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WORLD COTTON RESEARCH CONFERENCE-5 Renaissance Convention Centre, Mumbai 7-11 November 2011

Theme: Technologies for Prosperity

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WORLD COTTON RESEARCH CONFERENCE-5 Renaissance Convention Centre, Mumbai 7-11 November 2011

Theme: Technologies for Prosperity

(Oral Presentations of WCRC-5)

Editors Dr. K.R. Kranthi

Dr. M.V. Venugopalan Dr. R.H. Balasubramanya

Dr. Sandhya Kranthi Dr. Sumanbala Singh

Dr. Blaise

Organized by

International Cotton Advisory Committee, Washington, DC, USA

Indian Society for Cotton Improvement, Mumbai, India

Indian Council of Agriclutural Research, New Delhi, India

EXCEL INDIA PUBLISHERS New Delhi

Book of Papers

First Impression: 2011

© Indian Society for Cotton Improvement, Mumbai

World Cotton Research Conference on Technologies for Prosperity

ISBN: 978-93-81361-51-1

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Preface

“Every advance in civilization has been denounced as unnatural while it was recent”

—Betrand Russell

Indeed, it has now become more common than ever before, to debate, denounce but adopt changes. And, when it happens, adoption of new technologies happens in a manner like never before. The recent biotech advances in cotton epitomized the saga of technologies that became ‘game-changers’ to emerge victorious, unscathed, but wading through adversities.

Cotton is natures’ gift to mankind. The gentle fibers pass through tough mechanical rigor to become soft fabric that clothes and makes civilizations. For more than seven thousand years, cotton has been the best possible natures’ fabric and the world reveres it now. Cotton in many countries means livelihood, employment and food security. With a current share of 36.0% in fabrics, cotton continues to remain as the most skin friendly of all apparel available to mankind. The global cotton production in 2010 was 25.1 M tons from 34.0 M hectares. With population at 6.8 billion in 2010, the average per-capita utilization of fibers is estimated to be 10.4 kg. The global production of fibers increased from 52.0 M tons in 2000 to 72.5 M tons in 2010 at an average growth rate of 3.3% and is expected to reach 138 M tons by 2030 with an estimated 48.0 M tons of cotton production. The world population is estimated to increase at an annual growth rate of 1.4% to reach 8.2 billion by 2030. It is being speculated that the declining supply of raw materials and oil reserves in the future will constrain man-made fiber production and the demand for cotton will increase. Even today the demand for cotton would increase if the entire production and processing system is made more cost effective by improving yield per unit input. The cotton demand may increase, if the petroleum reserves become a limiting factor for the production of man-made fibers. Yields have to increase without any further area spread. Science and technologies alone will show the way. As we move on, to cater to the needs of burgeoning population, it becomes our collective responsibility to tread a path that is in consonance with nature. For several decades, cotton cultivation and post-harvest processing had become input intensive and chemical dependent. Together we will succeed as a global family only when we shall be able to discover methods of agriculture and industrial processes that will be least disruptive to the environment and profitable for all concerned in production and processing.

W.R. Whitney, chemist and founder of General Electric Company, said

“In the advance of civilization, it is new knowledge that paves the way, and the pavement is eternal”

The papers presented at the conference represent ‘New Knowledge’ and reflect the trend towards progress in science and technologies for a better future. We earnestly hope that the book of papers will be treasured by the cotton fraternity.

Editors

Contents

Preface v

COTTON IMPROVEMENT AND BIOTECHNOLOGY

1. Genetic Diversity Analysis in Cotton Germplasm Prafulla Naphade, Pandurang Kulkarni, Rahul Ramekar,

Ashok Jaybhaye Chandrashekhar Chaporkar, Bharat Char and Venugopal Mikkilineni 3

2. Creating Novel Diversity and using Comprehensive Methods for Their Further Use in Hybrid Research—An Exercise in Gossypium hirsutum L.

Rajesh S. Patil, Bharathkumar, Kasu Pawar, Sudheendra Ashtaputre, Ishwarappa Katageri, Basavaraj Khadi, Bhuvaneshwaragouda Patil, Shreekanth Patil and Shekhar L. 8

3. New Cotton Germplasm as an Intermediate Cycle Called SP 8 Development by the National Institute of Agricultural Technology–INTA

A. Tcach Mauricio, A.F. Poisson, Ivan Bonacic, Silvia Ibalo, Alex Montenegro Daniel Ojeda and Mariano Cracogna 13

4. Introgression of High Fibre Strength Trait to Upland Cotton using Marker-Assisted Selection

Nallathambi Kannan, P. Selvakumar, R. Krishnamoorthy, D. Raja, M. Bhuvaneshwari, V. Subramanian and M. Ramasami 17

5. Estimation of Genetic Parameters for Yield and Fibre Quality Traits in Inter-Specific Crosses of Cotton (Gossypium spp.)

Gunasekaran Mahalingam, Krishnasamy Thiyagu and Nagasamy Nadarajan 28

6. Introgression of Desirable Characters for Growing Cotton in Pakistan

Abid Mahmood, Jehanzeb Farooq and Noor-Ul-Islam 35

7. Temporal Changes in Metabolically Important Enzymes and Solutes act as Trigger for Epidermal Cell Conversion to Fibre Initials in Cotton

Gopalakrishnan N., A.H. Prakash and Y.L. Balachandran 43

8. Study of Interspecific Hybrids (Gossypium hirsutum x G. barbadense) for Heterosis and Combining Ability

K.P.M. Dhamayanthi 51

9. Predicting F Performance from Their Parental Charectaristics in Upland Cotton (Gossypium hirsutum L.)

R.K. Gumber, Pankaj Rathore and J.S. Gill 56

10. Thermosensitive Genetic Male Sterility System in Cotton (G. arboreum L.)

S.M. Palve, V. Santhy, S.R. Bhat, S. Laxman, Rajesh Patil, B.M. Khadi, Sonali Virkhede and Priyanka Bihariya 62

11. Heterosis for Yield and Yield Attributing Traits in Arboreum Cotton (Gossypium arboreum L.)

S.B. Lalage, N.D. Deshmukh, I.S. Halakude and J.C. Rajput 69

viii Contents

12. Multi-Level Determination for Heat Tolerance of Cotton Cultivars Nicola S. Cottee, Michael P. Bange, Daniel K.Y. Tan, J. Tom Cothren 72

13. Genetic Variability in Single Plant Selections for Improving Drought Tolerance in Upland Cotton

Suman B. Singh, A.H. Prakash and Amol A. Karpe 80

14. Genetic Parameters of Physiological Traits for Salinity Tolerance in Diverse Genotypes of Cotton (Gossypium hirsutum L. and Gossypium arbadense L.)

Hosseini Gholamhossein and Behdarvand Pejman 85

15. Marker-Assisted Selection for Improving Drought Resistance in Cotton

Yehoshua Saranga, Avishag Levi and Andrew H. Paterson 89

16. Tak FA8: New Jassid Tolerant Cotton Variety P. Seburuang,W. Sirichumpan,P. Nakapan,S. Thaitad,S. Lapbunjob

A. Traisiri,N.T. Khumla,S. Areerak,S.A. Juttupornpong,N. Panlai,A. Kasivivat,P. Sangsoda,R. Chuekittisak, B. Kumseub,P. Pulcha and K. Khockakang 92

17. High Boll Weight and High Ginning Outturn— The Major Tools for Breaking Yield Barriers in Gossypium arboreum

Punit Mohan, S. Manickam, S.K. Verma, D. Pathak, A.S. Singh and Tarun Kumar Das 95

18. Development of Naturally Coloured Gossypium hirsutum Cotton Genotypes Suitable for Textile Industry through Genetic Improvement

Manjula S. Maralappanavar, Vikas V. Kulkarni, Somshekhar, C. Madhura, S.S. Patil, K. Narayanan, K.J. Sanapapamma and Jyoti V. Vastrad 100

19. Divergent Selection for Yield and Earliness in Cotton (Gossypium hirsutum L)

P. Michalakopoulos, C. Goulas, A. Katsiotis and S. Rangasamy 104

20. Development of Recombinant Inbred Lines for Fibre Quality Traits in Gossypium hirsutum L

Jagmail Singh, Babita Chaudhary, Preeti Srivastva, Sapna Tiwari and Mukesh Kumar Sharma 111

21. Elite Cotton Varieties in the Zimbawean Private Sector Research Programme

Mandiveyi Jeremiah Kudzayi 115

22. Development of Biotic Stress Resistance Transgenic Diploid Cotton Utilizing Agrobacterium and Shoot Apical Meristem Cells

Sukhadeo Nandeshwar, Pranjib Chakraborty, Kanchan Singh, Mithila Meshram and Bipinchandra Kalbande 120

23. Cloning and Characterization of Cellulose Synthase Genes from Arabidopsis thaliana

Balasubramani G., Amudha J., Sahare S. and Kranthi K.R. 129

24. Cotton Transgenic with DRE-binding Transcription Factor Gene (DREBA) and Zinc Finger Gene (ZF) Confers Enhanced Tolerance to Drought

Amudha J., G. Balasubramani, A.H. Prakash, Shweta C., K.C. Bansal and K.R. Kranthi 136

Contents ix

25. Study of Heterosis in Inter Varietal Crosses of Asiatic Cotton (Gossypium herbaceum L)

N.N. Patel, D.U. Patel, D.H. Patel, K.G. Patel, S.K. Chandran and V. Kumar 149

26. Assessment of Genetic Diversity for Improved Fibre Quality Traits in G. barbadense Accessions to Widen Cotton Gene Pool

