Oct.-Dec.,2015 - Shakarganj Researchssri.pk/psj/PSJ October-December 2015.pdf · Oct.-Dec.,2015. 1 | P a g e Editorial Board Mr. Altaf M. Saleem Chairman Dr. Shahid Afghan Editor-in-Chief

Oct.-Dec., 2015

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Editorial BoardMr. Altaf M. Saleem ChairmanDr. Shahid Afghan Editor-in-ChiefDr. Iftikhar Ahmed MemberDr. Muhammad Zubair MemberDr. Javed Iqbal MemberDr. Aamir Ali MemberMr. Aamir Shahazad Editor

SubscriptionAamir ShahzadShakarganj Sugar Research InstituteToba Road, JHANGPh: +92 47 763 1001-5 Ext. 603, 604Email: [email protected]

Subscription RatePakistan PKR 1,000/-OVERSEAS US$ 50/-

Recognized byHigher Education Commission (HEC) Pakistan

Cited byAsia Net Pakistan (Factiva International)Commonwealth Agriculture & BiologyInternational (CABI-UK)

ISSN 1028-1193

Panel of RefereesDr. P. Jackson: Principal Scientist, CSIRO, AustraliaDr. Raul O. Castillo: Director General, ResearchStation EI Triunfo, EcuadorDr. Benjamin Legendre: Interim Director, AudubonSugar Institute, USADr. Yong-Bao Pan: Research Plant MolecularGeneticist, USDA-ARS, USADr. Jack C. Comstock: Research Leader, ARSUSDA, Canal Point Florida, USADr. Sizuo Matsuoka: Director, Canavialis SA, BrazilDr. Niranjan Baisakh: Asstt. Professor, - SPESS, LSUUSADr. Abdul Rauf: Prof. & Chairman Plant PathologyPMAS Arid Agriculture University, RawalpindiDr. Asif Tanvir: Professor, Dept. of Agronomy, UAFDr. Muhammad Bilal Chattha: Assistant Professor,Agriculture College, Punjab University

CONTENTS

02ADOPTION OF ENERGY SAVING EQUIPMENTS ATRAMZAN SUGAR MILLSMuhammad Yasin

07RATOON PERFORMANCE OF ELITE SUGARCANECLONES UNDER SOUTHERN PUNJAB CONDITIONS

Naeem Ahmad, Muhammad Aslam,Muhammad Kashif Hanif and Zulfiqar Ali

12

CHARACTER ASSOCIATION AND PATHANALYSIS OF THE PHYSIOLOGICALRESPONSES UNDER MOISTURE STRESS INSUGARCANE VARIETIES

Manel Dapanage and Sumangala Bhat

22

EFFECT OF SOWING AND HARVESTINGTIME ON THE YIELD AND SUGAR RECOVERYOF SUGAR BEET UNDER D. I. KHANCONDITION

Karim Bakhsh Malik, Soban Qureshi, Asif ImranShah and Muhammad Zubai

31SUGAR AND ADDICTION

World Sugar Research Organization (WSRO)Position Statements

37SUGAR INDUSTRY ABSTRACTS

42INTERNATIONAL EVENTS CALENDAR

43STORY OF SWEETS

i. Leg Of Lamb Stuffed With Riceii. Mango Ice Cream

44GUIDELINES FOR AUTHORS

PAKISTAN SUGAR JOURNAL

October-December, 2015 Vol. XXX, No.04

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ADOPTION OF ENERGY SAVING EQUIPMENTSAT RAMZAN SUGAR MILLS

Muhammad YasinProduction Manager, Ramzan Sugar Mills

ABSTRACT

In sugar industry energy conservation means to increase the earning of the organization, decreasein energy consumption for processing reduces the cost of production and give saving of fuel.Keeping in view these aspects and future vision of our honorable Managing Director, themanagement of Ramzan Sugar Mills is continuously working on energy saving program since last5 years. Some bold steps have been taken in this respect; modern technologies and efficientenergy saving equipments are adopted such as:

Falling Film EvaporatorsEvaporator ArrangementVapor Line HeatersDirect Contact HeatersFlash Heat RecoveryMolasses Conditioning With Low Temperature VaporUse of Hot Condensate for Sugar DryingAuto Condensing and Spray system

Installation of VFDsThe whole team of RSML is committed to optimal use of energy to ensure cost effectiveoperations and conservation of energy resources. By grace of ALLAH it is the hour of satisfactionthat we have achieved a goal of remarkable decrease in steam consumption and bagasse saving.This is the reason why RSML is travelling efficiently and successfully towards power co-generationwith available resources in the existing setup of project.

IntroductionAny attempt at EnergyConservation in a steamgeneration system isconstituted of two basicaspects,a- Installation of suitableenergy efficient equipment inthe factory.b-Energy efficient operation ofthe factory.The presentation dealsessentially with the first.

1. Falling film EvaporatorIn this popular type ofevaporator, juice travelsfrom top to the bottom andas it descends, it takes theentrained vapour along withit to a lower chamber, wherethe vapour and liquid areseparated. The falling filmevaporators have manyadvantages over theconventional evapora-tors:Effective juice distributionand short contact time

between juice and steam.Thefalling film evaporator offersan excellent heat transfer.The design of the evaporatorsis such that, the juice is incontact with the heatingsurface in a thin layer over thelength of the heating surface.In Ramzan Sugar MillsLimited, Chiniot, we got theopportunity to install a pair offalling film evaporators (3000M2 + 3000 M2) and by thegrace of ALMIGHTY ALLAH,


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after successful operation of1st set of FFEs , it wasdecided to install more FFEsfor further steam economy andenhancement in crushing, soin 2011 one more pair of FFEs(3000M2) each was installedand operated withconsiderable steam economyand remarkable fuel saving inseason 2012-13 and 2013-14.All these results and successencourages the managementof RSML to work more in thisrespect. Now another FFE of6000M2 is being installed todecrease steam consumptionup to 42% on cane and toenhance crushing capacity upto 12000 TCD.

2- VAPOR LINE HEATERThe vapors exerted by the lasteffect of evaporators setgenerally goes to condenser.These vapors contain a smartamount of heat energy whichis wasted in spray pond andcreates extra load on spraysystem. We decide to use thisenergy for 1st stage primaryheating. For this purpose inRSML tubular heaters areinstalled in vapor line of lasteffects.These heaters give aremarkable rise in temperatureof raw juice, which givesconsiderable economy ofvapors and load oncondensers is also reducedwhich leads towards lessconsumption of injection watertoo.

The AdvantagesIt works as an effectiveentrainment catcher.Consumes last effectevaporator effectively.Additional amount ofcondensate is obtainedwhich can be used to fulfillboiling house needs.Steam economy due tousage of vapors going tocondenser and lessconsumption of injectionwater.

3- Direct Contact HeatersThis invention is moreefficient in respect oftransmission of heatbecause of direct contact ofheating media with juice. Noheat loss occurs in shape ofcondensate because totalheat content of vapors istransmitted to juice.In R.S.M.L three D.Cheaters were installed inyear 2010. Direct Contact(DC) Heaters have high heattransfer coefficient due toabsence of resistances likeliquid film resistance,condensing vaporresistance, resistance ofscale and tube material.

Main benefits of DCheaters:Eliminate juice heatercleaningEconomical system as nostandby vessel is requiredfor cleaningLow maintenanceEasy to operate and controlHigh heat transfer efficiency

Can be operated at lowpressure vaporHeating of juice in countercurrent manner that removesdissolved gases veryefficiently and enhancesclarification efficiencies

FLASH CIGAR:In 2010 at the start of energysaving program at RSMLwhen it was decided to installa set of 1st two FFEs, it wasalso considered to installcentralized controlmanagement system ofcondensate.Condensate from allevaporators of quintuple effectexcept steam condensateenters in different chambersaccordingly, flash is taken outfrom each chamber andcondensate travels towardsnext chamber and at the end,from last chamber after takingout maximum flash it ispumped towards over headservice tank.Flash Cigar improves watermanagement of the plant byreducing the final condensatetemperature to level requiredfor process use.The basic principle is torecover the flash from thecondensate coming out fromthe heaters, evaporators andpans.It gives steam economy about= 1.76 %on cane

AdvantagesEliminates the installation ofno. of condensate tanks alongwith its Pumping System. This


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in turn saves electrical energyand also reduces cost ofmaintenanceElimination of sealing tanksand piping removescongestion at the ProcessHouseTrouble free operation andeasy to maintainNo air leakage in the vacuumsystemImproves the watermanagement of the plant

Stainless steel siphons areprovided to transfer thecondensate to lower pressurechambers making its operationtrouble free and fool proof.

5- Plate Heat ExchangerIt is a simple plate heatexchanger in which from oneend condensate of 1st effectFFE (steam condensate)enters having temperatureabout 120 °C, from the otherend a part of condensate ofabout 84°C from last chamberof cigar enters as countercurrent flow, here heat transfertakes place and steamcondensate of about 110 °Cpumped for boilers storagetanks, and from the other endtemperature of circulatedcondensate of last chamberrises up to 112 °C entersagain in first chamber of cigartank for flash recovery.

6- Molasses ConditionersPreviously for molassesconditioning at RSMLtraditional method of dilution,stirring and heating with

washing steam wasimplemented, but in 2010-2011 imported molassesconditioner were installedand operated successfully.This type of conditionersgives some benefits leadingtowards energy savings, andworks without additionalwater for dilution. Directcontact molassesconditioners ensure perfectdissolution of crystals byusing heat content of lowpressure vapor for savingsin steam.

AdvantagesDirect heating of molassesunder vacuum helps perfectdissolution of crystalsAvoids addition of water butalso improves the quality ofconditioned molasses whichis very good for the processHigh heat transfer efficiency.Efficient operation on lowpressure vapors. No stirrerrequired thus no troublesassociated with usingmechanical stirring.

7- Hot Water RadiatorsWe all are well aware thatextra moisture content infinished product createshuge problems and leavesbad effect over packedsugar. So drying of sugar isan important matter of sugarmanufacturing. Traditionallysteam radiators are used insugar industry to get hot airfor sugar drying. At R.S.M.L,in energy saving strugglesthese steam radiators also

replaced with hot waterradiators. For this purpose hotwater of about 80 - 85°C fromoverhead service tank is used.The temperature of hot airgained is 60 to 65 °C, whilethe dried sugar temperature is38 – 42 °C.

8- Efficient Condencing &Spray SystemIn the year 2009 decision wastaken by management toreplace the old multi jetcondensers and spray systemwith more efficient automatedcondensers and spray system.All multi jet condensers werereplaced with automatedcondensers. Old injectionpumps of 3200 M3/hr replacedwith 2200 M3/hr. Similarly onspray side pumps of 3200M3/hr were replaced. At spraypond old nozzles werereplaced with more effectiveclusters. Each cluster consistsof 5 nos. of nozzlesAs a result of modification atspray pond remarkable drop intemperature was achieved.

Previously the temperaturedifference was 5°C to 6°C.After installation of newclusters it becomes 10°C to12°C positively. As a result ofall these changes,consumption of injection waterreduced to give us hugesaving of electrical energy. Itis computerized controlsystem. The main aim ofwhich is to reduce the powerconsumption and number ofpumps required for injection


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water and spray pond waterby monitoring the vacuum andtemperature at variouslocations. Power consumptionat injection and spray with oldand new pumps is givenbelow.

Injection PumpsWithout Auto CondensingRunning Load 1033 KWWith Auto CondensingRunning Load 576 KWEnergy Saving 457 KW 1033KW - 576 KW =

Spray PumpsWithout Auto CondensingRunning Load 549 KWWith Auto CondensingRunning Load 202 KWEnergy Saving 347 KW549KW - 202 KW =Total Saving on AutoCondensing System

Without Auto CondensingWith Auto CondensingInjection Pumps 1033KW576KWSpray Pumps 549KW 202KWTotal 1582KW 778KW

Difference 1582KW - 778KW= 804 KW

9- Installation of VFDsFor saving of electricalenergy VFDs are installed atFeed tables, Cane carriers,Cane cutters and boilers.

Total Saving on FeedTablesWithout VFD With VFDFeed Table-1. 20 KW10 KWFeed Table-2. 24 KW 12KWFeed Table-3. 17 KW 7 KWFeed Table-4. 30 KW 15KWTotal 82 KW 47 KWDifference 82KW - 47KW= 35KW

Total Saving on CaneCarriersWithout VFD With VFDCane Carrier-1 43KW 25KWCane Carrier-2 80KW 60KWCane Carrier-3 60KW 40KWTotal 183KW 125KWDifference183KW - 125KW = 58KW

Total Saving on BoilersWithout VFD With VFDBoiler-2. 366KW 260KWBoiler-3. 370KW 263KWTotal 736KW 523KWDifference

736KW - 523KW = 213KWGRAND TOTALBOILERS 213KWCANE CARRIERS 58KWFEED TABLES 35KWG. TOTAL 306KW

CONCLUSIONS:Although the falling filmevaporators are the mainsource of energy savingendeavor in Ramzan SugarMills Limited and sinceinstallation of vapor lineheaters, they are also givingconsiderable energy saving,but “Many Small Drops Makea River” Spray system, FlashCigar, D.C Heaters, P.H.E,Molasses Conditioners, HotWater Radiators and VFDs etcall these equipments jointlycontributed in energy savingand shared a reasonableamount of saved fuel. Thissaving of fuel is encouragingthe management for power co-generation in the light of visionof our honorable ManagingDirector. So work on 60 MWpower plant installations hasbeen started and in future weare planning for completeelectrification of the project.


