghese

43. Project information and management system of ICAR (PIMS-ICAR).RC Goyal, PK Malhotra, VH Gupta, Sudeep, Alka Arora, Pal Singh

44. National information system on agricultural education network in India (NISAGENET-III).RC Goyal, VH Gupta

45. Software for survey data analysis.SB Lal, Anu Sharma, VK Mahajan, Hukum Chandra, Anil Rai


124

46. Development of expert system on seed spices.SN Islam, Hari Om Agarwal (IASRI,New Delhi), RK Kakani, Krishna Kant, OP Aishwat, MA Khan, GK Tripathi(NRC on Seed Spices, Tabiji, Ajmer)

47. Development of web enabled statistical package for agricultural research (SPAR 3.0).Sangeeta Ahuja

48. Development of gender information system for agriculture.HK Dash, M Srinath and Sabita Mishra (NRCWA, Bhubneshwar),SB Lal, Anu Sharma, Anil Rai (IASRI, New Delhi)

49. Expert system for maize crop (Collaboration with Directorate of Maize research).Hari Om Agarwal, Sudeep, Harnam Singh Sikarwar

50. Strengthening Statistical Computing for NARS (NAIP Component-I: Consortium Leader with 08 other ConsortiumPartners).VK Bhatia (Consortium Leader), Rajender Parsad (Consortium PI), PK Malhotra, VK Gupta,VK Mahajan, Seema Jaggi, Samir Farooqui, Ramasubramanian V, LM Bhar, AK Paul, N Shivaramne

Documents

Preface - iasri.icar.gov.in · • Signing of MOU with IARI, New Delhi to start new courses for M.Sc. and Ph.D. degree in Agricultural Statistics 1970 • Status of a full fledged