Amala Balu P., D. Kavithamani and S. Rajarathinam 153

COTTON PROTECTION

27. Survival of Helicoverpa armigera on Bt Cotton Hybrids in India—Can We Buy the Interpretations

A. Prabhuraj, Y.B. Srinivasa and K. Muralimohan 161

28. Field Performance of F,-F and non-Bt of BG-II (MRC-707 Bt) and JKCH-97 Bt Against Bollworms of Cotton

G.T. Gujar, G.K. Bunker, B.P. Singh and V. Kalia 165

29. Intrinsic Rate of Increase and Life Parameters of Cotton Leaf Eating Caterpillar Spodoptera litura on Bollgard II Hybrids

Golla M.V. Prasada Rao, T. Sujatha, G.A.D. Grace, N.V.V.S.D. Prasad and V. Chenga Reddy 174

30. Field Efficacy of Widestrike™ Bt Cotton, Expressing CryAc and CryF Proteins, Against Lepidopteran Pests in India

Moudgal R.K., Chetan Chawda, Gajendra Baktavachalam Sundara Rajan and Gary D. Thompson 184

31. Influence of Weather Parameters on Population of Mealybug, Phenacoccus solenopsis and its Natural Enemies on Bt Cotton

B.V. Patil, S.G. Hanchinal, M. Bheemanna and A.C. Hosamani 193

32. Insecticide Induced Resurgence of Mealybug, Phenacoccus solenopsis Tinsley in Cotton

Rishi Kumar, Dinesh Swami, Vijender Pal and K.R. Kranthi 198

33. Species Diversity, Pestiferous Nature, Bionomics and Management of Mirid Bugs and Flower Bud Maggots: the New Key Pests of Bt Cottons

S. Udikeri, S. Kranthi, K.R. Kranthi, N. Vandal, A. Hallad S.B. Patil and B.M. Khadi 203

34. Influence of Spatial Cropping Patterns of Cotton Cultivation on Population Dynamics of Mirid Bug, Creontiades biseratense (Distant)

B. Dhara Jothi, T. Sonai Rajan, V.S. Nagrare, M. Amutha, Rishi Kumar and T. Surulivelu 210

35. Determination of Economic Injury Level for Defoliator Spodoptera litura (Fab.) on Bt Cotton

M. Bheemanna, S. Hanchinal, A.K. Hosamani and R. Chowdary 216

36. Development of Metapopulation Approach for Landscape-level Lygus hesperus Management in Texas

M.N. Parajulee, R.B. Shrestha, W.O. Mcspadden and S.C. Carroll 220

x Contents

37. Survival of Pink Bollworm, Pectinophora gossypiella (Saunders) in Bt and Non Bt Cotton In Normal and Late Sowing with A Special Emphasize to Avoid Population Pressure

S. Mohan and S. Nandini 229

38. Dynamics of Biotypes ‘b’ and ‘q’ of Bemisia tabaci in Cotton Fields and Their Relevance to Insecticide Resistance

A.R. Horowitz, H. Breslauer, M. Rippa, S. Kontsedalov, M. Ghanim, P. Weintraub and I. Ishaaya 232

39. Gambit of IPM for Insect Resistant Transgenic Cotton N.V.V.S. Durga Prasad, G.M.V. Prasad Rao and V. Chenga Reddy 239

40. Cotton Pest Management Programmes using Threshold-Based Interventions Developed by CIRAD and its Partners in Sub‐Saharan African Countries

Silvie P.J., Adegnika M.A., Akantetou K.P., Ayeva B., Bonni G., Brevault T., Gautier C., Héma O., Houndete T.A., Ochou G., Prudent P. Renou A. and Togola M. 244

41. Can Natural Refuges Delay Insect Resistance to Bt Cotton Brévault Thierry,, Nibouche Samuel, Achaleke Joseph and Carrière Yves 255

42. Can Tomato be a Potential Host Plant for Pink Bollworm N. Ariela, S. Harpaz Liora, R. Mario, S. Roee and H.A. Rami 258

43. Impact of IRM Strategies on Bt Cotton in Andhra Pradesh T.V.K. Singh, N.V.V.S.D. Prasad, S. Sharma and S. Dayakar 261

44. Efforts to Mitigate Stickiness Problem in Sudan A. Abdelatif and E. Babiker 265

45. Present Status of Mealy Bug Phenacoccus solenopsis (Tinsley) on Cotton and Other Plants in Sindh (Pakistan)

Khuhro S.N., A.M. Kalroo and R. Mahmood 268

46. Changing Scenario of Cotton Diseases in India— The Challenge Ahead

D. Monga, K.R. Kranthi, N. Gopalakrishnan and C.D. Mayee 272

47. Emerging and Key Insect Pests on Bt Cotton— Their Identification, Taxonomy, Genetic Diversity and Management

S. Kranthi, K.R. Kranthi, Rishi Kumar, Dharajothi, S.S. Udikeri, G.M.V. Prasad Rao, P.R. Zanwar, V.N. Nagrare, C.B. Naik, V. Singh V.V. Ramamurthy and D. Monga 281

48. Efficacy of Triazoles in Management of Major Fungal Foliar Diseases of Cotton

A.S. Ashtaputre, N.S. Chattannavar, S. Patil, Rajesh N.K. Pawar and G.N. Hosagoudar 287

49. Damage Caused in Cotton by Different Levels of Ramulosis in Brazil Alderi Emídio De Araújo, Alexandre Cunha De Barcellos Ferreira

and Camilo De Lelis Morello 290

50. Insecticidal Toxin Genes from Bacterial Symbiont of Thermotolerant Isolate of Heterorhabditis indica, Entomopathogenic Nematode

Nandini Gokte-Narkhedkar, Kanchan Bhanare, Prachi Nawkarkar, Prashanth Chiliveri and K.R. Kranthi 293

Contents xi

51. Identification and Characterization of a Novel Source of Resistance to Root-Knot Nematode in Cotton

Mota C. Fabiane, Giband Marc, Carneiro, D.G. Marina, Silva, H. Esdras, Furlanetto Cleber, Nicole Michel, Barroso, A.V. Paulo and M.D.G. Regina 298

52. Predominance of Resistance Breaking Cotton Leaf Curl Burewala Virus (ClCuBuv) in Northwestern India

Prem A. Rajagopalan, Amruta Naik, Prashanth Katturi, Meera Kurulekar Ravi S. Kankanallu and Radhamani Anandalakshmi 304

COTTON PRODUCTION, PHYSIOLOGY AND ECONOMICS 53. Cotton Genotypes Performance under Rainfed

and Irrigated Conditions in two Regions of Northern Argentina Marcelo Paytas and Jose Tarrago 309

54. The Adaptation of Irrigated Cotton to the Tropical Dry Season S.J. Yeates 312

55. Which Carbon Footprint Tool for the Cotton Supply Chain F. Visser, P. Dargush and C. Smith 323

56. Studies on the Seed Cotton Yield, Growth and Yield Contributing Characters of New Bt Cotton Hybrids under Varied Agronomic Manipulations

Kulvir Singh, Harmandeep Singh, R.K. Gumber and Pankaj Rathore 338

57. Evaluation of Cotton Genotypes for High Density Planting Systems on Rainfed Vertisols of Central India

M.V. Venugopalan, A.H. Prakash, K.R. Kranthi, Rachana Deshmukh, M.S. Yadav and N.R. Tandulkar 341

58. Pruning and Detopping Studies in Bt-Cotton S.S. Hallikeri 347

59. Input use Efficiency, Productivity, Profitability and Sustainability of Bt Cotton Based Multi Tier System with Nutrient Levels

K. Sankaranarayanan, P. Nalayini, C.S. Praharaj and N. Gopalakrishnan 350

60. Effects of Prolonged and Integrated Use of Organics and Inorganics on the Performance of Cotton

S.N. Upperi and V.B. Kuligoud 359

61. Response of Cotton to Bio Boron and its Use Efficiency in Vertic Ustropept Soil of Tamil Nadu, India

P. Janaki and S. Meena 364

62. A Thermal Optimum Approach to Irrigation Scheduling in Australian Drip Irrigated Cotton

W.C. Conaty, J.E. Neilsen, J.R. Mahan, B.G. Sutton and D.K.Y. Tan 369

63. Efficient Water Management Technology for Sustainable Cotton Production in Central India

V. Kumar, R.G. Patil and J.G. Patel 376

64. Biodegradable Polyethylene Mulching—A New Approach for Moisture Conservation, Weed Control and Enhanced Productivity of Winter Irrigated Cotton-Maize System

P. Nalayini, K. Sankaranarayanan, K. Velmourougane and M. Suveetha 386

xii Contents

65. Comparative Study of Different Weeding Methods on Cotton Crop under Drip Irrigation System

Dil Baugh Muhammad, M.N. Afzal, I. Raza and P.L. Dupont 392

66. Comparative Efficiency and Economic Viability of Herbicides for Controlling Weeds in Bt Cotton (Gossypium hirsutum L.)