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RATOON PERFORMANCE OF ELITESUGARCANE CLONES UNDER SOUTHERN

PUNJAB CONDITIONSNaeem Ahmad*, Muhammad Aslam*, Muhammad Kashif Hanif* and Zulfiqar Ali**

* Sugarcane Research Station, Khanpur ** Sugarcane Research Institute, Faisalabad

ABSTRACT

A field experiment to investigate ratooning potential of ten sugarcane clones was carried during2013-2014 at Sugarcane Research Station, Khanpur under hot dry conditions of Southern Punjab.The genotypes under investigation were S2003US.114, S2003US.165, S2003US.824,S2006SP.18, S2006SP.25, S2006US.469, S2006US.658, S2006US.832, S2006US.834 andCPF.246 (Standard). The results revealed that new promising sugarcane clone S2006US.658 onaccount of best stubble sprouting plant-1 (2.79), highest 100-cane weight (103.67 kg) coupled withgood millable cane count (104.64 thousand ha-1) gave maximum stripped cane yield of 107.63tons ha-1 . It was matchingly followed by S2003US.114 and CPF.246. The top yielder is also goodin quality and as such it fetched maximum sugar yield of 12.86 tons ha-1 followed by S2003US.114(12.05 tons ha-1). The promising sugarcane clone S2006US.658 owing to 7.45 and 0.96 % moreratoon cane and sugar yield, respectively over standard variety is capable of replacing it and canmake gigantic strides in sugarcane production for sweet revolution. However, its wide scale testingin various agro ecological zones is invited for regional adoptability.

Keywords: Sugarcane, Clones, Ratoon, Sugar, Millable Canes.

INTRODUCTION

Ratoon keeping is a verycommon practice amongsugarcane growers as ischeaper to grow by about 30-40% due to saving in soakingirrigation, land preparation,cost of seed and sowingoperations (Akhtar et al.,2003).Ratoons have anadditional advantage in givingbetter juice quality and sugarrecovery in comparison to theplant crop of same varietyunder similar conditions(Yadava, 1991). Ratoonoccupies 35-50 % of the totalsugarcane area in Pakistan(Malik and Gurmani,2005).Afzal et al., 1990studied the ratoonperformance of six sugarcane

varieties and recordedmaximum average cane yieldof 75.55 tons ha-1 for CP 43-33. The same varietysurpassed in sugar yield. El-Geddawy et al., 2002elucidated that sugarcanevariety GIT.54-9 significantlysuperseded the othersugarcane varieties in respectof stalk height, diameter andweight in both ratoon crops.Rafique et al., 2005 carriedout two years field experimentto investigate ratooningpotential of 10 sugarcanevarieties and concluded thatCPF-234 and HSF-240 gavesignificantly more ratoon yieldduring both years of studyprimarily due to bettersprouting of subterraneanbuds and cane formation.

Bashir et al., 2007 undertooka field study on ratooningability of spring plantedsugarcane varieties andobserved that maximum caneyield was produced byCPF.237 and HSF.242 ofratoon crop. Jamil et al,200evaluated the ratooningbehavior of 22 candidatesugarcane varieties underNUYT programme. Findingsof theier study revealed thatpromising sugarcane varietiesS95HS.185, S97US.183,S96SP.302, CPHS.35,NSG.311 and Malakand-16were better ratooners. Khanet al., 2007 indicated thatsugarcane variety S96SP.302produced significantlymaximum ratoon cane yieldof 79.39 tons ha-1 against the


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lowest cane yield of 41.94tons ha-1 recorded forNSG.311.The higher caneyield was mainly associatedwith high number of millablecanes, cane height and canegirth. Aslam et al., 2011studied the ratoonperformance of 13 sugarcanevarieties and found thatCPF.246 on account of highernumber of sprouts/plant(1.57), significantly higher100-cane weight of 95.67 kg,highest millable cane count of

112.69 thousand ha-1,maximum cane yield of107.90 tons ha-1 andcomparable CSS of 12.74%against the check varietySPF-234, produced thehighest sugar yield of 13.74tons ha-1. Aslam et al., 2013conducted a field study toexplore ratooning potential ofeight sugarcane varieties anddisclosed that S2003US.114gave significantly higher caneyield of 108.05 tons ha-1

owing to good stubbles

sprouting, higher cane weightand reasonably good millablecane count. The top yielderwas also good in quality andproduced highest sugar yieldof 13.41 tons ha-1. Therefore,the present study wasplanned to assess theratooning performance ofnine elite sugarcane clones incomparison to commercialsugarcane variety CPF.246under southern Punjab agroclimatic conditions.

MATERIALS ANDMETHODS

The field experiment wasconducted under irrigatedconditions during springseason to evaluate theratooning potential of ten elitesugarcane genomes during2013-2014 at SugarcaneResearch Station, Khanpur.The experiment was startedduring 2013 when the springcrop was harvested in the firstweek of February and kept asratoon. The varieties includedin the study wereS2003US.114, S2003US.165,S2003US.824, S2006SP.18,S2006SP.25, S2006US.469,S2006US.658, S2006US.832,S2006US.834 and CPF.246(Standard). The experimentwas laid out in RandomizedComplete Block Design withthree replications. Thesugarcane genotypes weresown by dry method in 120cmapart trenches with a net plotsize of 3.6 × 10 m using aseed rate of 75000 doublebudded setts per hectare.The ratoon crop was fertilizedat the rate of 218-146-146 kgNPK per hectare,respectively. After harvesting

the plant crop, unevenstubbles were cut manuallywith the help of handchopper. Then interculturewas given to control weeds,loosen the soil to help rootdevelopment and thusfacilitate sprouting.Afterwards, whole of P, K and1/3 of N was applied to thecrop followed by irrigation.The remaining 2/3 N wasgiven in two equal splits, 1/3at completing sprouts (60days after harvesting of plantcrop) and 1/3 during thesecond fortnight of May whencrop was earthed up.Meanwhile data on number ofsprouts per plant wererecorded. The data on canedensity, weight, yield andquality were recorded at theharvest during the last weekof December 2013. The datathus recorded were analysedusing Analysis of Variancetechniques and LeastSignificance Difference testwas applied to compare thetreatment means at fivepercent level of probability(Steel and Torrie, 1984).

Sprouts per plantThe sprouting of underground

buds predicts the finalmillable cane stand of ratoonsugarcane crop to a largeextent. The sprouting ofsubterrain stubble eyes ismainly affected by climaticconditions, soil moisture,plant stand and vigor ofprevious sugarcane crop. Thedata presented in table- 1depict that there weresignificant differences in thenumber of sprouts per plantgiven out by the testedsugarcane clones. Thepromising sugarcanegenotype S2003US.658produced the highest numberof sprouts plant-1 (2.79). Itwas matchingly followed byS2003US.469.The lowestnumber of sprouts has beenrecorded for S2006US.832 inthis study. These differencesin the number of sproutsplant-1 may be attributed tothe varied inherent ratooningpotential of the sugarcanevarieties (Rafique et al.,2005).

Cane WeightCane weight is one of themost important yielddetermining characters whichdirectly affects the final


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sweep of sugarcane and isvery much genetic in nature.However, the managementpractices also affect canegirth and weight. It is evidentfrom the respective dataembodied in table- 1 that thetested sugarcane clonesbehaved differently withrespect to individual stalkweight. The new emergingsugarcane genomeS2006US.658 produced theheaviest canes (103.67 kgper 100 canes). It was non-significantly followed byS2006US.114 andCPF.246.The lowest 100-cane weight of 77.67 kg wasrecorded for S2006US.832preceded byS2006SP.18.Thesedifferences in the stalk weightwere probably due to thedifferences in the geneticpotential of tested sugarcanegenotypes. The results arequite in line with the findingsof Aslam et al., 2011 andAslam et al., 2013.

Cane DensityPlant population per unit areais a vital yield component anddirectly affects the finalharvest of the crop. Theestablishment of millablecanes is a reflection ofstubbles sprouts in ratooncrop of sugarcane. The datacompiled in table-1 evincethat the final cane standestablished by testedvarieties varied significantly.The highest number ofmillable canes were producedby S2006US.832 (112.70thousand ha-1) closely

followed by S2006SP.25(109.60 thousand ha-1) andS2006US.658 (104.64thousand ha-1).The thinneststand of 82.21 thousandcanes ha-1 was recorded forS2006US.834.The differentialbehaviour of sugarcanegenotypes for the productionof variable number of millablecanes may be attributed tothe varying inherent potentialof different genotypes toexplore environmentalresources. Similar resultshave also been reported byAslam et al., 2011 and Aslamet al., 2013.

Stripped cane YieldHigh cane yield is the ultimatetarget of every grower whichis the happy blend of theecosystem and the geneticpotential of a variety. Differentvarietal traits like stubblesprouting, cane formation,cane height, girth and percane weight have direct effecton the final ratoon cane yield.It is evident from the datapresented in table- 1 that thetested strains differedsubstantially in final ratooncane yield. The promisingsugarcane varietyS2006US.658 gavesignificantly highest ratooncane yield of 107.63 tons ha-

1. It was comparably followedby S2003US.114 andCPF.246 with a final tonnageof 101.37 and 100.17 perhectare, respectively. Thelowest cane yield of 74.66tons ha-1 has been recordedfor S2006US.834 precededby S2006SP.18.These

differences in the final caneyield of different sugarcanegenotypes may probably bedue to their varied geneticmakeup. Rafique et al.,2005, Jamil et al., 2007, Khanet al., 2007 and Aslam et al.,2011 have also reported thevaried tonnage of ratoonstripped canes for differentgenotypes in theirinvestigations.

Sugar YieldThe ultimate aim of all theefforts being carried out by aresearcher, grower or miller isthe attainment of highertonnage of sweet sugar whichis actually produced in thefield and extracted in thefactory. The scientific dataembodied in table- 1indicated that all thesugarcane clones understudy behaved differentlyfrom one another for theproduction of sugar yield perunit area. The highest sugaryield of 12.86 tons ha-1 wasproduced by the promisingstrain S2006US.658 closelyfollowed by S2003US.114(12.05 tons ha-1). The leastamount of white sugar (8.35tons ha-1) was recorded forS2006US.834.This differentialbehaviour of Sugarcanevarieties/clones to producesugar yield may be attributedto the variability in theirgenetic makeup to explorethe environment to which theywere exposed. Bashir et al.,2007, Aslam et al., 2011 andAslam et al., 2013 have alsoreported the similar results.


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ReferencesAfzal, M., S. Bashir and R.M.A. Khan. 1990. Influence of harvesting dates on ratoon cane crop.Pak. Sugar J., 4(4):23-25.

Akhtar,M., M.Ashraf and M.E.Akhtar.2003.Sugarcane yield gap analysis: Future options forPakistan. Sci.Tech.& Develop.I: 38-48.

Aslam,M.,M.Tauseef,A.R.Zahid and M.J.Anwar.2011.Ratoon performance of sugarcane Varietiesunder southern Punjab conditions. Pak. Sugar J., 26(4):21-24.

Aslam,M.,N.Ahmad, M.Naseem and A.R.Zahid.2013.Exploring ratoon potential of varioussugarcane varieties under southern Punjab conditions. Pak.Sug.J.,28(01):6-8.33.

Bashir,S.,A.A.Chattha,M.Afzal,J.Iqbal and M.Z.Khan.2007.Studies on the ratooning ability ofdifferent sugarcane varieties of different harvesting dates. Proc. 42nd Ann.Con. Pak. Soci.Sug.Tech.27-28 Aug.PP.170-182.

El-Geddawy,I.H., D.G.Darweish, A.A.El-Sherbiny, E.Eldin and A.El-Hady.2002. Effect of rowspacing and number of buds/seed sett on growth characters of ratoon crops for some sugarcanevarieties. Pak. Sugar J., 17(3):7-14.

Jamil,M.,S.Afghan,M.A.Majid and A.Rasool.2007.Ratooning performance of sugarcane varieties.Pak. Sugar J., 22(3):38-47.

Khan,N.,G.Rasool,M.A.Aunjam,K.Masood and A.Bakhsh.2007. Ratoonability of differentSugarcane candidate varieties under agro-ecological conditions of D.I.Khan. Proc. 42nd

Ann.Con.Pak.Soci.Sug.Tech.27-28 Aug.PP.103-9.

Malik,K.B. and M.A.Gurmani.2005.Cane production guide.My choice printing press,Hyderabad.PP.55.

Rafique,M.,A.A.Chattha,A.Jabbar,G.M.Wains,M.U.Chattha,M.Yasin and M.A.Munir. 2005. Proc.40th Ann.Con.Pak.Soci.Sug.Tech.5-7 Sept..PP.195-202.

Steel,R.G.D.and J.H.Torrie.1984. Principles and procedures of Statistics. 2nd Ed.,Mc. Graw HillBook Co., Inc., Tokyo,PP.107-09.