J.G. Patel, V.C. Raj, V.P. Usadadiya, R.R. Parmar, C.M. Sutaria, R.L. Leva and V. Kumar 396

67. Agronomic Management and Benefits of Glyphosate Tolerant Transgenic Cotton Hybrids

C. Chinnusamy, C. Nithya, P. Muthukrishnan and S. Jeyaraman 399

68. Evaluation of Pyrithiobac Alone and in Combination with Grassy Herbicides on Weed Control in Cotton

A.S. Rao 406

69. Defining Optimal Application Rate and Timing of Mepiquat Chloride for Cotton Grown in Conditions that Promote Excessive Vegetative Growth

G.D. Collins, R. Wells, R. Riar and K.L. Edmisten 410

70. Effect of Cool Conditions on Cotton Seedlings D.K.Y. Tan, S. Ormiston, M.P. Bange and J.S. Amthor 416

71. Increased Nutrient Uptake and Salinity Tolerance in AhCMO Tansgenic Cotton

Huijun Zhang, Jianlong Dai and Hezhong Dong 420

72. Improvement of Partial Root-Zone Soil Environment Increases Salinity Tolerance of Cotton

Hezhong Dong, L.I. Weijiang and L.I. Zhenhuai 432

73. Do Female-Led Farms Perform Less Well in Cotton Production? Insight from Hebei Province (China)

Michel Fok and Guiyan Wang 435

74. Debunking the Myths J. Reed, E. Barnes and P. O'Leary 442

75. Analysis of Growth and Instability of Cotton Production in India Anuradha Narala and A.R. Reddy 449

76. Total Factor Productivity of Cotton in Gujarat (India) A.R. Reddy, S.M. Yelekar, R.B. Petkar and N. Anuradha 454

77. Transfer of Technology Initiatives for Profitable and Sustainable Cotton Farming in India— An Empirical Analysis

S. Usha Rani and S.M. Wasnik 461

POST HARVEST PROCESSING 78. Enzyme/ Zinc Chloride Pretreatment of Short-Staple Cotton Fibres

for Energy Reductionduring Nano-Fibrillation by Refining Process

N. Vigneshwaran, Vilas Karande, G.B. Hadge, S.T. Mhaske and A.K. Bharimalla 471

79. Optimal Cotton Covered Jute, Nylon and Metal Core Spun Yarns for Functional Textiles— Production and Characterization

S.K. Chattopadhyay, A. Yadav, V.V. Kadam, Bindu V., D.L. Upadhye, V.D. Gotmare and A.K. Jeengar 477

Contents xiii

80. The Cotton Length Analysis using the Lengthcontrol Iwona Frydrych, Anna Pabich and Jerzy Andrysiak 487

81. An Innovative Bio-chemical Approach for Low Energy and Less Polluting Scouring of Cotton Textiles

P.V. Varadarajan, R.H. Balsubramanya, Nayana D. Nachane, Sheela Raj and R.R. Mahangade 493

82. The Within Bale Repeatability of Standardized InstrumentS for Testing Cotton Fiber Produced in Africa

E. Lukonge, M. Aboe, Gourlot, J.P. Gozé and E. Hublé 500

83. A Vision for Technical Textiles in this Decade A. Subramaniam 508

84. Cotton Stalk: An Additional Raw Material to Board Industry R.M. Gurjar, P.G. Patil, A.J. Shaikh and R.H. Balasubramanya 510

85. Differential Speed Setting Facility for Roller and Beater in Gins for Higher Ginning Rates

S.B. Jadhav and K.R.K. Iyer 524

86. Influence of Quality Attributes of Individual Bales on Yarn Quality

R.P. Nachane 531

87. Development of an Automatic Roller Grooving Machine for Making Helical Grooves on Rollers Used in Roller Ginning Machines

T.S. Manoj Kumar, V.G. Arude and S.K. Shukla 537

88. The Effect of Quarantine Treatments on the Physical Properties of Cotton Fibresand Their Subsequent Textile Processing Performance

M.H.J. Van, Der Sluijs, F. Berthold and V. Bulone 543

89. The Impact of Cotton Fibre Maturity on Dye Uptake & Low Stress Mechanical Properties of the Fabric

S. Venkatakrishnan and R.P. Nachane 553

90. Exploration of Residual Hazardous Compounds on Cotton Fibers Syed Zameer Ul Hassan and Jiri Militky 561

91. Studies on Composition of Oil and Fatty Acid in Bt and Non Bt Cotton (G. hirsutum)

Harijan Nagappa and Khadi B.M. 568

92. The Properties of the Naturally-Pigmented Cotton Cultivated in Nakornsawan Field Crop Research Center Thailand

Piyanut Jingjit and Parinya Seebunruang 572

AUTHOR INDEX 577

Cotton Improvement and Biotechnology

Genetic Diversity Analysis in Cotton Germplasm

Prafulla Naphade1, Pandurang Kulkarni1, Rahul Ramekar2, Ashok Jaybhaye2 Chandrashekhar Chaporkar1, Bharat Char2 and Venugopal Mikkilineni2

1Research & Development (Cotton Breeding) 2Research & Development (Molecular Breeding and Applied Genomics),

Maharashtra Hybrids Seeds Co. Ltd., Jalna, India

Abstract—Crop germplasm diversity contributes significantly to the development of improved crop cultivars aimed at increasing crop productivity. In this study, we have selected 192 proprietary inbred lines of Gossypium hirsutum that show variable phenotype for traits such as leaf hair density, leaf texture, boll size, plant architecture (type), fibre quality parameters, maturity group, and response to biotic and abiotic stresses. This germplasm pool was screened with 54 polymorphic Microsatellite markers. It was found that 47 loci out of the 54 loci show polymorphism between any two lines. The similarity index values ranged between 41% to 98%. Three major dendrogram clusters and twelve minor dendrogram clusters were observed. These results suggested that there is a high degree of genetic diversity in the cotton germplasm which was screened.

INTRODUCTION

Allelic diversity naturally present in the germplasm pool and characterization of the allelic diversity determines the genetic diversity present in the germplasm pool. This forms the basis for continuous evolution. Genetic diversity and the knowledge on relationship between genotypes are of great importance for crop breeding. It creates a resource pool of alleles and enables pooling of novel alleles and helps in creating new allelic combinations which result in creation of novel genotypes. From a practical crop breeding perspective, understanding the genetic variability will serve as a guide to choosing the parents from a larger pool of germplasm. Crossing individuals that are genetically distant can result in developing superior hybrids with higher heterotic potential and hence higher yields. Molecular level study of the genetic diversity will also help in situations where quantitative traits are desirable and in field conditions it is difficult to evaluate the lines due to the effect of the environment on the phenotype (Weir, 1990).

Cotton productivity and the future of cotton breeding efforts, as in many other agronomic crops, also depend on genetic diversity of cotton gene pools. Worldwide cotton breeders and producers have expressed concern over the narrow genetic basis of cultivated cotton germplasm that has caused a decline in yield and quality. Globally cotton breeding programme are working with a narrow germplasm pool thus resulting in genetic bottleneck through historic domestication events and selection (Iqbal et al., 1997).

Assessment of the genetic diversity of cotton cultivars is essential to breeding strategies, such as the characterization of individuals, accessions, and for the choice of parental genotypes in breeding programs. For any meaningful plant-breeding programme, accurate determination of genetic diversity is an essential step for an effective utilization of germplasm resources. An accurate estimation of genetic diversity can be invaluable in the selection of diverse parental combinations to generate progenies with maximum genetic variability and heterosis. In addition, introgression of desirable traits from diverse/wild germplasm into the elite cultivars to broaden the genetic base is possible (Ulloa et al., 2007). Estimation of genetic diversity based on the morphological and biochemical markers has its limitations due to environmental variations. Molecular marker techniques on the other hand have evolved as powerful tools for genetic diversity analysis and in establishing relationships between cultivars. Molecular genetic techniques using DNA markers have been increasingly used to characterize and identify novel germplasm for use in the crop breeding process (Zhang et al., 2003). A systematic assessment of genetic resources will also help to identify the specific crosses to be made and hence decrease the number of

1

4 World Cotton Research Conference on Technologies for Prosperity

crosses to be designed in a breeding program. This will enable better utilization and management of germplasm resources and also help enlarge the germplasm base hence removing the bottle necks in breeding (Karp, 2002). Classification of germplasm based on the geographic regions would also be valuable in understanding the structure of the cotton germplasm gene pools.

The development of abundant cotton SSR markers has stimulated more effort in molecular characterization of cotton germplasm around the world (Blenda et al., 2006; Zhang et al., 2008). DNA-based markers, microsatellite or simple sequence repeats (SSR) are co-dominant markers to assess genome level diversity. SSR markers have been used as tools in genotype identification and variety protection, seed purity evaluation, germplasm characterization, diversity studies, gene and quantitative trait locus (QTL) analysis, pedigree analysis and marker assisted breeding. SSR markers have played an important role in the dramatic progress of cotton genetics and genomics. Being both co-dominant and multi-allelic, microsatellites are highly reproducible and informative genetic markers (Morgante et al., 2002; Turkoglu et al., 2010). Another advantage of SSR markers is that they are highly transferable across species especially within a genus (Saha et al., 2004). The objectives of this study are 1) to evaluate the genetic diversity among selected cotton cultivars, and 2) to provide essential information for future marker-assisted breeding and to facilitate a more efficient use of germplasm in cotton breeding.

MATERIALS AND METHODS

One hundred and ninety two Gossypium hirsutum germplasm accessions were included for genetic diversity study. This germplasm is the proprietary core cotton collections developed at Maharashtra Hybrid Seeds Co. Ltd., Jalna, India.

Flow chart illustrating the methodology

Leaf crushing was done on a paint shaker and DNA extraction was done by Silica method (unpublished protocol). To develop a core set of polymorphic markers, we screened 278 markers across 13 elite germplasm lines and identified 54 polymorphic markers which were eventually converted into core set of SSR markers. This core set of 54 polymorphic markers were used to screen the 192 germplasm lines.

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Genetic Diversity Analysis in Cotton Germplasm 7

Fig. 3: Chromatogram File Generated by ABI3730 96 Well Capillary Electrophoresis

REFERENCES [1] Blenda, A., Scheffler J., Scheffler B., Palmer M., Lacape J. M., Yu J. Z., Jesudurai C., Jung S., Muthukumar, S.,

Yellambalase, P., Ficklin, S., Staton, M., Eshelman, R., Ulloa, M., Saha, S., Burr, B, Liu, S., Zhang, T., Fang, D., Pepper, A., Kumpatla, S., Jacobs, J., Tomkins, J., Cantrell, R., and Main, D. (2006). CMD: a Cotton Microsatellite Database resource for Gossypium genomics. BMC Genomics 7:132

[2] Iqbal, M.J., Aziz, N., Saeed, N.A., Zafar, Y., Malik, K.A. (1997). Genetic diversity evaluation of some cotton varieties by RAPD analysis. Theor. Appl. Genet. 94: 139-144.