Table-1 Ratoon performance of sugarcane varieties under southern Punjab conditions

Sr.No

Variety SproutsPlant -1

100-caneweight(Kg)

Canedensity000/ha

Cane yield(t/ha)

CCS%

Sugar yield(t/ha)

1 S2003US.114 2.53a 100.67ab 101.09ab 101.37ab 11.89 12.052 S2003US.165 2.68a 90.67abc 98.81ab 89.45cdef 11.95 10.683 S2003US.824 1.84b 87.00abc 97.40ab 84.29efg 11.73 9.894 S2006SP.18 1.94b 81.33bc 96.74ab 78.51fg 11.58 9.305 S2006SP.25 1.67b 89.00abc 109.60a 97.34abcd 11.66 11.356 S2006US.469 2.61a 93.00abc 100.20ab 92.44bcde 12.07 11.157 S2006US.658 2.79a 103.67a 104.64ab 107.63a 11.95 12.868 S2006US.832 1.04c 77.67c 112.70a 86.71def 11.72 10.16

9 S2006US.834 1.56b 91.33abc 82.21b 74.66g 11.19 8.3510 CPF.246 2.59a 97.67abc 102.89ab 100.17abc 11.88 11.90

LSD 0.05 0.39 21.54 22.97 11.07 -- --Values with different letter(s) differ significantly (P=0.05)


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CHARACTER ASSOCIATION AND PATHANALYSIS OF THE PHYSIOLOGICAL

RESPONSES UNDER MOISTURE STRESS INSUGARCANE VARIETIES

Manel Dapanage and Sumangala Bhat*Department of Biotechnology, College of Agriculture, University of Agricultural Sciences, Dharwad

580 005. *Corresponding author’s email: [email protected]

ABSTRACT

Fifty two commercial varieties of sugarcane (Saccharum sp.) were evaluated based on themorpho-physiological responses to moisture stress. All the varieties were planted in pots undergreen house conditions and two replications were subjected to moisture stress by withholdingirrigation after two months of growth. The appearance of the wilting symptoms of each varietyunder stress condition were recorded and analysis of moisture stress related physiological traitssuch as proline, electrical conductivity (EC), relative water content (RWC) and chlorophyll contentwere done 8 days after stress induction under stress and unstressed conditions. RWC (stress),chlorophyll content (stress) and EC (unstressed) showed positive correlation and total contributioneffect on moisture stress tolerance which measured in terms of the days taken for appearance ofwilting symptoms. Therefore, improvement in moisture stress tolerance in sugarcane could beachieved by selecting breeding materials with high EC (unstressed), RWC (stress) and chlorophyllcontent (stress).

Key words: Heritability, Correlation, Path coefficient, Moisture stress, Physiological traits,Sugarcane

INTRODUCTION

Sugarcane is the world’slargest crop by productionand cultivated on an about26.0 million hectares, in morethan 90 countries (FAO,2014). As the majorcontributor of sucrose to theworld, it is being cultivated intropical and subtropicalregions in the world. Due tothe increasing population,demand for the sucrose isincreasing day by day. Theexpansion of cultivation areaand introduction of the highyielding varieties are the wellrecommended solutions tomeet the increasing demand.As a highly water demandingcrop at the initial stages of the

plant growth anddevelopment, expanding thearea under cultivation hasbecome a problem to thesugarcane farmers. Hence,development of high yieldingmoisture stress tolerantcultivars is the best solutionto meet the increasingdemand (Silva et al., 2007).The performance of agenotype in terms ofproductivity is the net result ofgenotype into environmentinteraction. Morphological,physiological changes andbiochemical modifications areresponsible for moisturestress tolerance (Yordanov etal., 2003). Therefore, plantscientists are makingconcerted efforts in identifying

genotypes with higher yieldcoupled with relatively bettermoistures stress tolerance.But the progress in breedingfor moisture stress toleranceis slow due to the quantitativeand temporal variability ofavailable moisture acrossyears, the low genotypicvariance in yield under theseconditions and inherentmethodological difficulties inevaluating component traitstogether with the highlycomplex genetic basis of thischaracter (Turner et al.,2001). Studying the traitswhich contribute to moisturestress tolerance in differentvarieties and their geneticbasis is, therefore,fundamental to enable


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breeders and molecularbiologist to develop newvarieties with improvedmoisture stress tolerance.Further, an understanding ofthe physiological processes inrelation to stress tolerance isessential for identifyingphysiological criteria forscreening the abiotic stresstolerant varieties (Rao, 1994).The knowledge of the relativecontribution of individual traitsto moisture stress tolerancemay be accomplished bycorrelation studies but theidea of direct and indirectcontribution of each traittowards tolerance cannot betraced through correlationstudies (Allard, 1960;Chaubey and Singh, 1994).Therefore, the path coefficientanalysis is utilized to have anidea of direct, indirect andtotal contribution of the traitstowards moisture stresstolerance (Dewey and Lu,1959). Therefore, this studywas conducted to gatherinformation on heritability,correlation and pathcoefficient of physiologicaltraits related to moisturestress tolerance in 52sugarcane varieties.

MATERIALS ANDMETHODS

Fifty two commercialsugarcane varieties wereplanted in the pots filled withsoil (one single bud sett perpot) in four replications. Allpots were irrigated once intwo days and maintainedunder green house condition.After 2 months of planting,water stress was induced bywithholding the irrigation(stress) for two replications of

each variety and remainingwere irrigated as usual(unstressed). Treated plantswere subjected for increasingwater deficiency and date ofappearance of wiltingsymptoms were recordedduring the moisture stressperiod. Leaf samples werecollected 8 days aftermoisture stress induction foranalysis of moisture stressrelated physiological traitssuch as RWC (Silva et al.2008), chlorophyll contentusing SPAD meter (502 Plus,Spectrum Technologies,Plainfield, IL, USA), freeproline content (Bates et al.1973) and electricalconductivity using theelectrical conductivity-meter.The data were analyzedstatistically using standardprotocols (Panse andSukhatme 1954). The simplecorrelation coefficients werecalculated to determine thedirection and magnitude ofassociations among differentcharacters and tested againsttable‘t’ values (Fisher andYates, 1963). Path coefficientanalysis was made on thebasis of correlationcoefficients taking moisturestress tolerance as effect andthe physiological traits relatedto moisture stress as causes.Direct and indirect effects ofcomponent traits on moisturestress tolerance were workedout using path coefficientanalysis (Dewey and Lu,1959).

RESULTS

Appearance of wiltingsymptomsDifferent varieties differed forthe number of days taken for

the appearance of wiltingsymptoms after withholdingirrigation (Table 1). Of the 52,three varieties namely Co94008, CoT 8201 and ISH100 showed wilting symptomsafter 12 days of moisturestress induction and Co 775and Co 99010 varietiesshowed early (4 days) wiltingsymptoms. Rest of thevarieties showed the wiltingsymptoms 6 (11 varieties), 8(27 varieties) and 10 days (9varieties) after stressinduction (Table 1).

Physiological traitsANOVA indicated thesignificant differences in theresponses of varieties tomoisture stress in all thephysiological traits studied(Table 2). The geneticparameters such asgenotypic variance (Vg),phenotypic variance (Vp),genotypic coefficient ofvariation (GCV), phenotypiccoefficient of variation (PCV),heritability (broad sense)(Hbs), for various moisturestress related traits undercontrol and moisture stresswere calculated andpresented in Table 3. Thehighest genotypic (128.95)and phenotypic (130.51)variability were observed forRWC (stress) and minimumgenotypic (0.02856) andphenotypic (0.02860)variability observed for freeproline content (unstressed)of the varieties. Prolinecontent (stress) showed themaximum GCV (125.70) andPCV (125.77) and RWC(unstressed) showed theminimum values for GCV(4.93) and PCV (5.92).Heritability for all traits werehigh (> 60%) and ranged from


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69.34 (RWC under control) to99.89 (proline content understressed condition).

Correlation among thedifferent moisture stressrelated traits.Correlation coefficients weredetermined to know thenature and magnitude ofrelationship existing betweenmoisture stress related traitsand the degrees ofassociation of differentcharacters are presented inTable 4. Correlation amongthe data of appearance ofwilting symptoms and otherphysiological traits related tomoisture stress wereobserved. EC (unstressed(0.352)), RWC (stress,(0.648)) and chlorophyllcontent (stress, (0.427))showed positive correlationwith the date of appearanceof wilting symptom and thepercent reduction of RWC (-0.628) and chlorophyllcontent (-0.675) showednegatively correlations. Themoisture stress related traitsalso showed the significantcorrelations among the traits.Proline content undermoisture stress conditioncorrelated significantly andpositively (0.435) withelectrical conductivity undermoisture stressed condition.Further, RWC under stressedcondition were positively andsignificantly (0.422)correlated with the chlorophyllcontent under stressedcondition.

Path coefficient analysisIn the path analysis,correlation coefficients werepartitioned into direct andindirect effects (Tables 5) andresults showed that RWC

(stress) had highest totalcontribution effect (0.633)including indirect effects(0.772) on time taken forappearance of wiltingsymptoms. Chlorophyllcontent (stress) showedmaximum direct contributioneffect (0.429) towardsmoisture stress tolerance. EC(unstressed) showed positiveindirect (0.127), direct (0.235)and total contribution effecttowards the time taken for theappearance of wiltingsymptoms. Free prolinecontent showed low totalcontribution effect (0.012) dueto high negative indirect effect(-0.154) though it had positivedirect effect (0.167) onappearance of wiltingsymptoms.

DISCUSSION

Moisture stress is a complexprocess connected withalmost all aspects of biology(Bayoumi et al. 2008).Genetic improvement inmoisture stress tolerancemay be achieved by targetingtraits closely associated withmoisture stress tolerance. Anumber of characteristicshave been proposed asindirect selection criteria forgenetic improvement ofmoisture stress tolerance inbreeding programmes(Skinner et al., 1987;Rebettzke et al., 2002).Understanding theassociations between traits isof great importance inbreeding and selectionstudies especially for traitswith low heritability or difficultto measure traits (Bakhsh etal., 2006; Silva et al., 2007).Consideration of genetic

relationships betweenimportant attributes inexploiting genetic populationsthrough breeding anddirected selection is essential,primarily to understand howchanges made by selectingone character may causechanges in others (Jackson,1994; Tyagi and Khan, 2010).This knowledge can be usedwhen devising appropriateselection strategies forparticular traits in asugarcane breedingprogramme (de Sousa-Vieiraand Milligan, 2005). Changesin physiological parametersunder moisture deficit stresswere observed (Levitt, 1972)and the analyses of changesof physiological parameterswere considered as reliablecriteria for the selection ofcultivars (Silva et al., 2007).In this study, moisture stresstolerance was measured interms of days taken to appearthe wilting symptoms. Thevarieties showed wiltingsymptoms 12 days afterstress induction weregrouped as highly tolerantand the varieties whichshowed witling symptoms 4days after stress inductionwere grouped as highlysusceptible (Table 1).Analysis of variance for all thetraits showed significantgenotyping effects indicatinggenetic variability among thevarieties and the possibility ofgenetic improvement in mostof the traits studied throughselection (Punia, 1982; Khanet al., 2004). Significant waterregime x varieties interactionsfor all the traits revealed thatmean performances of thevarieties were influenced bythe water level.


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The GCV and PCV were highunder stress than unstressedcondition for all thecharacters except EC.Bayoumi et al. (2008) alsoreported higher GCV andPCV under stress thanunstressed condition for RWCand proline content in wheatin the experiment carried outin field. Among the fourmoisture stress related traitsstudied, proline content(stress and unstressed) andEC (stress and unstressed)and RWC (stress) showedhigh values of PCV and GCVindicating that these traitscontributed markedly to thetotal variability and possibilityfor further improvement forthese traits. Though, PCVand GCV for chlorophyllcontent (stress andunstressed) were moderateand it is amenable for furtherimprovement. RWC(unstressed) showed lowvalues for PCV and GCVwhich suggest that negligiblecontribution of this trait tototal variability. Further, itindicated that there is a littlescope to improve further formoisture stress tolerance.Less PCV and GCV values inRWC was recorded byPraveen and Patil (1997) inthe experiment conducted tostudy the genetic parametersof twelve Ber cultivars.Difference between GCV andPCV were also found to beless for all the traits indicatingthat these traits were lessaffected by environmentalfluctuations and real effect ofthe genotype (Johnson et al.,1955). Presence of variabilityin the population isprerequisite for selection.However, coefficient ofvariation reveals only the

extent of variability fordifferent characters in thepopulation. The effectivenessof selection for a traitdepends on the relative levelof genetic and non geneticvariation. Hence heritability isa useful parameter, whichconsiders the role of heredityand environment in theexpression of a character(Allard, 1960). Effectiveselection can be achievedonly when additive effects aresubstantial and environmentaleffects are small. In thisstudy, the estimated broadsense heritability values forall the traits under stressedand unstressed conditionswere high and ranged from69.34 to 99.89. In general,high heritability for any traitsindicates that the traits areless subjected toenvironmental influence andsuitable for phenotypicselection. Since, the presentexperiment was conductedunder green house condition,environment influence waslow and high heritabilityvalues (>60) for all the traitswere observed. Among theobserved heritability values,RWC under control conditionshowed lowest heritabilityvalue (69.34). Similar resultfor RWC was recorded byPraveen and Patil (1997) inBer.

Correlations amongphenotypic traits may reflectbiological processes that areof considerable evolutionaryinterest and can be the resultof genetic, functional andphysiological ordevelopmental nature(Soomro et al., 2006; Ulloa,2006). In this study,correlation study was made to

establish the extent ofassociation betweenmorphological andphysiological data. Percentincrease in EC and EC(stress) were not shown anyrelation with the date ofappearance of witlingsymptoms. Due to positivedirect, indirect and totalcontribution effects, EC of avariety (EC control) wassignificantly and positivelycorrelated with the date ofappearance of wiltingsymptoms. Hence, selectionof genotypes withcomparatively high EC mayimprove the tolerancemoisture stress. RWC is akey indicator of the degree ofcell and tissue hydration,which is crucial for optimumphysiological functioning andgrowth processes. Among thephysiological parameters,estimating RWC to representthe plant water balance isconsidered as a fast andcheap tool (González andGonzález-Vilar, 2001). In thisstudy, RWC (stress) waspositively correlated (0.648)with the date of appearanceof wilting symptoms andpercent reduction in RWCwas negatively correlated (-0.628) to the date ofappearance of wiltingsymptoms. Therefore, RWCcan be suggested as a goodindicator of stress tolerance insugarcane. Numerous studieshave shown that maintenanceof relatively high RWC duringmild moisture stress isindicative of moisture stresstolerance (Jamaux et al.,1997, Altinkut et al., 2001,Colom and Vazzana, 2003).RWC was used as a tool todistinguish moisture stresstolerance sugarcane varieties


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by Silva et al. (2007) andGraça et al., (2010) andreported that varieties withhigher percentage in RWC asmoisture stress tolerant andvice versa. Further, pathanalysis revealed that RWC(stress) showed high positivetotal contribution effect(0.633) on the time taken forappearance of wiltingsymptoms due to the highindirect effects (0.772).Decrease in leafphotosynthetic pigmentsunder moisture stress as hasbeen shown by Chaves et al.(2002) in Quercus ilex, byManivannan et al. (2008) insunflower and by Silva et al.(2007, 2011) and O’Neill et al.(2006) in sugarcane.Chlorophyll content(unstressed (-0.424)) andpercent reduction (-0.675) ofchlorophyll content showedsignificant and negativecorrelation with the date ofappearance of wiltingsymptoms. The chlorophyllcontent (stress) waspositively correlated (0.427)to the date of appearance ofwilting symptoms. Hence,chlorophyll content also canbe used as a good indicatorof stress tolerance. Thisresult is in accordance withthe earlier reports(Jangpromma et al., 2010;Silva et al., 2007; 2011),which reported that themoisture stress tolerantsugarcane cultivars havehigher level of chlorophyllunder moisture stress thandrought susceptible cultivars.Further, path coefficientanalysis showed thatchlorophyll content (stress)showed high positive totaleffect (0.429) including high

direct effect (0.434) on timetaken for appearance ofwitling symptoms. Butchlorophyll content(unstressed) have negativetotal effect on time taken forappearance of witlingsymptom due to highnegative direct effect (-0.399).Proline is known to beinvolved in plant response tovarious environmentalstresses, including moisturestress. Proline accumulationunder moisture stress hasbeen found in plant (Johari-Pireivatlou, 2010, Mafakheriet al., 2010, Vajrabhaya et al.,2001, Parida et al., 2008,Munawarti et al., 2013). Inthe present study also all thevarieties showed increase inproline content undermoisture stress conditioncompared to normalcondition. The appearance ofwilting symptoms and theproline content of thevarieties under control andstressed conditions did notshow any significant relation.Hence, the proline contentmay not be a good indicatorof stress tolerance in thesugarcane varieties includedin this study. Hanson et al.(1979) working with Hordeumvulgare L., also suggestedthat proline accumulation wasof no practical use inbreeding, even though theyfound a heritable componentto this trait. Further, Ceh et al.(2009) also found nocorrelation between prolinecontent and moisture stress-resistance in Hops (Humuluslupulus L.) and Ilahi andDorffling (1982) found thatmoisture stress-susceptiblecultivars of Zea mays hadhigher proline content than

moisture stress-resistantones. On the contrary, Ma etal. (2004), Bayoumi et al.(2008) and Naser et al.(2010) suggested that prolineaccumulation could be usedas a marker for moisturestress tolerance. Differencesin the role of proline withrespect to moisture stresstolerance in sugarcane havealso been reported. Rao andAsokan (1978) found thatmoisture stress resistantvarieties of sugarcaneaccumulated more prolinethan susceptible ones andsuggested that prolineaccumulation could be usedas an index of moisture stresstolerance, whereas Zhao etal. (2010) suggested thatproline was not a sensitivewater stress indicator insugarcane. Path coefficientanalysis for proline alsorevealed low total effects ontime taken to appearance ofwilting symptoms. Therefore,proline content may not be agood indicator of stresstolerance.This study revealedthat moisture stress toleranceis associated with its variouscomponents genetically andphenotypically in variousmagnitudes. Further, thestudy has indicated thecontribution and magnitude ofthe correlations amongmoisture stress tolerancerelated physiological traits,their heritability and genotype× environment interactionsthat could be encounteredwithin the sugarcanebreeding programme anddemonstrated differentialresponses of differentsugarcane varieties tomoisture stress conditions.


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Table 1: The varieties and the number of days taken for appearance of wilting symptomsunder moisture stress

Days afterwithholdingirrigation

No ofvarietiesshowedwilting

Name of the variety Tolerance group

4 2 Co 775, Co 99010 Susceptible

6 11 CoM 88121, Co 98013, Co 720, Co 7804, Co 99012, Co 86011,CoC 92061, Co 8371, Co 7527, Co 92020, Co 85246

Moderatelysusceptible

8 27

Co 1163, Co 419, CoJn 94-8, Co 7704, Madumathii, CoJ 83, Co8213, Co 86002, Co 7602, CoSNK 03044, CoSNK 03632, Co403, Co 86250, CoM265, Co 94012, Cp 5268, CoSNK 05104,Co 85002, Co 62175, CoSNK 05103, Co 92005, Co 85004, Co740, Co 99008, Co 1148, Co 86032, CoC 671

Moderatelytolerant

10 9 Co 7405, Co 88025, Ms 68 47, Co 7424, Madhuri, Co 86249, Co2001-15, Co 93009, Co 99004

Tolerant

12 3 CoT 8201, ISH 100, Co 94008 Highly tolerant

Table 2: ANOVA for few moisture stress related parameters among 52 sugarcane varieties

Source of Variance DF MSSProline EC RWC Chlorophyll

Replication 1 0.01 0.00 0.51 6.78Water regimes 1 136.85** 9.99** 71476.89** 3546.07**Error(a) 1 0.002 0.00 55.47 3.25Variety 51 5.06** 0.090** 166.79** 71.49**Water regimes X varieties 51 12.75** 0.36** 1705.92** 186.96**Error (b) 102 0.0027 0.0004 4.8481 0.9457SEM 0.026 0.010 1.101 0.486

** - Significant at 0.01%

Table 3: Estimates of genetic parameters for moisture stress related traits among 52sugarcane varietiesVg = genotypic variance, Vp = phenotypic variance, GCV = genotypic coefficient of variation,PCV = phenotypic coefficient of variation, H (bs) = heritability (broad sense)Trait Treatment Variance Coefficient of variation (%) H(bs)

Vg Vp GCV PCVProline Unstressed 0.02856 0.0286 107.62 107.69 99.87

Stress 5.0 5.01 125.70 125.77 99.89EC Unstressed 0.022 0.023 26.71 26.94 98.31

Stress 0.0637 0.0641 25.29 25.39 98.25RWC Unstressed 18.41 26.54 4.93 5.92 69.34

Stress 128.95 130.51 22.75 22.89 98.81Chlorophyll Unstressed 27.89 29.01 13.48 13.75 96.15

Stress 29.88 30.66 17.69 17.91 97.47


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Table 4: Correlation coefficients values for date of wilting and moisture stress relatedparametersC – Unstressed condition

Cproline

Dproline

Inc/proline

CEC

DEC

Inc.EC

CRWC

DRWC

Redu-ctionRWC

CSPAD

DSPAD

ReductionSPAD

Wiltingdate

C proline 1

D proline 0.035 1Increaseproline

-0.358** 0.438** 1

C EC 0.134 -0.109 -0.152 1

D EC -0.03 0.435** 0.465** 0.06 1IncreaseEC

-0.146 0.385** 0.537** -0.676** 0.653** 1

C RWC -0.09 0.074 0.114 0.046 0.156 0.051 1

D RWC 0.158 -0.208 -0.043 0.357** 0.113 -0.225 0.135 1ReductionRWC

-0.176 0.224 0.071 -0.344* -0.079 0.235 0.101 -0.971** 1

C SPAD 0.184 -0.052 -0.162 -0.318* -0.036 0.208 0.04 -0.287* 0.296* 1

D SPAD 0.255 -0.157 -0.178 0.131 0.016 -0.129 0.038 0.422** -0.403** 0.219 1ReductionSPAD -0.097 0.139 0.049 -0.333* -0.033 0.256 -0.017 -0.584** 0.572** 0.446**

-0.763** 1

Wiltingdate

0.025 -0.02 -0.01 0.352* 0.152 -0.182 0.073 0.648** -0.628**-0.424**

0.427**-0.675**

1

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).D - Moisture stress conditionEC – Electrical conductivityRWC – Relative water contentSPAD – Chlorophyll content in SPAD units

Table 5: Path coefficients of physiological traits related to moisture stress tolerance.Character Total indirect

effectDirect effect Total effect

C proline 0.151 -0.115 0.036D proline -0.154 0.167 0.012C EC 0.127 0.235 0.362D EC 0.232 -0.088 0.144C RWC -0.068 0.121 0.052D RWC 0.772 -0.139 0.633C Chlorophyll content 0.098 -0.399 -0.301D Chlorophyll content -0.005 0.434 0.429C – Under unstressed conditionD – Under moisture stress condition


EFFECT OF SOWING AND HARVESTING TIME ONTHE YIELD AND SUGAR RECOVERY OF SUGAR

BEET UNDER D. I. KHAN CONDITIONKarim Bakhsh Malik, Soban Qureshi, Asif Imran Shah and Muhammad Zubai

ABSTRACT

To ascertain the optimum time of planting and harvesting under D.I. Khan conditions, studies wereconducted at the Research Farm of Al Moiz Industries, D.I. Khan. The three years studies, startingfrom 2008-09 to 2010-2011, included five planting dates (1st October, 15th October, 1st November,15th November and 1st December) and five harvesting dates (1st April, 15th April, 1st May, 15th Mayand 1st June). The experiment was laid out in split plot design, placing sowing dates in main plot whileharvesting dates as sub plots superimposed on main plots; all randomly distributed in four replications.

The data indicate that October planting with May harvesting gave significantly the highest yields around 85– 90 tha-1 with sugar recoveries of 11,50 – 11.80%’. Compared to October, Sowing the crop on 1st Nov,15th Nov. and 1st Dec. gave a yield reduction of 10.43%, 25.27% and 39.25%, respectively.Sowing the crop on 1st Nov, 15th Nov. and 1st Dec. gave a yield reduction of 10.43%, 25.27% and39.25%, respectively. On the other hand harvesting on 1st April and 15th April reduced yield by36.74% and 25-00%, respectively, while harvesting the crop on 1st June also dropped the yield by5.50%. Compared to the month of May, harvesting on 1st April and 15th April reduced sugarrecovery by 14.81% and 9.94%. To promote better yields and recoveries longer growth periodshould be preferred with a condition to avoid sowing beyond October and harvesting beyond May.

INTRODUCTION

Sugar beet is a crop oftemperate regions and isplanted as summer crop,however under sub tropicaland continental conditions thecrop is planted as a wintercrop before the onset ofsevere cold. The temperatureis the most important factorfor managing its sowing,growth and harvestingoperations. Under temperateconditions optimum day timetemperature for first 90 daysof plant growth is 16 to 27oC;after 90 days of emergence toharvest, bright sunny days

are required with 18o to 27oCfollowed by night timetemperature of 5 to 100C.These conditions helpmaximize yield and quality insugar beet.(Cattanack,Dexter and Oplinger), 1991.According to Terry (1970), theoptimum temperature forplant growth is about 240 C,and 17-200 C for root growth.Cool weather withtemperature around 150 Cfavors sugar accumulation inthe roots, while temperatureabove 300C retard sugaraccumulation. Sugar in beetroot remains at high level at140 C to slightly mild

temperature, but at thetemperature above 300Caccumulation of sugar inroots and sucrose percentagedrastically decline(Ustimenko, 1983). Regionswith long day length are mostsuitable for plant growth andyields. In Pakistan, sugarbeet cultivation is yetconfined in Mardan,Peshawar and D, J, KhanDistricts. Sugar beet is grownas a winter crop and sowingis done before winter to availof conditions favorable forseed germination and earlyplant growth. Sowing andharvesting dates are one of


the most importantmanagement factors thataffect plant growth, yield andquality of beet roots. Anumber of studies have beencarried out on its planting andharvesting times. Aminetal(1989) recorded beet rootyield of 68.49 t ha-1 byplanting sugar beet on 1st

Oct. followed by a gradualreduction in yield by delayedplanting of beet on 15th Oct.(64.80 t ha-1), 1st Nov.(48.25 tha-1) and 15th Nov.(46.78 t ha-

1). Late planting also showedcorresponding reduction insugar yield. Earlier studies byAmin etal(1987) and Amin(1988) also proved thatsowing sugar beet in Oct.gave higher yield than lateplanting. Higher yield inearlier planting was attributedto a longer period of favorableenvironments for plantemergence, and root growthand development than its lateplanting. In Mardan, sugarbeet root yield of 60, 55, 45and 35 tons per hectare wasreported from 9, 8, 7 and 6months crop duration,respectively. To harvest areasonable yield it wasrecommended that beet cropshould avail of longer stay inthe field.(Jan, 1964).Studies on planting sugarbeet on 1st of Sept., Oct. andNov. revealed that Oct.planting gave the highestyield of beet roots than earlieror late planting (Leilah etal,2005). In Egypt, studies onplanting sugar beet on 1st and15th of Sept., Oct. and Nov.revealed higher beet rootyield from 15th Oct. to 15th

Nov.(Rafay, 2012). It was

observed that very earlyplanting induce more gaps inplant stand. Earlier sowingprolong growth period whichis one of the most crucialyield determining factors(Oleson, etal, 1990). Pooryield from late planting wasdue to availability of limitedgrowth period and lowtemperature that suppressgrowth. Short vegetationperiod in the late sowingreduced root yield and sugarcontents ((Sogut and Arioglu,2004). From the cropharvested at 180, 195 and210 days after sowing(7-12Oct), the later harvestingresulted in greater yield ofbeet roots and sugar contentsthan earlier harvesting(Hussein etal, (2012). Theplanting and harvesting timehas direct impact on overallgrowth period of the crop thataffected the yield of sugar beet.Sugar beet avails six to eightmonths of growing period inPakistan. Considering very coldspell soon after sowing andvery hot weather at harvesting,we are left with very short timefor sowing and harvestingoperations. Studies have beenundertaking to ascertain verysuitable time of planting andharvesting for getting goodyield and sugar recovery.