[3] Karp, A. (2002). The new genetic era: will it help us in managing genetic diversity? In: Managing [4] Plant Genetic diversity. (Eds.): J.M.M. Engels, V.R. Rao, A.H.D. Brown and M.T. Jackson. [5] International Plant Genetic Resources Institute, Rome, Italy, 43-56. [6] Krishnasamy Thiyagu, Narayanan Manikanda Boopathi, Nagasamy Nadarajan, Ayyanar Gopikrishnan, Pandi Selvakumar,

Santoshkumar Magadum and Rajasekar Ravikesavan. (2011) Sampling and exploitation of genetic variation exist in locally adapted accessions using phenotypic and molecular markers for genetic improvement of cotton. Genecon. 10: 129-153.

[7] Morgante, M, Hanafey, M. and Powell, W. (2002). Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nat. Genet. 30: 194-200

[8] Saha, S., Wu, J., Jenkins, J.N., McCarty, J.C. Jr, et al. (2004). Effect of chromosome substitutions from Gossypium barbadense L.3-79 into G. hirsutum L. TM-1 on agronomic and fiber traits. J. Cotton Sci. 8: 162-169.

[9] Turkoglu, Z., Bilgener, S., Ercisli, S., Bakir, M., et al., (2010). Simple sequence repeat-based assessment of genetic relationships among Prunus rootstocks. Genet. Mol. Res. 9: 2156-2165.

[10] Ulloa, M., Brubaker, C. and Chee, P. (2007). Cotton. In: Genome Mapping & Molecular Breeding (Kole C, ed.). Vol. 6. Technical Crops Springer, New York.

[11] Weir, B. S. (1990). Genetic data analysis: methods for discrete population genetic data. Sinauer Associates, Inc. publishers. Sunderland, Massachusetts. 377.

[12] Zhang, Y., Wang, X.F., Li, Z.K., Zhang G.Y. and Ma Z.Y, (2011). Assessing genetic diversity of cotton cultivars using genomic and newly developed expressed sequence tag-derived microsatellite markers. Gen. Mol. Res. 10 (3): 1462-1470.

Coefficient0.01 0.07 0.14 0.20 0.26

100MW

1 122 111 119 190 11

100 127 103 105 136 145 32 99

163 156 102 161 74 98 5

88 113 133 134 148 132 191 131

6 135

8 44

125 165 117 143 164 53

166 40 48

182 169 115 108 150 118 140 141 104 121 178 97

157 186 106 107 129 158

Creating Novel Diversity and using Comprehensive Methods for Their Further Use in Hybrid Research—

An Exercise in Gossypium hirsutum L.

Rajesh S. Patil, Bharathkumar, Kasu Pawar, Sudheendra Ashtaputre, Ishwarappa Katageri, Basavaraj Khadi, Bhuvaneshwaragouda Patil,

Shreekanth Patil and Shekhar L.

UAS, Dharwad, India

Abstract—Cotton breeding is a continuous endeavour aiming to produce better genotypes and hybrids. The present exercise involved choosing the F1 hybrids, from national trials, as parents and then employing methods to assess the diversity produced in the F5 segregants leading to identification of elite lines which can be used in further hybrid research. The two parts of study spanning a period of five years began in 2007-08 and was initiated with an objective to isolate superior Gossypium hirsutum genotypes related to yield and fibre properties from double crosses whose F1 parents were chosen for their diversity and superior traits. Segregants from a three-way cross and also the respective single cross parents of double crosses were included in the study. In all there were 115 lines drawn from five double cross, one three-way cross and six single cross hybrids in F5 which were evaluated in an augmented design during kharif of 2010-11.

Five genotypes viz., Line-632, Line-131, Line-642, Line-1151 and Line-1101 had better yields ranging from 8.90 to 21.77 per cent over best check Sahana with mean yields higher than 20.27q/ha. Line-632 had the highest seed cotton yield of 21.70 q/ha which was 21.77 per cent better than Sahana (17.82 q/ha). It also had superior fibre length.

In second part of the study, the diversity generated was assessed through K-means clustering. Seven clusters were formed accommodating the 115 lines. The second step was to employ a simple method called ‘Path-of-productivity’ analysis to identify the different paths the top 12 lines took towards producing higher yields. As expected, they did have differences in their paths to higher yield attributable to their differential genetic makeup. In addition, these 12 genotypes fell in five different clusters identified in the previous step. Considering both tests, 10 genotypes were finally identified to be included in a diallel to pave way for hybrid research. Lines- 632, 131, 642, 1151, 11101, 1081, 531, 391, 8141, and 12111 were the chosen genotypes.

INTRODUCTION

Genetic diversity is at the heart of all plant breeding activities. Crossing over and recombination among the chromosomes of a heterozygote leads to the formation of genetically dissimilar gametes. Such gametes of two heterozygotes can be brought together when we use F1 hybrids as parents of a double cross. Creating and harnessing novel genetic diversity through such conventional means is one method of obtaining superior segregants. In the present study, the F1 hybrids which served as parents of the double crosses were chosen from the different cotton growing zones of India in the hope that geographical diversity would contribute to the diverseness of the hybridization material. Greater the genetic diversity better would be the release of variability in the segregants. In the later generations (say F4/F5), where these desirable segregants are fairly stabilized, they can be evaluated against checks. Productive segregants are isolated in each generation via individual plant selection. After extensive yield performance trials, the new genotypes can be released as new varieties. Freom here starts the next activity. The genetic variability created can be harnessed for heterosis breeding. The new genotypes can be subjected to diversity analysis and diverse groups can be identified from which genotypes can be picked for hybridization. A method called ‘Path-of-Productivity’ has been described and now, can be used in conjunction with diversity analysis to identify genotypes that can serve as parents of new hybrids. The parents can be brought together in a diallel cross to identify superior hybrids. These hybrids will again help in embarking upon a fresh cycle of recombination and creation of diversity.

2

Creating Novel Diversity and using Comprehensive Methods for Their Further Use in Hybrid 9


Six intra-hirsutum hybrids of cotton were identified from the All India Coordinated Crop Improvement Project trials during 2005-06 and were used as parents in producing double crosses and a three-way cross in 2006-07. From 2007-08 onwards, individual plant selections were made based on productivity and fibre properties in each generation till 2009-10. One hundred and fifteen plants belonging to different crosses were identified in 2009-10 for evaluation during 2010-11. These hundred and fifteen genotypes in F4/F5 were obtained through individual plant selection (IPS) from five double crosses, one three –way cross and six single cross (parents) hybrids. The details are given in Tables 1 and 2. These 115 genotypes were evaluated in augmented design with five check varieties during kharif 2010-11 at Agricultural Research Station, Dharwad to identify productive genotypes. Analysis of variance (ANOVA) for augmented design–II (Federer, 1977) for all characters was carried out separately. Parameters based on the mean performance of the varieties and also parameters of genetic variability for the different traits were obtained. GCV and PCV values were calculated as per Burton (1951) and heritability (broad sense) was obtained as per Johnson et al., (1955). Selection efficiency reflected in genetic advance and GAM was assessed as per Johnson et al., (1955). In the present study, a simple method called ‘Path-of-productivity’ (Rajesh Patil et al., 2007), used earlier in arboreum cotton with some degree of success, has been outlined which helps in finding out differences in the trait contributions to the final yield of a genotype. If two such genotypes with different paths to productivity are hybridized one can expect hybrid vigour as there could be underlying genetic differences responsible for their differing path-of-productivity. As an adjunct to this, conventional genetic diversity analysis can be done to decide upon the genotypes to be chosen as parents in a hybridization program. Diversity generated was assessed through K-means clustering using Systat software. The most productive 12 lines were considered for ‘path-of-productivity’ analysis. The 10 lines, selected after the ‘path-of-productivity’ analysis, were allocated to their respective clusters to see if they fell in diverse clusters. Together, the methods can identify parents amenable to a hybridization program.

TABLE 1: HYBRIDS FROM AICCIP TRIALS AND THEIR PERFORMANCE FEATURES ACROSS THE THREE COTTON GROWING ZONES OF INDIA DURING 2005-06 THAT SERVED AS PARENTS OF THE DOUBLE CROSSES

Hybrid North Zone (6 Locations) Central Zone (7 Locations) South Zone (6 Locations)

Seed

Cot

ton

Yie

ld (k

g/ha

)

Fibr

e L

engt

h (m

m)

Fibr

e St

reng

th

(g/te

x)

S:L

Rat

io

Seed

Cot

ton

yiel

d (k

g/ha

)

Fibr

e L

engt

h (m

m)

Fibr

e St

reng

th

(g/te

x)

S:L

Rat

io

Seed

Cot

ton

yiel

d (k

g/ha

)

Fibr

e le

ngth

(m

m)

Fibr

e st

reng

th

(g/te

x)

S:L

rat

io

GSHH-2201 1284 26.40 20.40 0.77 2060 26.90 21.40 0.80 2127 30.20 23.00 0.76 VBCH-2312 1669 30.30 21.90 0.72 1808 30.80 24.10 0.78 1988 29.70 24.40 0.82 CHATRAPATHI 1148 33.10 25.70 0.78 1977 33.30 25.40 0.76 1882 32.80 22.90 0.70 BCHH-1232 1430 31.30 22.20 0.71 2046 29.80 22.70 0.76 2235 32.00 22.50 0.70 JKCH-2022 1228 29.60 22.10 0.75 2103 31.10 22.80 0.73 2709 32.10 22.80 0.71 RATNA 1265 29.70 20.60 0.69 1970 32.70 24.00 0.73 2056 29.50 24.50 0.83

Note: S:L ratio is the fibre strength to length ratio, a combined parameter to judge fibre property

TABLE 2: LIST OF COTTON GENOTYPES DERIVED FROM DOUBLE AND SINGLE CROSS HYBRIDS INCLUDED FOR EVALUATION AT ARS DHARWAD DURING KHARIF 2010-11

Entry No F4 progeny of Cross Progenies Entry No F5 Progeny of Cross Progenies Double Cross Hybrids Single Cross Hybrids

DC-1. GSHH-2201 × RATNA 10 DC-7 GSHH-2201 6 DC-2. VBCH-2312 × RATNA 3 DC-8 VBCH-2312 13 DC-3. CHATRAPATHI × RATNA 17 DC-9 CHATRAPATHI 9 DC-4. BCHH-1232 × RATNA 4 DC-10 BCHH-1232 8 DC-5. JKCH-2022 × RATNA 11 DC-11 JKCH-2022 14

Three-way Cross Hybrids DC-12 RATNA 12 DC-6. RCR 4 x RATNA 7

Note: Altogether, a total of 115 progenies/genotypes were evaluated.