MATERIAL ANDMETHODSThe three years projectstudy(2008-09 to 2010 –2011), financially sponsoredby the Pakistan AgriculturalResearch Council,Islamabad, was conducted atthe research farm of Al-Moizindustries, Dera Ismail Khan,

over a three years projectduration of 2008-09 to 2010 -2011. The study included fiveplanting dates, viz: 1st

October, 15th October, 1st

November, 15th Novemberand 1st December with fiveharvesting dates, viz: 1st April,15th April, 1st May, 15th Mayand 1st June. Planting wasdone in split plot designplacing planting time in mainplot and harvestings time assub plot super imposed onthe main ; randomly laid outin four replications. Each subplot measured 3.75 m;covering five rows of 6 meterslength each having row toplants space of 75 cm x 20cm. The land was deepprepared and well pulverizedto attain good tilth. Two bagsof DAP and one bag of SOPwere applied after seedbedpreparation prior to planting.Planting was done with atractor operated mechanicalplanter, followed by irrigation.As the field came in moiststage it was sprayed with aherbicide “Dual Gold”. Onlatter stage weeds werecontrolled by manualweeding. The 75 Kg of Ureawas applied in two splitdoses, first one four weeksafter sowing and the last doseapplied eight weeks ofsowing. The irrigations wereapplied as and when needed.At the time of harvesting fivebeet roots of almost uniformsize were picked from eachplot and sent to the sugarmills laboratory for sugaranalysis tests. Beet roots ofcentral three rows of eachplot were manually dug,leaves with crown section


were cleaned off and beetroots weighed for beet rootyield data. The beet root yieldand recovery data were gotstatistically analyzed and arediscussed hereunder.

RESULTSBeet root yieldThe data on beet root yieldsas affected by various sowingand harvesting dates for theperiod 2008-09, 2009-10 and2010-11 are presented inTable-1. Sowing dates. Thedata show significantdifferences in the means ofcane yield, during theexperimental periods. During2008 the beet planted on 15th

October gave the highestyield of 80.95 t ha-1. The lowyield during 1st October wasdue to infestation ofpest(Grey weevil) that badlyaffected crop stand of thecrop. The planting donebeyond 15th October affectedthe crop yields adversely. Thelowest yields of 59.25 and50.10 t ha-1 were observedduring 15th Nov. and 1st Dec.,respectively.During 2009-10and 2010-11 periods, Oct.planting gave the highestyields of beet roots perhectare and the means weresignificantly different fromNov. and Dec. sowings.However, yields of 1st and15th Oct. were statisticallyalike. Compared to Oct.planting sugar beet on 1st

Nov., 15th Nov. and 1st Dec.showed a large reduction inyield which was to the tune of10.43%, 25.26% and 39.25%,respectively. According to

Oleson etal(1990), earlysowing is the crucial yielddetermining factor thatprolong growth to attain goodgrowth.Harvesting dates. The datain Table 1 show significantdifferences in the means ofcane yield recorded duringthe three years ofexperimental period, During2008-09, harvesting the cropon 15th May and the latterdates showed non significantdifferences in their means.The lowest yields wereobserved on 1st April with alittle rise on 15th April harvest.During 2010-11, harvestingon 1st May gave the highestyield of beet roots (90.64 t ha-

1) and its means weresignificantly different from restof the dates., followed by 15th

May and 1st June. Harvestingon 1st April recorded thelowest yield (33.09 t ha-1),with considerable yieldincrease on April 15.Unusually low yield of Aprilmonth is due to severe attackof grey weevils on a few plotsthat the plots had to be re-sown. During 2010 – 2011interaction showed significantdifferences wherein Octoberplanting with 15th Mayharvesting gave the highestyield of 105 – 107 t ha-1.Sugar RecoveryThe data in Table-2 showsignificant differences inmeans of both sowing andharvesting dates during theperiod 2009-10 and 2010-2011. However, during 2008 -09, means were notsignificantly different.

Sowing dates. The Oct.planting has shown thehighest recoveries, and themeans were significantlydifferent from Nov. and Dec.sowing during both the years.Harvesting dates.During 2009-10 the cropharvested on 1st May gavethe highest sugar contents of11.11% and was significantlydifferent from rest of theharvesting dates. The 15th

May was next best inrecovery, significantlyfollowed by 1st June. Sugarbeet harvested in April hasshown the lowestrecoveries.During 2010-11harvesting in May and Junegave equally good recoveries,significantly followed by Aprilharvesting. In this yearweather was not much harshto show wide variation insugar contents during Mayand June periods.Mean beet root yield andsugar recoveriesThe data in Table-3 indicatesthat October planting andMay harvesting have yielded76.86 and 75.48 tons beetroot per hectare, respectively.The Sugar recovery data inTable-4 indicate that highestsugar recoveries of 10.87%and11.06% were obtainedfrom October sowing andMay harvesting, respectively.With subsequent delay insowing beyond October on 1st

Nov, 15th Nov and 1st Dec.,sugar contents were reducedto 10.33%, 10.10% and9.93%, respectively The interaction of sowing withharvesting indicate that Oct.sowing with May harvesting


yielded the highest beet rootweight of 85-90 tha-1 with thehighest sugar contents of11.58 – 11.81%.

DiscussionThe planting and harvestingdates have most conspicuousrole in successful cropproduction. The importance ofplanting time is with respectto providing conditionsfavorable for germination,initial crop stand and growthand development of beet reetplants. On the other sideharvesting time regulatematurity period so as toharvest maximum sugar yieldper unit area. Both plantingand harvesting times alsodetermine the growth periodoptimally required for sugarbeet root growth anddevelopment. In view of theresults discussed in Table-3the October planting, givinghigher beet root yield, seemto be the ideal period ofplanting sugar beet. Sowingthe crop on 1st Nov., 15th Nov.and 1st Dec. gave a yieldreduction of 10.43%, 25.27%and 39.25%, respectively.This clearly indicate that toget economic yields thesowing should be completedin the month of October. Onthe other hand compared toMay, harvesting on 1st Apriland 15th April reduced yieldby 36.74% and 25-00%,respectively, while harvestingthe crop on 1st June alsodropped the yield by 5.50%. Itcould be concluded that beetroot yield is gradually reducedwith any delay in plantingbeyond Oct. Similarlycompared to May, harvesting

in April and June result inmarked reduction in yield. Toobtain better yields longercrop cycles has also beenrecommended by Jan (1964).With respect to sugarcontents, subsequent delay insowing beyond October on 1st

Nov, 15th Nov and 1st Dec.,showed sugar reduction by4.96%, 7.08% and 9.93%respectively. As forharvesting, the month of Mayappear to be the mostsuitable period for harvestingsugar beet to get the highestaverage sugar contents(11.06%). Compared to themonth of May, harvesting on1st April and 15th Aprilreduced sugar recovery by14.81% and 9.94%. The datafurther indicate that increasein beet root yield and sugarcontents are greatlycorrelated with overall growthperiod of the crop. Therelationship of growthduration with beet root yieldand sugar recoveries areshown in Table-5. The dataindicate that Oct. sowing withMay harvesting yielded thehighest beet root weight of85-90 tha-1 with the highestsugar contents of 11.58 –11.81%. These yield rangeswere obtained from thegrowth duration of 197 – 227days. On the other hand Nov.– Dec. sowing with April 1- 15harvesting gave yield rangesof only 28 – 45 t ha-1 Thesetrends were observed fromshorter growth duration of136 – 166 days. Infect Nov.and Dec. planting while slowsdown the growth due to lowtemperature, reduced thegrowth period, while June

harvesting has physiologicaleffect of beet root rotting. Thephilosophy of higher yieldfrom Oct. planting and Mayharvesting is that the Octoberplanted crops get wellestablished to attain goodgrowth before onset of winter.It is important to obtain fullleaf cover as early aspossible during growth toharvest higher yield of sugarbeet. This crops cycle alsoavails of longer growth periodthan Nov. & Dec. planted andApril harvested crop. Thedata in Table-5 indicate thatboth crop yields and qualityare mostly associated withlonger growth period. Thusthe data are in conformitywith findings of Hussein et al(2012). Though Oct. sowingwith June harvesting avail oflonger growth period but thecrop is subject to scorchingheat and fermentation due tohigh temperature whichresults in severe yield andquality losses. Aprilharvesting have alwaysshown drastic reduction inbeet yield and sugarrecoveries. It is becauseafter termination of cold spellin February crop does notavail of longer period ofproper root development andsugar synthesis andaccumulation. Yieldreduction from shortvegetation period has alsobeen reported byAsiogler(200). Nevertheless,some early maturingvarieties may be selected toharvest better sugar yieldsper unit area.


Temperature effectsThe mean monthlytemperature data of D.I. Khan(Table-6) indicate that themonth of October offers mostsuitable weather conditionsfor sowing sugar beet. Withdelay in sowing to Nov. andthen Dec. temperaturesgradually drops too low for itsgermination. December,January and even February

are not even ideal for its plantgrowth; In severe cold shocksgrowth remain suppressed.Proper root formation takesstart after mid February andthereafter period closes tomaturity by mid April. In orderto have a vigorous crop standsowing should be completedby mid October, and theplants should have welldeveloped leaves beforeonset of winter in November.

As for harvesting Aprilappears to be the best in D.I.Khan while the month of Mayshow marginal temperatureranges for harvesting ahealthy crop; the month ofJune has too hightemperatures. To harvestgood sugar yields, sugar beetvarieties may be searchedout to initiate harvesting inApril and vacate the fieldswith the termination of May.

Table-1 Effect of different planting and harvesting dates on the yield of sugar beet during2008 – 2011 period.

2008-09 Harvesting time - Beet root yield t ha-1Planting time 1st April 15-Apr 1st May 15-May 1st June Mean LSD05

1st Oct. 59.18 69.25 73.55 75.33 68.95 69.25 b

9.70

15-Oct 70.63 75.33 88.75 86.05 83.95 80.95 a1st Nov. 61.25 66.88 68.45 79.18 69.58 69.33 b15-Nov 47.30 51.75 62.20 74.48 60.63 59.25 c1st Dec. 33.85 46.63 57.60 60.00 52.40 50.10 c

Mean yield 54.45 c 61.98 bc 70.10 a 75.00 a 67.10 abLSD05 7.98

2009-10 Harvesting time - Beet root yield t ha-1Planting

time 1st April 15-Apr 1st May 15-May 1st June Mean LSD05

1st Oct. 65.75 75.45 75.30 85.95 78.08 76.10 a

6.11

15-Oct 71.90 67.28 73.05 92.93 78.63 76.75 a1st Nov. 59.38 66.85 62.63 80.23 69.80 67.78 b15-Nov 41.05 46.40 45.65 63.55 51.38 49.60 c1st Dec. 31.00 35.40 35.80 48.85 41.83 38.58 d

Mean yield 53.80c 58.28bc 58.48bc 74.30a 63.95bLSD05 6.06

2010-11 Harvesting time - Beet root yield t ha-1

Planting time 1st April 15-Apr 1st May 15-May 1st June Meanss LSD05

1st Oct. 44.64 k 68.95ghi 107.54a 95.08bcd 84.80def 80.20a

5.05

15-Oct. 45.50 k 59.24ij 105.23ab 92.87cde 86.79def 77.85a1st Nov. 32.45 l 50.17jk 98.18abc 82.62ef 85.30def 69.67b15-Nov. 33.07mn 39.46kl 78.85fg 84.39def 81.43f 61.45c1st Dec. 19.18 n 31.04imn 63.30i 66.60hi 76.41fgh 51.40d

Mean yield 33.09 d 49.72 c 90.64a 84.33B 82.94b5.05

LSD05 6.521(interaction


Table- 2 Effect of different planting and harvesting dates on the sugar recovery of sugar beetduring 2008 – 2011 periods.2008-09 Harvesting time – sugar recovery %

Planting time 1st April 15-Apr 1st May 15-May 1st June Mean LSD05

1st Oct. 10.22 10.85 11.25 12.00 9.46 10.76

NS

15-Oct. 10.02 10.90 11.18 11.95 9.45 10.781st Nov. 9.57 9.75 10.53 11.70 10.29 10.3715-Nov. 9.95 10.70 10.86 11.68 10.59 10.761st Dec. 9.47 10.40 10.53 11.53 10.64 10.51

Mean yield 9.85 10.42 10.87 11.77 10.17LSD05 NS2009-10 Harvesting time - sugar recovery %


1st Oct. 9.74 9.94 11.84 10.69 10.74 10.59 a

0.297

15-Oct 9.50 9.88 11.56 11.08 10.43 10.49 a1st Nov. 9.01 9.66 11.24 10.53 10.35 10.16 b15-Nov 8.54 9.39 10.79 10.79 10.13 9.93 b1st Dec. 7.90 9.25 10.11 10.36 10.34 9.59 c

Mean yield 8.94e 9.62d 11.11a 10.69b 10.40c

LSD05 0.2662010-11 Harvesting time - sugar recovery %


1st Oct. 10.50 11.08 12.35 12.05 11.30 11.45 a

0.265

15-Oct 10.35 10.50 12.35 11.88 10.93 11.20 a1st Nov. 9.98 9.55 10.92 11.98 9.88 10.28 b15-Nov 9.68 9.38 9.85 9.88 10.58 9.87 b1st Dec. 9.18 8.23 9.00 9.28 10.70 9.25 cMean yield 9.94b 9.75b 10.90a 10.83a 10.68a

LSD05 0.265

Table-3 Mean yield of sugar beet for the period 2008-09 to 2010-2011.Harvesting time - Mean yield – t ha-1

Planting time 1st April 15-Apr 1st May 15-May 1st June Mean Mean variation %

1st Oct. 56.62 71.21 85.45 85.47 77.28 75.1915-Oct 62.67 67.23 89.00 90.64 83.11 78.531st Nov. 50.89 61.28 76.44 80.67 74.90 68.8415-Nov 40.45 45.89 62.26 74.14 64.48 57.441st Dec. 28.22 37.66 52.23 58.48 56.87 46.69Mean yield 47.75 56.65 73.08 77.88 71.33Mean variation %


Table-4 Mean sugar recoveries of sugar beet for the period 2008-09 to 2010-2011.Harvesting time

Planting time 1st April 15-Apr 1st May 15-May 1st June MeanMean

variation %1st Oct. 10.15 10.62 11.81 11.58 10.50 10.9315-Oct 9.96 10.43 11.70 11.64 10.40 10.821st Nov. 9.52 9.65 10.91 11.40 10.17 10.3315-Nov 9.39 9.82 10.50 10.78 10.43 10.101st Dec. 8.85 9.29 9.88 10.39 10.56 9.79Mean yield 9.57 9.96 10.96 11.16 10.41

LSD05

Table-5a. Mean yield of beet roots t ha-1 in relation to various growth periods - days

Plantingtime

1st April 15-Apr 1st May 15-May 1st June Mean

yield Days yield Days yield Day

s yield Days yield Days

1st Oct. 56.62 182 71.21 197 85.45 212 85.47 227 77.28 243 75.19

15-Oct 62.67 166 67.23 182 89.00 197 90.64 212 83.11 227 78.53

1st Nov. 50.89 151 61.28 166 76.44 182 80.67 197 74.90 212 68.84

15-Nov 40.45 136 45.89 151 62.26 166 74.14 182 64.48 197 57.44

1st Dec. 28.22 121 37.66 136 52.23 151 58.48 166 56.87 182 46.69

Mean 47.75 56.65 73.08 77.88 71.33

Table- 5b Mean sugar recoveries in relation to various growth periods - days

Plantingtime

1st April 15-Apr 1st May 15-May 1st June Mean

Days

Days Days Day

sDay

s

1st Oct. 10.15 182 10.62 197 11.81 212 11.58 227 10.50 243 10.93

15-Oct 9.96 166 10.43 182 11.70 197 11.64 212 10.40 227 10.82

1st Nov. 9.52 151 9.65 166 10.91 182 11.40 197 10.17 212 10.33

15-Nov 9.39 136 9.82 151 10.50 166 10.78 182 10.43 197 10.10

1st Dec. 8.85 121 9.29 136 9.88 151 10.39 166 10.56 182 9.79

Mean 9.57 9.96 10.96 11.16 10,41


Table-6. Mean monthly temperature and precipitation during growth period of sugar beet cropin D.I. Khan

Month Temperature Co-mean daily Precipitation “mm”High Low MeanSeptember 36.7 23.8 30.2 17.6October 33.4 17.3 25.3 4.8November 27.7 10.5 19.1 2.1December 21.9 5.3 13.6 10.4January 20.3 4.2 12.2 10.0February 22.1 7.3 14.7 17.5March 26.9 12.9 19.9 34.8April 33.5 18.5 26.0 21.7May 38.7 23.2 30.9 17.2June 41.5 26.8 34.2 14.4

References

Amin, M. G. Ahmed and M. Khan (1982). Sugar beet root yield and quality as affected by differentplanting dates. Pak. Soc. Sugar Tech. 169-173.

Amin, M.; A. Khan and D. Khan (1989). Effect of dates of sowing on yield and quality of sugar beet.Pak. J. Agric. Res. 10:30-33.

Amin. M. (1987) Effect of different growth periods on the root yield and quality of sugar beet. Sarhad j.Agric. Res. 3:1-8.

Cattanack, A.W.,Dexter, A.G. and E.S.Oplinger (1991). Sugarbeet: Alternate Field Crops Manual.

Hussein, M.A.; Al-Sayed; A.R. Usama; A. Abdel-Razzak; M. S. Hazem; M.. Sarhan; F. Haya. And S.Fateh (2012). Effect of harvesting dates on yield and quality of sugar beet varieties. Australian JBasic and Applied Sci. 6(9): 525-529.

Jan, O. (1964). Sugar beet cultivation in Peshawar valley (Bulletin). Sugarcane Res. Station, Mardan,NWFP.

Leilah, A.A.; M.A. Badawi; E.M. Said: M.H, Ghonema and M.A.E. Abdon (2005).Effect of plantingdates, plant population and nitrogen fertilization on sugar beet production under the newlyreclaimed sandy soils in Egypt.. Scientific J. King Faisal Univ.(Basic and Applied Sciences)6(1):95-109

Rafay, Y.A. (2010). Root yield and quality traits of three sugar beet varieties in relation to sowing datesand stand densities. World J. Agri. Sci. 6(5): 589-594.

Sogut, T. and H. Arioglu (2004). Plant density and sowing dates effect on sugar beet yield andquality. Journ.Agronomy 3(3): 215-218.

Terry,N (1970). Developmental Physiology of the Sugar beet. J. Exp. Bot. 21(67): 477-796.

Ustimenko- Baumoveky, G.V, (1983). Plant growing in the tropics and sub tropics. Translated from

Russian, by M K.Viktorova. Mir Publishers Moscow, PP 245-256


SUGAR AND ADDICTIONWorld Sugar Research Organization (WSRO) Position Statements

Sugar and Health: Judgingthe EvidenceWritten September 2011

BackgroundEvidence for a role of sugar inhealth derives fromepidemiological andexperimental studies.

Epidemiology attempts toexplain disease distributionswithin populations byobserving any associationbetween disease andexposure to some possiblecausative agent, such as diet.Experimental (or intervention)studies attempt to manipulateexposure under morecontrolled conditions andmeasure the effect. Bothtypes of studies have theirlimitations. However,evidence from interventionstudies is generallyconsidered more reliable thanthat from observationalstudies.

Epidemiological studies ofdietEpidemiological studies ofdiet fall into a number of sub-divisions. The simplest typeof study involves observingthe average diet and diseaseexperience of a populationand comparing it with theobserved diet and disease ofother populations. These arecalled “ecological studies”.Such studies usually usenational estimates of averagefood intake per person torepresent nutrient intake.

These nutrient estimates mayarise from individual foodconsumption surveys for arepresentative sample of thepopulation.

However, this data is notavailable in all countries, inwhich case, researchers mayoften use data on food supplyto the population, togetherwith an estimate of waste.

Such estimates of dietaryintake are far fromsatisfactory in forming a clearpicture of nutrient intake anddisease - see ‘GeneralLimitations of EpidemiologicalStudies’ and ‘DietaryAssessment’ below.Ecological studies aregenerally considered toprovide the weakest evidenceconcerning associationsbetween nutrition anddisease.However, such studies allowan inexpensive preliminaryexamination of hypotheses inadvance of more valid, andusually more expensive,investigations.

A second type of study in thisgroup is the “case controlstudy”. In such studies, foodintake is estimated, usuallyretrospectively, in individualsdiagnosed with a specificdisease, and compared to anappropriate disease-freecontrol group. Case controlstudies may suffer fromdifficulties in identifying anappropriate control group.

The reliability of patients’recollection of their dietmonths or years prior todiagnosis may not be reliable.In addition, patients burdenedwith disease may be biasedto selectively recall certainaspects of their diets prior totheir diagnosis. In“prospective cohort studies”,the diet of individuals, usuallyassumed healthy, isestimated and the cohort isfollowed for a period of time,which is often years.

The participating subjects areusually chosen for theircomparability in mostrespects other than theirpotential exposure to aparticular dietary component.Comparisons are then madebetween the diets of thosethat subsequently developeda disease or health outcomeversus those that did not.

Large numbers of subjectsare often involved inprospective studies, whichtherefore usually employfood-frequency 2questionnaires or 24-h dietaryrecall to estimate nutrientintake. In some prospectivestudies, dietary intake isassessed part-way throughthe study in addition to thebaseline in an attempt toimprove accuracy.

“Cross sectional studies”examine the associationbetween disease andexposure at a specific point in


time. This design suffers fromthe danger that people whohave developed a disease orhealth condition may havechanged their diet.Consequently, their diet at thetime it is estimated may notcorrespond to their precedingdiet.

General limitations ofepidemiological studies.Epidemiological studydesigns share a number oflimitations. Since they areobservational in nature, theycan only provide a correlationbetween disease outcomeand a dietary component orpattern. The intake of anindividual diagnosed with adisease or health outcomemay not correspond to thepopulation average.

Correlations do not provecausality and shouldpreferably only be employedto direct further experimentalstudies.

All observational studies aresubject to the risk ofconfounding. That is, thepresence of other variableswhich are they themselvesrelated to the exposure andthe outcome. These othervariables may either not havebeen recognised by theresearchers or may not havebeen measured for somepractical reason.

As a result, a correlationbetween some aspect of dietand a disease outcome maybe misleading. If theconfounder is known andmeasured, then a correction

factor is applied to allow amore accurate estimate of thedegree of influence from aparticular aspect of diet.However, measurement ofthese other influences is alsosubject to error, which thenintroduces furtherinaccuracies into the finalestimate of the importance ofdiet.

Errors may also arise fromthe use of inappropriatestatistical tests. In moststudies of diet, a largenumber of different dietarycomponents and patterns areexamined for correlations withdisease outcome. Tests arethen applied to estimatewhether a correlation that isobserved could have arisenby chance.

These statistical tests need tomake allowance for thenumber of correlations beingmade. If no correction ismade then correlationsclaimed to be statisticallysignificant (that is that theyare unlikely to be the result ofchance) may actually not besignificant.

This problem is made worseby the habit of someresearchers to publish theresults of a single study in anumber of separate papersover several years. It is thennot immediately apparentwhether a correction formultiple correlations wasundertaken.

Experimental StudiesThe most reliable form ofevidence is provided by

experimental studies inhuman subjects, oftenreferred to as interventionstudies. Ideally, the design ofsuch studies should involvethe random assignment ofsimilar subjects into at leasttwo groups, an experimentaland a control group. Thisdesign is termed a“randomised controlled trial(RCT)”.

Confounding variables shouldbe controlled as much aspossible by the selection ofsimilar subjects acrossgroups, and by controllinglifestyle factors for at least theduration of the study.

The groups are thencompared for specificoutcomes resulting from theexperimental intervention. 3Intervention studies may beundertaken under controlledconditions, usually in alaboratory setting, where allfood is provided to subjectsand confounders such asphysical activity can becontrolled. RCTs may alsobe undertaken in a free livingsetting where either food isagain provided, or food istaken ad libitum with specificinstructions as to the dietaryintervention.

In the latter scenario, thesubject’s dietary intake needsto be checked to ensure thatthe subjects adhere to theintervention, and that all otherdietary components andconfounders have remainedstable for the duration of thestudy.


It is, however, extremelydifficult to change one aspectof the diet without consequentchanges arising in otheraspects of diet. Where thechange is to a macronutrientthere must always be acompensating change toother macronutrients if adifference in total food energyintake is to be avoided. Tominimise the effect ofknowledge of theexperimental design on theresults, it is preferable toensure that both investigatorsand participants are unawareof the nature of theintervention and of whichsubjects have been assignedto the different groups. Thisstudy design is termed“double blind”.

In practice this is particularlydifficult to achieve in studiesinvolving diet. A majorconstraint of interventionstudies in human subjectsrelates to ethics. It is rarelypermitted to undertake anexperiment that may causesignificant harm to thesubjects.

As a result, studies into thepossible adverse effects ofsome aspect of diet arerestricted. In some cases,indirect evidence may beobtained by studying theeffect of reducing the intakeof a potentially harmfuldietary component below thatusually consumed.

In other cases, if a biologicalindicator of future potentialharm exists, then a short termincrease in consumption (that

is not likely to causepermanent effects) ispermitted with the effects onthe biological indicator beingmonitored.

For example, a short termrise in blood cholesterolwould be considered anindicator that cardiovasc- ulardisease risk would beincreased if the rise werepermanent. However, due tothe ability of humans to adaptto a wide variety of diets,acute changes may notnecessarily reflect long termeffects. The cost oflongduration studies isusually financially impractical.Therefore, given the long timeframe thought to be involvedin the development of all themajor noncommunicablediseases, the results of acutestudies need to be viewedwith caution. Experimentalevidence may also be gainedfrom animal and in vitrostudies.

Although animal studies mayallow some insight intonutrition-health interactions,the results can never beassumed to apply in humanswithout direct confirmationfrom human studies. In vitrostudies are generallyundertaken on cells which areexposed to an agent.However, again the resultscannot be extrapolated to awhole body human system.

Dietary AssessmentMost studies of therelationship between diet anddisease fundamentally rely onestimates of the habitual diet

of individual subjects. Theseestimates invariably arisefrom self-reports of foodintake. Since an individual’sfood intake varies from day today, and individuals may notreport what they eataccurately, such estimatesare notoriously unreliable(Lioret et al., 2011, Siebelinket al., 2011, Stote et al.,2011).

The most commontechniques for assessingsubject’s usual diet comprisediet histories, 24-h dietaryrecall, and food frequencyquestionnaires. Diet historiesare 4 usually undertaken byinterview to gain anunderstanding of what aperson usually eats anddrinks. 24-h recall requiressubjects to remembereverything they ate and drankin the previous 24 h.

Food frequencyquestionnaires usuallyexplore an individual’sgeneral consumptionpatterns, or exploreconsumption of a specifictype of food or drink and for aspecific duration eg. theprevious year. Thesemethods have all been shownto be inaccurate.

Numerous replicatemeasures of intake arerequired to obtain morereliable estimates of usualintake (Balogh et al., 1971,Pereira et al., 2010, Stote etal., 2011). For example,

Balogh (1971) estimated thatmore than 11 random 24-h


recalls would be required toachieve an estimate with±20% accuracy of anindividual’s mean intake ofdietary sugar.