RESULTS AND DISCUSSION

The genotypes were evaluated in augmented design for productivity traits and also for fibre properties. The ANOVA revealed that the variability generated in the experimental material across all the traits was larger. The various genetic parameters have been given in Table 3. The top five genotypes viz., DC-632, DC-131, DC-642, DC-1151 and DC-1101 were superior to the zonal and local check, Sahana, in both yield as well as fibre properties. The performance of selected superior genotypes against the two released check varieties across seed cotton yield and fibre traits has been given in Table 6. Genotypes DC-632 (2170 kg/ha), DC-131 (2064 kg/ha) and DC-642 (1993 kg/ha) were superior to checks Sahana (1782 kg/ha) and RAH-100 (1457 kg/ha). Superiority in fibre length (23.93 % over Sahana in DC-391) and fibre strength (20.08 % over RAH-100 in DC-11101) has been recorded. Genotype DC-632 apart from having a yield superiority of 17.89 per cent over best check was also superior for the fibre properties. Another genotype DC-771 had a fibre length of 31.30 mm and strength of 25.50 g/tex.

TABLE 3: VARIABILITY PARAMETERS FOR DIFFERENT MORPHOLOGICAL CHARACTERS AMONG SINGLE AND DOUBLE CROSS DERIVED LINES AT ARS DHARWAD DURING KHARIF 2010-11

Var

iabi

lity

Para

met

ers

Plan

t Hei

ght (

cm)

Num

ber

of M

onop

odia

Num

ber

of S

ympo

dia

Sym

podi

al L

engt

h at

50

% P

lant

Hei

ght

Num

ber

of N

odes

per

Pl

ant

Inte

r B

oll D

ista

nce

(cm

)

Stem

Dia

met

er

(cm

)

Num

ber

of B

olls

Per

pl

ant

Bol

l Wei

ght (

g)

Num

ber

of S

eeds

Per

Bol

l

Seed

Inde

x (g

)

Lin

t Ind

ex

(g)

GO

T

(%)

Hal

o L

engt

h (m

m)

Seed

Cot

ton

Yie

ld

(g/p

lant

)

Mean 97.20 2.10 22.10 49.40 24.00 7.30 1.20 4.40 4.40 27.70 8.70 4.70 35.30 29.10 19.30 Maximum 140.50 4.00 37.00 70.00 39.00 10.00 1.90 13.10 7.30 35.80 10.00 6.10 39.60 37.80 39.10 Minimum 70.00 0.90 15.40 33.00 17.40 3.80 0.70 1.10 1.70 20.40 6.50 3.40 30.20 21.10 4.30 Vg 105.87 0.06 4.81 17.25 5.85 0.22 0.01 0.49 0.01 1.41 0.48 0.23 2.79 7.55 23.18 Vp 160.68 0.38 11.65 46.85 12.20 0.95 0.08 2.86 0.62 7.77 0.72 0.40 4.86 8.65 59.80 PCV 13.04 29.28 15.44 13.86 14.55 13.37 24.01 38.46 17.95 10.07 9.74 13.52 6.25 10.11 40.07 GCV 10.59 11.86 9.92 8.41 10.08 6.37 9.13 15.84 2.38 4.28 7.95 10.23 4.73 9.44 24.94 h²bs(%) 65.89 16.40 41.30 36.82 47.95 22.69 14.46 16.98 1.76 18.11 66.57 57.18 57.46 87.22 38.76 GA (%) 17.20 0.21 2.90 5.19 3.45 0.46 0.09 0.59 0.03 1.04 1.16 0.75 2.61 5.29 6.17 GAM (%) 17.70 9.89 13.14 10.51 14.38 6.25 7.15 13.45 0.65 3.76 13.36 15.93 7.39 18.16 31.99

TABLE 4: PATH-OF-PRODUCTIVITY ANALYSIS IN THE 12 MOST PRODUCTIVE GENOTYPES OF THE 115 NEW GENOTYPES PRODUCED AND EVALUATED

Mean Values of 12 Most Productive Genotypes for 16 Traits Genotypes 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

DC-632 39.07 105.10 3.00 22.80 24.40 50.00 28.80 8.80 1.50 6.30 6.20 3.60 1.50 32.60 34.84 48.26 DC-131 37.15 82.90 1.50 16.80 17.80 47.20 24.60 7.20 1.44 13.10 2.84 14.90 2.20 34.80 34.17 34.70 DC-642 35.88 106.60 1.00 18.90 21.30 54.00 27.80 7.80 1.30 7.32 4.90 4.30 1.70 32.90 34.91 60.95 DC-1151 35.47 99.50 2.20 21.00 23.00 51.00 27.00 7.20 1.00 6.20 5.72 7.40 4.20 33.80 43.69 22.26 DC-1101 34.95 101.30 2.40 19.20 20.20 50.20 24.80 8.00 1.56 6.70 5.22 14.50 2.30 34.50 37.54 51.30 DC-11101 31.65 103.50 2.10 23.40 25.40 51.00 30.00 6.60 1.10 5.70 5.55 7.60 5.20 34.80 37.71 16.26 DC-1081 31.47 92.30 2.40 19.40 21.40 47.00 28.00 7.80 1.10 5.70 5.52 1.90 1.10 35.20 37.12 34.90 DC-531 31.00 86.40 2.20 16.10 18.30 46.00 30.00 7.60 1.10 9.20 3.37 17.60 4.00 31.70 38.24 43.00 DC-391 30.95 82.40 1.80 22.00 23.00 49.20 31.00 7.30 1.78 6.80 4.55 18.70 4.00 34.80 34.79 54.00 DC-8141 30.93 95.10 3.30 19.60 22.00 49.00 29.60 7.70 1.10 6.50 4.76 3.70 1.30 34.10 38.10 114.62 DC-1131 30.39 92.80 1.80 20.00 22.00 48.00 29.00 8.10 1.00 8.20 3.71 15.10 4.10 34.70 38.70 23.78 DC-12111 29.80 108.00 2.10 23.60 25.80 48.00 29.00 6.70 0.80 5.70 5.23 9.30 5.20 38.00 36.78 44.90 Group Mean 33.23 96.33 2.15 20.23 22.05 49.22 28.30 7.57 1.23 7.29 4.80 9.88 3.07 34.33 37.22 45.74 Overall Mean 19.21 97.15 2.22 22.10 23.96 49.45 28.16 7.29 1.22 4.39 4.36 9.32 2.81 34.83 37.10 52.07

The per se performance and per cent deviation values of the top 12 genotypes from the overall mean for all traits have been given in Table-4&5. Twelve genotypes were considered for ‘path-of-productivity’ analysis as the mean seed cotton yield of these 12 genotypes was higher than the two checks. The group mean of the 12 genotypes was higher than the overall mean for 60 per cent of the traits. Important traits like seed cotton yield, number of bolls, boll weight and photosynthesis had above average expression. Negative but desirable expression was seen in plant height, number of monopodia and length of sympodium at 50 per cent plant height. The per cent deviations across the contributing traits, showed differences among the genotypes. These differences can safely be assumed to be arising out of genetic

Creating Novel Diversity and using Comprehensive Methods for Their Further Use in Hybrid 11

differences among the lines. All the 12 genotypes were high yielding but had different paths to productivity owing to differential gene architecture. The differences among the path to productivity of the 12 genotypes, when 2 lines are compared against each other at a time, shows that lines DC-1101 and DC-1131 showed less than 50 per cent difference with other lines. Both these lines can be conveniently dropped from any hybridization programme. The other 10 lines viz., DC-391, DC-531, DC-642, DC-131, DC-1151, DC-1081, DC-11101, DC-632, DC-12111 and DC-8141 can be used to set up a diallel crossing set which will help ultimately to identify superior hybrids. The line DC-632 can be crossed to any of these three lines viz., DC-131, DC-1081 or DC-531 as all the three pairs of parents showed more than 60 per cent trait difference between the parents of the cross. Using the ‘path-of-productivity’ can thus lead to proper choice of parents for a planned production of hybrids.