Therefore, the practice ofemploying a single, or evendual estimate of intake toreflect dietary pattern over anumber of years is highlyquestionable. Indeed, theinaccuracy of dietary data inepidemiological studies hasbeen used as acounterargument when theresults of such studies do notcorrespond to the outcomeobserved in interventionstudies (Kromhout et al.,2011).

Food diaries, where all foodand drink consumption isrecorded for a period of time(usually 3 or seven days), inparticular when the amountsare measured, areconsidered the highest qualityof nutritional assessment.However, they are costly andthus rarely undertaken inepidemiological studies.

In addition, there is always arisk that subjects will changetheir dietary habits, or mis-record simply because theyare being monitored. Under-reporting of energy or dietarycomponents the subjectconsiders in a negative lightare of particular concern.Under-reporting has beenidentified to be more likely inoverweight and obeseindividuals and thoseconsciously trying to limit theirfood intake. (Lichtman et al.,1992).

Physical Activity and Cardio-respiratory Fitness asConfounders Physical activityand cardio-respiratory fitnessare major confounders instudies examining the effectsof nutrition on a number ofdiseases and therefore needsto be controlled, or adjustedfor, in studies.

Most studies employ self-report and questionnaires toassess physical activity andconsequently, like dietaryassessment, are subject toerror. For example, theHealth Survey for England(NHS Information Centre,2009) reported that more than60% of UK adults (>16 y) didnot meet the minimumrecommended physicalactivity guidelines, asassessed by self-report. Thisnumber rose to ~95% whenassessed by the moreobjective method ofaccelerometry.

Limitations in the evidenceAny review of the evidenceon micronutrient dilutionneeds to address thecontradictions in the scientificliterature. Livingstone andRennie (2009) discussed theissues that account for theinconsistent findings acrossstudies. These include: Variations in the definition of‘sugars’. The terms usedrange from “total sugars”, to“added” or “free sugars”, tothe UK definition of “non-milkextrinsic sugars” (NMES).The categorisation cansubstantially affect the

observed relationshipbetween sugars andmicronutrient intake. Forexample, unsweetened fruitjuice is conventionallyincluded in the categories oftotal and NMES sugars, butmay not be included in ‘addedsugars’. As a result, thechoice of sugarscategorisation cansignificantly affect therelationship betweenestimates of sugars andVitamin C intake.

Use of differentbenchmarks to assessadequacy of micronutrientintake

Direct estimates ofmicronutrient status are rarelyused. Instead, estimates ofrequirement, in the form ofdietary reference values(DRV), are compared withestimates of habitual dietaryintake, in order to assessadequacy of intake. Bothestimates are prone touncertainties, and the choiceof DRV can substantially alterthe results of suchcomparisons. The DRV usedcan vary from the level ofintake that is estimated to beinadequate for the vastmajority (97.5%) of thepopulation (Lower NutrientReference Intake: LNRI) tothe level of intake that isjudged to be adequate for thevast majority (again


97.5%) of the population(Reference Nutrient Intake:RNI). Between theseextremes lies the estimatedaverage requirement (EAR)for a particular micronutrient.Comparison with the EAR iscurrently proposed to formthe methodological basis forassessing adequacy ofmicronutrient intake(WHO/FAO, 2004). With allDRVs, comparison of anestimated individual or groupmean micronutrient intakewith a DRV, withoutconfirmatory biochemical orclinical measures, does notprove suboptimal nutritionalstatus.#2

Evidence arising fromobservational studies that relyon self-reported dietaryintake. Underreporting is anaccepted limitation of self-reported dietary surveys(Livingstone and Black, 2003)and, as a consequence, theproportion of peopleestimated to have aninadequate intake ofmicronutrients isexaggerated. Some studieshave tried to correct forunderreporting by excludingdata from subjects whosedietary records showimplausibly low total energyintake. This still leavessubjects who may havereported plausible energyintakes but have,nonetheless, not fully

reported all their food anddrink consumption.

An inconsistent approach toadjusting for energy intake.Since total food energy intakeappears to be the mostimportant predictor ofmicronutrient intake (DoH,1989, Gibson, 2001), oneneeds to control or adjust forenergy intake to determineany independent effect ofsugars intake. Most studiesattempt to adjust for energyintake by reporting sugarsintake as %energy.

However, this variable is itselfaffected by intake of othermacronutrients. Forshee andStorey (2001) employed anenergy partitioning approachto try to isolate theassociation of added sugarswith micronutrient intake fromthat of energy in the diets ofAmerican children andadolescents. The authorsconcluded that theassociation with sugars intakewas inconsistent and variedwith age group, and rangedfrom no association, tostatistically positive andnegative associations.Furthermore, they determinedthat the impact of addedsugars was too small to haveany clinically significant effecton diet quality.

Reviews of the evidence

A number of recent reviewshave focussed on the topic ofsugars and micronutrientdilution (Gibson, 2007,Livingstone and Rennie,2009), while Ruxton et al.,(2010) evaluated the topicwithin a broad range of healthissues related to sugarsconsumption. Most evidenceemanates fromepidemiological studies withno intervention studiesspecifically changing only thesugar content of the diet withthe primary purpose ofexamining changes inmicronutrient intake.

However, some interventionstudies have examinedaspects of micronutrientintake while altering thesugars, or refined or simplecarbohydrate levels, of thediet. These studies showeither no impact, or only aminor impact, on nutrientadequacy (Gibson, 2007,Ruxton et al., 2010). Onreviewing all availableevidence, both Gibson (2007)and Ruxton et al. (2010)considered that someevidence existed for a dilutioneffect at high consumptionlevels of sugars. Gibson(2007), in a systematicreview, concluded that therewas some evidence that adiet containing a highproportion of added sugars(above 20% energy) waslikely to be marginally lowerin micronutrients than a dietcontaining a proportion ofadded sugars closer to themean intake of thepopulations studied. Theoptimal micronutrient intakes


appeared within diets whichcontained moderate levels ofsugars, since manyassociations were n-shaped,with lower intakes at bothhigh and low intakes ofsugars. Ruxton et al., (2010)also reported that a dilutioneffect was apparent fromcross-sectional studies, butwith fairly consistent evidencethat most diets wereadequate in micronutrients.Nutrient adequacy in thepresence of a high sugarintake may reflect the sourcesof sugar in the diet, sincefortified breakfast cereals,sweetened dairy products,and juices are also importantsources of micronutrients. Incontrast, Livingstone andRennie (2009) determinedthat the totality of evidencedid not provide convincingevidence to either support orrefute the notion that addedsugars result in a dilutioneffect within the range ofintakes commonly seen.

Drawing conclusions fromthe evidenceDue to the limitations in allcurrent methods ofdetermining the preciserelationship between nutrientintake and disease,conclusions must be basedon the balance of evidencefrom all relevant studies,rather than that from anindividual study, or selectedgroup of studies. When anumber of studies have beenundertaken, the overallweight of evidence should bedetermined from high quality,systematic literature reviewsor meta-analysis.

In recent years, there hasbeen increased recognition ofthe need to move away fromexamining the evidenceselectively using purelynarrative reviews, which maybe more open to bias.

Systematic reviews of all theevidence are essential,particularly when theevidence is to be employed inguiding public health. Abiologically plausiblemechanism for an effect isalso required.

The strength of the evidencethat a nutritional factor eitherincreases or 5 decreasesdisease risk may then beclassified, for example, asbeing ‘convincing’, ‘probable’,‘possible’, ‘suggestive’,‘limited’, or, ‘unlikely’ etc.However, the criteria used inassigning the evidence to oneof these categories currentlyvary between differentnational and internationalorganisations.

STATEMENTWSRO considers that onlythe highest level of evidencei.e. convincing, should beemployed when providingguidance on nutrient intake tothe public. Furthermore,WSRO considers that agrading criteria of ‘convincing’should only be used whenevidence exists from morethan one type of scientificstudy, including fromappropriately designed RCTs,and supported by systematicreviews and meta-analyses.Observational

epidemiological studies,however large and wellconducted, are insufficient.Their increasing use as abasis for public health adviceand policy is hazardous, forthe reasons outline above.Numerous examples existwhere evidence from largeprospective studies has notbeen onfirmed by subsequentRCTs.

References

Balogh, M., Kahn, H. A. &Medalie, J. H. (1971)Random repeat 24-hourdietary recalls. Am J ClinNutr, 24, 304-10.

NHS Information Centre(2009) Health Survey forEngland - 2009: Health andLifestyles. Accessed

Kromhout, D., Geleijnse, J.M., Menotti, A., et al. (2011)The confusion about dietaryfatty acids recommendationsfor CHD prevention. Br JNutr, 106, 627-32.

Lichtman, S. W., Pisarska, K.,Berman, E. R., et al. (1992)Discrepancy between self-reported and actual caloricintake and exercise in obesesubjects. N Engl J Med, 327,1893-8.

Lioret, S., Touvier, M., Balin,M., et al. (2011)Characteristics of energyunderreporting in children andadolescents. Br J Nutr, 105,1671-80.

Pereira, R. A., Araujo, M. C.,Lopes Tde, S., et al. (2010)


How many 24-hour recalls orfood records are required toestimate usual energy andnutrient intake? Cad SaudePublica, 26, 2101-11.

Siebelink, E., Geelen, A. & deVries, J. H. (2011) Self-

reported energy intake byFFQ compared with actualenergy intake to maintainbody weight in 516 adults. BrJ Nutr, 1-8.

Stote, K. S., Radecki, S. V.,Moshfegh, A. J., et al. (2011)

The number of 24 h dietaryrecalls using the USDepartment of Agriculture'sautomated multiplepassmethod required to estimatenutrient intake in overweightand obese adults. PublicHealth Nutr, 14, 1736-42.


SUGAR INDUSTRY ABSTRACTSEFFICACY OF FLUTRIAFOL COMPARED TO OTHER TRIAZOLE FUNGICIDES FOR THE CONTROL OF SUGARCANE SMUT

Shamsu A Bhuiyan, Barry J Croft, Glen R Tucker, Rebecca James

SMUT IS AN important disease of sugarcane, caused by the fungus Sporisorium scitamineum. Two fungicides,propiconazole and triadimefon can be applied as a 5 min dip to protect the buds from smut infection. This 5 min dipof 1–2 tonne bundles of seed cane has some practical problems. The treatment requires a separate, large 5 000–10000 L tank and disposal of the waste fungicide by an environmentally acceptable method is difficult and costly. Theaim of this research was to evaluate the potential of flutriafol for control of smut by methods that will be morepractical for field application. Two pot experiments were undertaken to: (i) determine whether flutriafol mixed withfertiliser can be taken up by sugarcane roots in sufficient concentration to protect plants from smut infection; and (ii)compare the efficacy of flutriafol with other triazole fungicides, propiconazole and triadimefon, when mixed withfertiliser or used as a dip. The pot trials also tested methods of inoculation with smut that could be used in larger-scale field trials of the fungicide. Results indicated that flutriafol is effective in significantly reducing sugarcane smutinfection when applied at rates of 100–400 g a.i./ha mixed with fertiliser and at rates of 12.5 g a.i./100 L and abovewhen applied as a 10-minute dip of setts. There were significant relationships between application rate of flutriafoland smut suppression when the fungicide was applied mixed with fertiliser. The 10-minute dip applications of thethree triazole fungicides were more effective than the fungicide/fertiliser mix. Propiconazole and triadimefon wereequally effective when applied as a dip, but they were less effective than flutriafol when mixed with fertiliser. Controlwas achieved when the smut was injected into the buds or applied by a dip of the setts at planting. Results suggestthat flutriafol can kill smut fungus after it has established within the plant. Dipping setts in a suspension of smutspores is a practical method of inoculation that can be used for future field trials of flutriafol.

A STATISTICAL APPROACH FOR IDENTIFYING IMPORTANT CLIMATIC INFLUENCES ON SUGARCANE YIELDS

Y Everingham, J Sexton A Robson

INTERANNUAL CLIMATE VARIABILITY impacts sugarcane yields. Local climate data such as daily rainfall, temperatureand radiation were used to describe yields collected from three locations–Victoria sugar mill (1951–1999), Bundabergaveraged across all mills (1951–2010) and Condong sugar mill (1965–2013). Three regression methods, which havetheir own inbuilt variable selection process were investigated. These methods were (i) stepwise regression, (ii)regression trees and (iii) random forests. Although there was evidence of overlap, the variables that were consideredmost important for explaining yields by the stepwise regressions were not always consistent with the variablesconsidered most important by the regression trees. The stepwise regression models for Bundaberg and Condongdelivered a model that was difficult to explain biophysically, whereas the regression trees offered a much moreintuitive and simpler model that explained similar levels of variation in yields to the stepwise regression method. Therandom forest approach, which extends on the regression tree algorithm generated a variable importance list whichovercomes model sensitivities caused by sampling variability, thereby making it easier to identify important variablesthat explain yield. The variable importance list for Victoria indicated that maximum temperature (February–April),radiation (January–March) and rainfall (July–October) were important predictors for explaining yields. For Bundaberg,emphasis clearly centred on rainfall, particularly for the period January to April. Interestingly, the random forest modeldid not rate rainfall highly as a predictor for Condong. Here the model favoured radiation (February to April), minimumtemperature (March–April) and maximum temperature (January to April). Improved understanding of influentialclimate variables will help improve regional yield forecasts and decisions that rely on accurate and timely yieldforecasts.