TABLE 5: MEAN DEVIATIONS OF TOP GENOTYPE VALUES FROM OVERALL MEAN ACROSS ALL TRAITS

Genotypes 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 DC-632 103.38 8.18 35.14 3.17 1.84 1.11 2.27 20.71 22.95 43.51 42.24 -61.37 -46.62 -6.40 -6.09 -7.32 DC-131 93.39 -14.67 -32.43 -23.98 -25.71 -4.55 -12.64 -1.23 18.03 198.41 -34.96 59.87 -21.71 -0.09 -7.90 -33.36DC-642 86.78 9.73 -54.95 -14.48 -11.10 9.20 -1.28 7.00 6.56 66.80 12.39 -53.86 -39.50 -5.54 -5.90 17.06 DC-1151 84.64 2.42 -0.90 -4.98 -4.01 3.13 -4.12 -1.23 -18.03 41.23 31.21 -20.60 49.47 -2.96 17.76 -57.26DC-1101 81.94 4.27 8.11 -13.12 -15.69 1.52 -11.93 9.74 27.87 52.62 19.64 55.58 -18.15 -0.95 1.19 -1.48 DC-11101 64.76 6.54 -5.41 5.88 6.01 3.13 6.53 -9.47 -9.84 29.84 27.35 -18.45 85.05 -0.09 1.64 -68.78DC-1081 63.82 -4.99 8.11 -12.22 -10.68 -4.95 -0.57 7.00 -9.84 29.84 26.63 -79.61 -60.85 1.06 0.05 -32.98DC-531 61.37 -11.07 -0.90 -27.15 -23.62 -6.98 6.53 4.25 -9.84 109.57 -22.72 88.84 42.35 -8.99 3.07 -17.42DC-391 61.11 -15.18 -18.92 -0.45 -4.01 -0.51 10.09 0.14 45.90 54.90 4.39 100.64 42.35 -0.09 -6.23 3.71 DC-8141 61.01 -2.11 48.65 -11.31 -8.18 -0.91 5.11 5.62 -9.84 48.06 9.14 -60.30 -53.74 -2.10 2.70 120.12DC-1131 58.20 -4.48 -18.92 -9.50 -8.18 -2.93 2.98 11.11 -18.03 86.79 -15.00 62.02 45.91 -0.37 4.31 -54.33DC-12111 55.13 11.17 -5.41 6.79 7.68 -2.93 2.98 -8.09 -34.43 29.84 19.91 -0.21 85.05 9.10 -0.86 -13.77Group Mean 72.96 -0.85 -3.15 -8.45 -7.97 -0.47 0.50 3.80 0.96 65.95 10.02 6.04 9.13 -1.45 0.31 -12.15

Note: Group mean is of 12 genotypes and overall mean is of 115 genotypes

To make this simple test for diversity assessment more comprehensive, the conventional cluster analysis through K-means was also performed. The cluster details are presented in Table-7. The ten genotypes picked up on the basis of ‘path-of-productivity’ analysis fell in 5 different clusters showing their diverse genetic make-up. This analysis also proves the genetic diversity existing among the ten lines which can be used in a hybridization set-up based on the ‘path-of-productivity’ analysis. The parents of each of the three pairs of crosses suggested above also belonged to different clusters making them ideal parents for a heterotic cross.

INDEX FOR THE 16 DIFFERENT TRAITS

1 Seed Cotton Yield (g/plant)

5 Number of Nodes Per Plant

9 Stem diameter (cm) 13 Transpiartion Rate (µmol of H2Om²S¯¹)

2 Plant height(cm) 6 SL at 50% plant height(cm)

10 Number of bolls 14 Leaf temperature (0c)

3 Monopodia per plant

7 Angle of sympodium at 50% plant height (deg)

11 Boll weight (g) 15 Chlorophyll content(mg/gm fresh weight) of leaf)

4 Sympodia per plant 8 Inter boll distance (cm) 12 Photosynthesis (µmol of CO2 m² S¯¹ )

16 RWC (%)

TABLE 6: PERFORMANCE SUPERIORITY OF SELECTED GENOTYPES OVER TWO CHECKS ACROSS YIELD AND FIBRE PROPERTIES

% Improvement over Sahana % Improvement over RAH-100 Seed Cotton Yield (kg/ha) Seed Cotton

Yield Fibre

Length Fibre

Strength Seed Cotton

Yield Fibre

Length Fibre

Strength For Both Seed Cotton Yield and Fibre Properties

DC-632 17.89 13.59 8.48 32.83 9.06 11.16 2170 DC-642 10.56 13.59 8.48 26.87 9.06 11.16 1993

For Fibre Properties Only DC-11101 -1.34 10.70 17.67 17.09 6.02 20.08 -- DC-391 -3.50 23.93 11.26 15.22 19.90 13.85 -- Mean values of checks Sahana RAH-100

1782 kg/ha 26.70 mm 20.50 g/tex 1457 kg/ha 28.10 mm 19.90 g/tex --


TABLE 7: THE SEVEN CLUSTERS SHOWING THE DIVERSITY OF THE TEN GENOTYPES SELECTED ON THE BASIS OF PATH-OF-PRODUCTIVITY

Clusters Number of Genotypes Genotypes Selected on the Basis of Path-of-Productivity I 20 DC-391, DC-531 II 20 DC-642 III 18 DC-131, DC-1151, DC-1081, DC-11101 IV 26 DC-632, DC-12111 V 5 -- VI 10 DC-8141 VII 16 --

REFERENCES [1] Burton, G.W., (1951). Quantitative inheritance in pearlmillet (Pennisetum glaucum S. and H.). Agron., 43:404-417. [2] Federer, W. T., (1977). Experimental design; Theory and Application. McMillan, New York. [3] Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimates of genetic and Environmental Variability in soybean.

Agron., 47:314-318. [4] Rajesh, S. Patil, Shreekant S. Patil, Rashmi, Bhuvaneshwargouda, R. Patil and Khadi, Basavaraj M. (2007). ‘Path-of-

Productivity’ – A method to handle genetic material using F1s in cotton (Gossypium arboreum L.). Proceedings of World Cotton Research Conference – 4, Lubbock, Texas, USA.

New Cotton Germplasm as an Intermediate Cycle Called SP 48114 Development by the National

Institute of Agricultural Technology–INTA

A. Tcach Mauricio, A.F. Poisson, Ivan Bonacic, Silvia Ibalo, Alex Montenegro, Daniel Ojeda and Mariano Cracogna

Estación Experimental Agropecuaria INTA Sáenz Peña, Chaco, Argentina

Abstract—Cotton in Chaco, Argentina, is grown under rainfed conditions. The availability of water during flowering determines the retention of fruiting structures. Better performance depends mainly on water availability during the reproductive phase. In varieties with short cycle, the losses due to stress are the most and is becoming necessary to develop varieties as intermediate types helps to compensate losses due to stress at flowering. The objective of this investigation was to select cotton with intermediate habit and agronomic traits equivalent to early types. From the F2 populations of a cross between lines SP 99138 x SP 99035 in 1994/1995 season, selection was made by visual observation and an individual plant was obtained. The selection plant was named as SP48114 after following pedigree method of breeding. During 2004/2005 the elite population was part of a network regional comparative trials conducted at 4 locations for 3 seasons. From the F3 generation onwards it was tested for ginning and the progenies were artificial infected with Xanthomonas axonopodis pv malvacearum. All susceptible plants were discarded. F8 generation was tested for the blue disease caused by cotton leaf roll dwarf virus (CLRDV) through artificial infection and only resistance lines were selected. The line SP 48114 is characterized by greater differentiation of fruiting points on the main stem 5 % more than Guazuncho 3 INTA. This commercial variety has short cycle and high boll retentions in first fruiting branches. The selected line SP 48114 maintains boll retentions in the inferior part of the plant similar to Guazuncho 3 INTA and continued to flower for more days. This feature increases the flowering period for about 10 days and improves the compensation at time of water stress. The fiber parameters viz., fiber length is 29 mm, strength 31 g / tex and lint percentage about 39 to 40.

INTRODUCTION

In Argentina, the main province of cotton-growing area is Chaco, where cotton is grown only under rainfed conditions (SAGPyA, 2009). The precipitation in this area is erratic and irregular during growing season, which increases the risk in the production. It necessiates the research work in the Argentinean cotton industry for improvement in water use efficiency (Payta 2010).

The cotton has xerophytic adaptation, however 53% of the area is cultivated under irrigated conditions in the world (Hearn, 1994). When the cotton plant cross dry conditions, its vegetative grows is terminate, being very difficult to restart vegetative growth and produce more squares and flowers (Hearn 1994). Fryxel (1986) observed various strategies in wild species, of adaptations to arid conditions, life cycle being one of them.

The main objectives of INTA´s programme for cotton breeding is development of varieties with short cycle (Royo et al., 2007). Sekloka et al., 2007 found that varieties with short cycle showed better performance in dry conditions as it may run away to dry period. The problem is that typical sowing date may not run away to dry period. The varieties with short cycle can cluster the flowering and compensate the eventual loss when its peak phase coincides with the stress. Further, flowering can be maintained for more time in varieties with intermediates cycle, without any losses and hence such varieties are to be developed. The objective in this investigation was to select a cotton line with intermediate cycle and agronomic traits equivalent to early materials.

3



The Argentine breeding programme follows the classical pedigree method (Allard 1960; Poisson 2005). From the cross of two different genotypes, the following generations were selfed and individual plants and progeny row selections were carried out from the F2 to successive generations. From the F4 generation onward, the seeds were not selfed and were collected to carry out replicated evaluation trials. In the AES Saenz Peña the germplasm lines were evaluated until the F6 generation. The previous generations were inoculated with the pathogens causing bacterial blight. The F8 were infected with aphids which are vector for virus causing blue disease. After the F7 generation, selected lines were evaluated at four additional localities viz., El Colorado, Reconquista, Colonia Benitez (dryland); and Santiago del Estero (irrigated). Current commercial cultivars were used in all trials for comparison purposes. Several trials in four locations at 3 seasons were conducted. The complete process is shown in the picture No. 1. Trials were planted as a randomized complete block design with four replications in plots of two rows, 10 m long. Plants were separated at a distance of 10 cm. in the row and at one m. between rows. Bolls were hand-picked in each plot to determine the yield. Thirty selected bolls were used to determine GOT by baby ginner lint turnout and using HVI equipped for fiber parameters.

In the last season in 1 meters of row, numbers of fruiting branch and plant height in several trials were also studied. The dates were analysed with Infostat software and averages were separated with test LSD Fisher.


The flow chart for the line development from the F2 populations, the plant that made the progeny row and successive testing generations is show in Fig 1. This material with intermediate cycle finished the process of test in the 2006-2007 season, but is not registered still.

CYCLE

The differentiations of new nodes in the main stem and successive fruit point on fruiting branch were at regular intervals, generating the typical pyramidal shape present in cotton (Hearn 1994). This process can be maintained for more time in SP 48114 compared with Guazuncho 3 INTA, the late variety with short cycle. SP 48114 during 2010-2011showed that ( at 110 days after planting), the growth cycle ended with 2 to 4 more potential fruiting branch than Guazuncho 3 INTA, in addition the final height was 12 to 7 cm more than Guazuncho 3 INTA. Both the parameters are associated with the growth cycle. This feature could allow obtaining better performance in dry conditions. The relative performance is shown in Table 1.

TABLE 1: AGRONOMIC PARAMETERS REGISTERED AT 110 DAYS AFTER SOWING, SEASON 2010-11. PRESIDENCIA ROQUE SÁENZ PEÑA, CHACO. DATAS BY THE SAME LETTER ARE NOT DIFFERENT AT 5% PROBABILITY LEVEL.

Line/ Variety No. of Fruiting Branch Plant Height cm SP 48114 14,25 a 94,25 a SP 8461 12,75 ab 92 ab SP 44825 12,5 ab 74,5 c Poraite INTA 12,1 b 76,7 c Guazuncho 3 INTA 12 b 81,5 bc CV 9,64 10,2

SANITY

The line presented high resistance to bacterial blight caused by Xanthomonas axonopodis pv malvacearum, because in the process of selections it was artificially infected from F3 to F12 (Fig1.). In addition to this process it was also infected with cotton leaf roll dwarf virus (CLRDV) during F8 generations. When the plant developed the symptoms, the resistant lines were selected. The sanitary performance was achieved by INTA´s varieties (Poisson 2002).

New Cotton Germplasm as an Intermediate Cycle Called SP 48114 Development by the National Institute of Agricultural 15

Fig. 1: Process of Breeding Used for Development SP 48114 from Year 1993

YIELD AND FIBER PROPRIETIES

The line was evaluated in several trials from the season 2004-2005 which showed good performance and achieved the first positions in the test in relation to commercial varieties (Royo et al., 2007). During the dry and wet conditions of 2009-2010 and 2010-2011, the line SP 48114 showed better performances than varieties with short cycle (Guazuncho 3 INTA and Poraite INTA). (Table 2 and 3). Both experiments were grown in Presidencia Roque Saenz Peña, Chaco, with four replications each. The differential behaviour can be explained for more possibilities to maintain the process of flowering for more days. Sekloca (et. al., 2007) found that the varieties with intermediate cycle present better performance in medium conditions, related to drought and humidity. The lint turnout % in both experiments for SP 48114 was better (Table 2 and 3). In dry conditions, the fiber length was 1 to 4 mm shorter in SP 48114 in comparision to Guazuncho 3 INTA (Table 2). However, in wet conditions the fiber properties was similar than that of Guazuncho 3 INTA (Table 3).

Thus, it is possible to select lines with more differentiations fruit point at growing stations and maintain similar agronomic parameters as varieties with short cycle.

TABLE 2: LINT YIELD AND QUALITY PARAMETERS FOR PCIA. ROQUE SÁENZ PEÑA, CHACO, 2009-10. THE DATA FROM THE TRIAL WITH 2 COMMERCIAL CULTIVARS, 3 PROMISING LINES, INCLUDING SP 48114. SEASON WITH DRY CONDITIONS DURING FLOWERING. DATE BY THE SAME LETTER ARE NOT DIFFERENT AT 5% PROBABILITY LEVEL

Varieties/ Line Lint Yield (kg/ha) Lint Turnout (%) Length (mm) Strength (g/Tex) Micronaire Index SP 48114 674 a 39,5 a 25,9 ab 28,7 b 4,7 a SP 48666 639 a 38,4 a 25,1b 28,6 b 4,7 a SP 81424 590 a 37,3a 26,05ab 29,8 ab 4,6 a Poraite INTA 452 b 38,1 a 26,6 a 30,4 ab 4,4 a Guazuncho 3 INTA 411 b 39,4 a 26,5 a 31,7 a 4,6 a CV 12,1 6,6 3,3 4,6 11,6

TABLE 3: LINT YIELD AND QUALITY PARAMETERS FOR PCIA. ROQUE SÁENZ PEÑA, CHACO, IN THE YEAR 2010-11. THE DATES FROM THE TRIAL WITH 2 COMMERCIAL CULTIVARS 3 PROMISING

LINE, INCLUDING SP 48114, SEASON WITH WET CONDITIONS. DATE BY THE SAME LETTER ARE NOT DIFFERENT AT 5% PROBABILITY LEVEL

Varieties /line Lint Yield (kg/ha) Lint Turnout (%) Length (mm) Strength (g/Tex) Micronaire Index SP 48114 962 a 41,2 ab 29,3 a 31,3 a 4,7 Poraite INTA 695 b 40,4 b 28,3 a 32,5 a 4,5 SP 48666 645 b 41,2 ab 27,9 b 31,5 a 4,6 Guazuncho 3 INTA 662 c 41,6 a 29,6 b 32,1 a 4,6 SP 6180 494 c 39,3 c 27,2 b 31,6 a 4,5 CV 14,1 1,43 1,74 2,69 4,7

Winter 1993 cross in green house between SP 99138 SP 99035

Season 1993/1994 F1 Generations

Season 1994/1995 F2 Generations Visual Selection of individual Plant

Season 1995/1996 F3 Generations Progeny row

Agronomic characterization and artificial infected with xanthomonas axonopodis pvmalvacearum

Seasons 1996/1997 – 2003/2004 F4-F12 -Generations

Agronomic Testing, artificial infected with xanthomonas axonopodis pv malvacearum andselecting and in F8, artificial infected with cotton leaf rolf duarfvirus (CLRDV) and selecting resistance lines

Seasons 2004/2005 – 2006/2007 Regional comparative trials in 4 locations for 3 seasons


REFERENCES [1] Allard, R. W. (1960). Principles of plant breeding. John Wiley. N.Y. 473 p. [2] Fryxell, P. A. (1986). Ecological adaptations of Gossypium species. pp. 1-7 In Mauney, J.R and Steward, J.McD. (Eds).

Cotton Physiology. The Cotton Foundations, Memphis, TN. [3] Hearn, A. B. (1994). The principles of cotton water relations and their application in management. World Cotton Research

Conference 1:66-92. [4] Paytas, M. (2010). Improving cotton yield under water limiting conditions in Argentina. Repor. ICAC Research Program. [5] Poisson, J. A. F. (2002). Breve historia de la producción de algodón en la Argentina. In: 1923-1 de agosto-2002. De Chacra

Oficial a Estacion Experimental. 79 anos de investigación algodonera en el centro de la provincia del Chaco. Editorial INTA EEA Saenz Pena, Centro Regional Chaco-Formosa.Pag.8

[6] Poisson, J. A. F., Bonacic, I., Royo, O. and Ibalo, Y. S. (2005). Mejoramiento genético de algodón. Ano Agrícola 2004/2005. In: Proyecto Nacional de Algodon. Informe de avance No 1. 2o Reunión anual. Sosa M.A. y O. Peterlin (Ed). Ediciones Instituto Nacional de Tecnología Agropecuaria. Pages 9-11.

[7] Royo, O. M., Poisson Juan, A. F.; Bonacic, I., Montenegro, A., Ibalo, S. I., Mazza, S., and Giménez, L. (2007). Direction of Cotton Breeding in Argentina. In: Proceedings of the World Cotton Research Conference. Lubok Texas

[8] Sekloka, E. And Jacques, L. (2007). Early-compact American and late-vegetative African cotton ideotypes can address the increasing diversity of cropping conditions in Africa. 4 Word Cotton Research.

Introgression of High Fibre Strength Trait to Upland Cotton using Marker-Assisted Selection

Nallathambi Kannan, P. Selvakumar, R. Krishnamoorthy, D. Raja, M. Bhuvaneshwari, V. Subramanian and M. Ramasami

Rasi R and D Centre, Rasi Seeds (P) Ltd., Attur–636102, Tamil Nadu, India

Abstract—Cotton fibre is a basic raw material used in the textile industry. In recent years, changes in spinning technology have resulted in the need of unique and often increased cotton fibre quality, especially fibre strength. In this concern, an attempt was made to improve fibre strength of G. hirsutum by utilizing G. barbadense as donor through Backcross (BC) and Modified Back Cross (MBC) pedigree breeding methods following marker-assisted selection using Simple Sequence Repeats (SSR) markers. The Phenotypic Co-efficient of Variation (PCV), Genotypic Co-efficient of Variation (GCV), heritability and genetic advance was studied in 475 numbers of F2 populations. The result showed fibre strength varied from 18.0 to 36.0 g/tex and 32 % of plants in the population fall under 27.0 to 36.0 g/tex group. The PCV was higher than GCV which shows fibre strength is highly influenced by environment. The moderate heritability and high genetic advance was observed for fibre strength; hence the selection is effective for this trait and the heritability is due to additive genes effect. The identified SSR markers for fibre strength have been utilised to select the high fibre strength plants in each generations. In BC1F1 generation, fibre strength varied from 24.4 to 32.7 g/tex. After continuous selection of high fibre strength plants using molecular markers in each generation, we obtained high productive progenies with high fibre strength that ranged from 30.0 to 35.7 g/tex having more recurrent background genome in BC1F8 generations. High recovery of hirsutum background with high strength and different staple length progenies were obtained in modified backcross population. Thus the high strength hirsutum lines developed will serve as a donor for introgressing the fibre strength to improve the elite parental lines through marker-assisted background selection.