MEASURING POPULATION IMPROVEMENT IN THE SRA SUGARCANE BREEDING PROGRAM

Mc Cox, Fc Atkin, X Wei, G Piperidis, Rc Parfitt, Jk Stringer

EACH YEAR, SUGARCANE breeders in each region plant and assess new populations of clones in Clonal AssessmentTrials (CAT, target 2,000–2,500) and Final Assessment Trials (FAT, target 150–250). These clonal populations areselected originally from seedling families that are derived from crosses between two parents. Breeder input annuallyinto parent selection, cross selection, seed selection, family selection and, ultimately, clonal selection, is critical indelivering new varieties to the Australian sugar industry. It could also be assumed that, through continualimprovements in all aspects of selection mentioned, the current clonal populations produced are ‘better’ than previouspopulations for the important traits under selection – i.e. cane yield (TCH), CCS and the combination of these twoand other traits as the selection index called relative Economic Genetic Value (rEGV). This concept of ‘PopulationImprovement’ is important to plant breeders to achieve continual improvement in genetic gain and in the newvarieties released. However, currently there are no routine methods developed to quantify this improvement. Thereare a number of difficulties in comparing the different populations across years. These include large year to year andsite to site variation and the appearance of a new disease, such as the recent orange rust (2000) and smut (2006)epidemics. Population statistics relative to a common standard variety or set of standard varieties would be one wayto overcome this problem, but the standard varieties used by breeders also change with time. This generallyprecludes the assessment of populations over long time periods, which would be optimal (e.g. 10 to 20 years).However, data are available to assess populations over much shorter periods. This paper examines methods tomeasure clonal population improvement within the SRA regional selection programs and reports on the trends inpopulation improvement and their implications and limitations.

EFFICACY OF NEW CHEMICALS TO CONTROL PINEAPPLE SETT ROT OF SUGARCANE

Priyanka Wickramasinghe, Shamsul A Bhuiyan, Barry J Croft

PINEAPPLE SETT ROT, caused by Ceratocystis paradoxa, is an economically important disease of sugarcaneworldwide. It causes germination failures of seedcane or setts leading to poor crop establishment. Among theregistered fungicides in Australia, the organomercury fungicide Shirtan® (methoxy ethyl mercuric chloride) is the mostpopular because it may stimulate germination of setts in addition to controlling pineapple sett rot. However, theorganomercury fungicides have greater health and environmental impacts than other fungicides in use due to thepresence of mercury. Two glasshouse experiments and a field experiment were undertaken at Sugar ResearchAustralia, Woodford, aiming to assess the efficacy of fungicides Vibrance®, Dynasty® and Mirador® against pineapplesett rot of sugarcane compared to two registered chemicals, Sinker® and Shirtan®, and to assess their ability tostimulate sett germination. The results of these experiments clearly indicate that Dynasty® and Vibrance® can beeffectively used to control pineapple sett rot of sugarcane in glasshouse conditions with similar effectiveness toSinker® and either better or similar effectiveness to Shirtan®. More research is needed to further evaluate the efficacyof fludioxonil (one of the component chemicals of Dynasty®) and Vibrance® in controlling pineapple sett rot under fieldconditions, and for the control of other important fungal diseases such as sugarcane smut.


NEW SOURCES OF RESISTANCE TO MAJOR DISEASES FROM WILD RELATIVES OF SUGARCANE

Barry Croft, Shamsul Bhuiyan, Robert Magarey, George Piperidis, Eunice Wong, Priyanka Wickramasinghe, Judi Bull,Mike Cox, Graham Stirling, John Foreman, Phillip Jackson

THE HYBRIDISATION OF noble sugarcane, Saccharum officinarum, with its wild relative S. spontaneum in the early1900s was responsible for greatly improved resistance to a number of diseases, increased vigour and improvedratooning. New crosses made in Australia with S. spontaneum clone Mandalay during the 1960s resulted in theimportant parent clone, QN66-2008, which is the parent of 25 and grandparent of 18 ‘Q’ varieties. Introgressionbreeding requires many years of crossing, screening of progeny and backcrossing to retain the beneficialcharacteristics while reducing the negative characters associated with the wild relatives, such as low sugar and highfibre. A collaborative introgression breeding program between CSIRO, BSES/SRA and Chinese research organisationscommenced in 2000. Chinese breeders made crosses with Erianthus spp. and S. spontaneum from Asia. Seed andclones from this program were imported into Australia through quarantine and have been tested for yield anddisease resistance. A selection of over 600 introgression clones has been screened for resistance to pachymetra rootrot, root knot nematode, root lesion nematode and smut. Some clones from the advanced backcrosses that areresistant to these diseases have been identified and are currently being further tested for potential as commercialvarieties or as parents to provide new sources of resistance to the diseases and to broaden the genetic base ofcommercial varieties. This paper reports on the variation in resistance to diseases of the introgression crosses fromsugarcane wild relatives including the disease resistance of true crosses with the genus Erianthus.

.

EFFECT OF SILICON FERTILISERS ON SUGARCANE SMUT IN AUSTRALIA

Shamsul A Bhuiyan, Barry J Croft

SMUT CAUSED BY the fungus, Sporisorium scitamineum, is an important disease of sugarcane in Australia. Atrial was conducted in Bundaberg on a silicon-deficient sandy soil to determine the efficacy of soil-appliedsilicon for control of smut in two susceptible (Q157 and Q205A), one intermediate (Q208A) and two resistant(Q151 and Q200A) varieties. Silicon was applied as air-cooled blast furnace slag (14–18% silicon) at 6 t/ha(8.1 kg/9 m row) to selected plots and incorporated using a rotary hoe. Test varieties were planted betweenspreader rows of smut-infected Q205A. The trial was maintained for three years until second ratoon. Diseaseassessments were carried out prior to harvesting, and yield data were collected only in the second ratoon.The silicon levels in leaf tissue were significantly higher in silicon-treated plots compared to untreatedcontrols. The highly resistant variety Q151 showed no smut in either silicon or untreated plots throughout theexperiment. The intermediate to resistant variety Q208 had 3% smut in the silicon treatment and 6% smut inthe untreated plots in the second ratoon crop and the moderately resistant variety Q200A had 12% smut inthe silicon treatment and 8% smut in the untreated. These differences were not significant. At the finalinspection in the second ratoon crop there were no significant differences in smut incidence between thesilicon-treated and untreated plots of the susceptible variety Q157 (99 and 100% respectively), butsignificance differences were observed in Q205A (86 and 93% respectively). Tonnes of cane per hectare(TCH) and tonnes of sugar per hectare (TSH) were significantly higher in the silicon-treated Q208A comparedwith the untreated Q208A. The highest TCH and TSH in this trial were obtained from Q208A with silicon (150and 26 t/ha respectively). Silicon did not significantly increase TCH or TSH in the other varieties and nodifferences in commercial cane sugar (CCS) were observed between silicon treated and untreatedvarieties. This experiment showed that resistant and intermediate varieties are effective in controlling smutwith no addition of silicon under very high inoculum pressure from the disease. Silicon did not control smut inhighly susceptible varieties, but possibly minimised the adverse stress response in Q208A.


AN EFFECTIVE APPROACH TO DELIVERING SUGARCANE IRRIGATION EXTENSION AT BUNDABERG BASED ON REALTIME WEB-BASED TECHNOLOGY

MG HAINES

BUNDABERG HAS A supplementary irrigation water supply capable of supplying approximately one third of thepotential annual crop moisture demand and rainfall is often insufficient or inappropriately timed for the seasonalrequirements of the sugarcane crop. This situation lead to the development of an extension program designed toimprove scheduling techniques to maximise crop utilisation of both water sources. There are several locations acrossthe world where field monitoring of soil moisture is practiced and data are received through web technologies(Kenana Sugar Company, Sudan, Indonesia, Murray Darling Irrigation Area, Australia) but discussions with thesegroups indicate that data are generally delivered to the primary user for the specific use of the company, agronomydepartment or the specific farming operation. A modern interpretation of the role of agricultural extension is onethat enables change in individuals, communities and industries involved in the primary industry sector and in naturalresource management. The concept of identifying champions with the intention that other farmers will beencouraged to adopt similar goals and practices is a long-standing extension method. However, when dealing withissues of irrigation, promoting outcomes after the event does not alert the target group to the need for timelychange and therefore is unlikely to successfully achieve the desired outcome. A Bundaberg web-based extensionprogram designed to draw all farmers in the district into a technology group of likeminded users was developed.Monitoring systems located on the farms of high performing enterprises provide a constant flow of real timeinformation which enables the industry as a whole to react to climatic influences. The potential outcomes of thisprogram are a sustainable increase in productivity, a reduction in irrigation input costs and a greater understandingof factors that impact on the local environment.



INTERNATIONAL EVENTS CALENDAR

February 1 3 2016ASBF Annual Meetng Long Beach, CA USA ASBF

February 2-4 2016Louisiana Division of ASSCT, Lafayette, LA USA ASSCT

May 17-20 2016Sugar Industry Technologists Annual Meeting Osaka, Japan SIT

February 23 26 2016ASSBT Clearwater, FL USA ASSBT

June 22 24 2016Florida and Louisiana Joint Division of ASSCT New Orleans, LA USA ASSCT

October 19-24 2016Latin American Sugar Technologist Meeting (ATALAC), Olinda, Pernambucco, Brazil


STORY OF SWEETSLeg Of Lamb Stuffed With Rice

IngredientsFor Stuffing:- 2 tbsp. oil- 2 tbsp. butter- 1 medium onion, peeled anddiced- 2 cups button mushrooms, quartered-1/2 green bell pepper, diced-4 whole red chilies-1 clove garlic, minced-2 cups boiled rice-2 tbsp. fresh cream-1 tbsp. fresh coriander leaves-1 tsp. salt-1\2 tsp. pepper

For leg of lamb:- 3 tbsp. lemon juice- 2 tsp. salt- 1\2 tsp. black pepper- 1 tbsp. garlic paste- 1 tsp. chili powder- 4 tbsp. oil- 2 1\2 kg. boneless leg of lamb1. Melt butter with oil in large nonstick skillet overmedium heat.2. Add onion, mushrooms, bell pepper, chilies andminced garlic clove and sauté until mushrooms are

tender, about 5 minutes.3. Add rice and cook until heatedthrough, stirringconstantly. Cool. Add cream, corianderleaves, salt and pepper and mix to blend.4. Preheat oven to 425°F. In a bowl, mix together lemonjuice, salt, pepper, garlic paste, chili powder and 2tablespoons oil.5. Unroll lamb, pat dry and rub with marinade. Place cutside up of lamb on work surface. Spread half ofstuffingevenly over lamb, press to adhere.6. Starting at narrow end, roll up lamb tightly, enclosingfilling. Place lamb in netting to hold shape.7. Hold one end of lamb and fill the opposite end withrest of stuffing. Use kitchen string to tie ends of netting.8. Rub outside of lamb with remaining 2 tablespoonsoil, Place it on rack in roasting pan. Roast lamb todesired doneness, about 11\2 hour.9. Remove from oven. Cover with foil and let stand 15-20minutes. Remove string and netting. Cut lamb into1/2-inch-thick slices. Place on platter.10. Serve it with Nan and Chutney.Serves: 8Note: For ease of preparation,ask the butcher to butterflythe leg of lamb for you.

Mango Ice CreamIngredients-1 Peach mango (peeled, chopped)-1 Pawpaw (peeled, chopped)-1 tbsp. Lemon juice-4 Egg yolks-2/3 cup Icing sugar-1/2 cup Thickened cream-1/4 cup Fresh coconut milk-1 tbsp. Ground almonds-Garnish Fresh fruit or mint sprigs

MethodPuree the mango and pawpaw together with thelemon juice.2. Beat the eggs and icing sugar in the top of adouble boiler until the eggs are pale and thick.Remove from the heat, pour into a bowl andcontinue to beat until the mixture is cool. Fold thefruit puree into the egg mixture and add the cream,coconut milk and almonds.3. Pour the mixture into a mould or freezer trayand freeze for 2-3 hours.4. To Serve: Dip the mold into hot water for 30seconds before turning out, or scoop out as icecream balls. Garnish with fruit or fresh mint sprigs.


GUIDELINES FOR AUTHORS

Dear Fellow Author(s),

Pakistan Sugar Journal (PSJ) offers research, analysis, and reviews to keep its local andinternational readership up to date with latest developments in the sugar industry. PSJtakes into account the application of research and focuses on areas in agriculture related tosugar, milling and processing.

In order to have your articles published in the PSJ, you are requested to adhere to thebelow instructions and prerequisites to enable timely review of your submissions by theeditorial board:

I. Write the title of your article in CAPITAL LETTERS in the center of the page.II. Write the complete name of all authors with their addresses – it is compulsory in the

text. References should be cited by author and years as, for one, two or moreauthors (Hammer, 1994, Hammer and Rouf, 1995; Hammer et al., 1993),respectively.

III. Write HEADINGS in bold letters and in the center of the page.IV. Type your article only in TIMES NEW ROMAN format.V. Send TABLES and FIGURES on separate page with bold title and mark its numbers

correctly.VI. Observe the following rule for REFERENCE, for one author: Hussain, K. 1991 for

two authors; Khan, M. and A. Habib 1995, for more than two; Ali, K., A.Hussain and S. Nasir, 1990.

VII. Always send two soft copies and one hard copy of CD. Please do not use FLOPPYDISK for this purpose.

VIII. Send copies on an A-4 size page, preferable LASER PRINT in word documentIX. Papers published in the PSJ are free of charges (for authors).X. Send your papers to following address by mail or email:

Dr. Shahid AfghanEditor-in-Chief, Pakistan Sugar JournalShakarganj Sugar Research Institute, Jhang (Pakistan)Phone: +92 47 763 1001-5 | Ext. 602, 603Email: [email protected]

Documents

Oct.-Dec.,2015 - Shakarganj Researchssri.pk/psj/PSJ October-December 2015.pdf · Oct.-Dec.,2015. 1 | P a g e Editorial Board Mr. Altaf M. Saleem Chairman Dr. Shahid Afghan Editor-in-Chief