INTRODUCTION Cotton is the most preferred natural fibre in the world and plays a major role in the economy of agriculture and industry. Among the four cultivated species, Gossypium hirsutum is well known for high yield and dominates the world’s cotton fibre production followed by the Gossypium barbadense that is known for superior fibre qualities. In cotton improvement, in addition to yield enhancement of lint, the fibre qualities such as staple length, fibre strength, and fineness and maturity are very important. The demand for improved fibre quality by textile industry will continue. Improvements in textile processing, particularly advances in spinning technology, have led to increased emphasis on breeding cotton for improved fibre characteristics, especially strength. (Rahman and Malik, 2008). The requirements in textile spinning machinery with the adoption of rotor spinning, demands fibres with high strength to meet out spinning productivity. Most of the presently developed cotton varieties have low fibre strength of 18 to 24 g/tex. Genetic variation for the fibre qualities are very limited in most of the currently cultivated Gossypium hirsutum cotton. Thus there is an urgent need to introduce fibre strength characteristics from Gossypium barbadense to upland cotton while maintaining the cotton fibre yield.

Cotton fibre strength trait is governed by several genes located in several loci of chromosomes and are inherited quantitative way and thus influenced by quantitative trait loci (QTLs). Most traits in breeding programs are quantitatively inherited, complicating their manipulation through phenotypic and/or genomic approaches. Each of the QTLs has relatively small effects and is influenced by genotype and environment showing strong GxE interaction, which leads to low genetic advance in cotton improvement (Kohel, 1999ab).

Cotton fibre strength trait is governed by several genes located in several loci of chromosomes and are inherited quantitative way and thus influenced by quantitative trait loci (QTLs). Most traits in breeding programs are quantitatively inherited, complicating their manipulation through phenotypic and/or genomic approaches. Each of the QTLs has relatively small effects and is influenced by genotype and environment showing strong GxE interaction, which leads to low genetic advance in cotton improvement (Kohel, 1999ab).

4


The modified backcross method followed for pyramiding of multiple traits is one of the ways by which the inherent fibre strength trait can be transferred to an upland cotton elite line. Experiments in cotton showed the negative linkage between yield and fibre traits and following modified backcross (MBC) is expected to circumvent this effect. However, due to several QTLs involved for both yield and fibre traits, the breeding cycle is expected to be longer.

The identification and utilization of molecular markers make it possible for plant breeders to find a rapid and precise approach of marker-assisted selection (MAS) of desirable plants with target traits. Introgressing the traits of interest can be followed using molecular markers that are mapped flanking or tightly linked with the traits being incorporated. Following the advancement of MAS and MBC method, it is expected to have selection for both recurrent parent background as well as genes to be introgressed from non-recurrent parent. The use of MAS facilitates a faster introgression since plants can be sampled and genotypes with target traits can be identified even at the early stage of development. Among the available types of molecular markers, microsatellite markers simple sequence repeats (SSR) have shown to be the most adequate for breeding programs due to their co-dominance and multi-allelic characteristics, and for their ability to automate the process.

The main objective of the study has been to improve fibre strength of G. hirsutum by introgression of QTLs associated with fibre strength from G. barbadense by means of backcross (BC) and modified backcross (MBC) pedigree breeding methods using fibre strength QTL SSR markers. Thus a combination of MBC with MAS for selection of desirable cotton lines with enhanced yield and high fibre strength was followed in our breeding strategy.

The present investigation was also undertaken to study the phenotypic and genotypic coefficient of variability, phenotypic and genotypic variances, heritability and genetic advance of the variation existed in F2 and F3 population originated from the inter-specific crosses in cotton.


In the present study, the field experiments were conducted at the Rasi Seeds (P) Ltd., Research Farm, Attur, Salem (District) Tamil Nadu state (INDIA).

The salient features of parents involved in the backcross and modified backcross are furnished in Table 1. The breeding scheme, number of plants raised and number of plants selected in each generation of backcross and modified backcross are shown in Figs. 1 to 4. The experiments were raised in the winter season (August – February). All the recommended cultural practices of cotton production in the area were done periodically.

TABLE 1: SALIENT FEATURES OF PARENTS INVOLVED IN THE STUDY

Parents Species Used as Boll Weight (g)

Ginning % Span Length (mm)

Lint Index Fibre Strength (g/tex)

Fineness (Mic)

Uniformity Ratio

RC 64 G. hirsutum Recurrent

Medium (4.0-4.8)

Medium (33-36)

Long (30-32)

Medium 4.5-5.5

Medium (24-26)

Medium (4.0-4.2)

Excellent (47-49)


Medium to Big (4.9-5.6)

Low (31-33)

Extra Long(33-35)

Medium 4.0-5.0

Strong (26 – 28g/tex)

Fine (3.3-3.7)

Excellent (47-48)


Medium to Big (4.8-5.8)

Low (30-32)

Extra Long(34-36)

Medium 4.0-5.0

Strong (25-27)

Fine (3.5-3.8)

Excellent (47-48)


Big (5.3-6.0)

Medium (33-35)

Extra Long (33-35)

Medium 4.0-5.0

Medium (24-25)

Fine (3.5-3.7)

Excellent (47-49)

RC 45SB G. barbadense Donor Small (2.8-3.7)

Low (25 -28)

Extra Long(37-40)

Medium 4.0-5.0

Very Strong (33-36)

Very Fine (2.8-3.1)

Excellent (48-50)

Phenotypic Characters

Selected plants in each single plant progeny were observed and their biometrical and fibre quality traits were recorded. The genetic analysis for the traits such as boll weight (g), Number of bolls/plant, ginning percentage (GP %), lint index (LI), seed index (SI), single plant yield (g) and fibre quality parameters

Introgression of High Fibre Strength Trait to Upland Cotton using Marker-Assisted Selection 19

were done in the F2 population along with their parents. The fibre quality traits viz., 2.5% span length (mm), uniformity ratio (%), fibre fineness (micronaire), fibre strength (g/tex) and elongation were estimated by High Volume Instrument USTER® HVI Spectrum in ICC mode.

Fig. 1: The Breeding Scheme, Number of Plants Raised and Number of Plants Selected Based on MAS in the Backcross Population

Fig. 2: The Breeding Scheme, Number of Plants Raised and Number of Plants Selected Based on MAS in the Modified Backcross Population (I)

First G.hirsutum (RC64) x G.barbadense (RC45SB)Season2002(W) Identification of polymorphic markers of both parents (658 markers were screened and 454 were pol

Second G.hirsutum (RC 64 ) x F1Season F1 backcross with the recurrent parent2003(W)

475 F2 individuals were rasied and genotyping were done with 158 polymorphic markers based on low and high Third BC1F1 1. 276 plants were raisedSeason 2. 15 high fibre strength plants with more recurrent background were selected 2004(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Fourth BC1F2 1. Individual 15 plant progenies were grown. (40 plants/progeny)Season 2. 8 high fibre strength plants with more recurrent background were selected 2005(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Fifth BC1F3 1. Individual 8 plant progenies were grown. (21 plants/progeny)Season 2. Homozyous progenies similar to recurrent2006(S) parent with high fibre strength 17 plants were selected based on phenotypic and genotypic data (MAS)

3.Recurrent plant type with high fibre strength plants will be forwarded from superior progenies

Sixth BC1F4 1. Individual 17 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2006(W) parent with high fibre strength 67 plants were selected based on phenotypic and genotypic data (MAS)


Seventh BC1F5 1. Individual 67 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2007(W) parent with high fibre strength 82 plants were selected based on phenotypic and genotypic data (MAS)


Eighth BC1F6 1. Individual 82 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2008(W) parent with high fibre strength 148 plants were selected based on phenotypic and genotypic data (MAS)


Ninth BC1F7 1. Individual 148 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2009(W) parent with high fibre strength 54 plants were selected based on phenotypic and genotypic data (MAS)


Tenth BC1F8 1. Individual 54 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2010(W) parent with high fibre strength 36 plants was selected and forwarded



475 F2 individuals were rasied and genotyping were done with 158 polymorphic markers based on low and high Third RC 62 X BC1F1 1. 276 plants were raisedSeason 2.More G.hirsutum plant type with high fibre strength plants2004(W) to be crossed with G.hirsutum recurrent parent(RC62)

Fourth MBC1F1 1. 309 plants were raisedSeason 2. High fibre strength plants with more recurrent background were selected 2005(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Fifth MBC1F2 1. Individual 305 plants were raisedSeason 2. 71 high fibre strength plants with more recurrent background were selected 2006(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Sixth MBC1F3 1. Individual 71 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2007(W) parent with high fibre strength 44 plants were selected based on phenotypic and genotypic data (MAS)


Seventh MBC1F4 1. Individual 44 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2008(W) parent with high fibre strength 17 plants were selected based on phenotypic and genotypic data (MAS)


Eighth MBC1F5 1. Individual 17 plant progenies were grown. (10 plants/progeny)Season 2. Homozyous progenies similar to recurrent2009(W) parent with high fibre strength 25 plants were selected based on phenotypic and genotypic data (MAS)


Ninth MBC1F6 1. Individual 25 plant progenies were grown. (10 plants/progeny)Season 2. Homozyous progenies similar to recurrent2010(W) parent with high fibre strength 27 plants were selected and forwarded


Fig. 3: The Breeding Scheme, Number of Plants Raised and Number of Plants Selected in the Modified Backcross Population (II)

Fig. 4: The Breeding Scheme, Number of Plants Raised and Number of Selected Based on MAS in the Modified Backcross Population (III)

Mean values were used for different statistical analysis. Analysis of variance and genotypic and phenotypic variation were calculated following Singh and Chaudhury (1985). Phenotypic coefficient of variation (GCV), Genotypic coefficient of variation (PCV) were estimated using the formula suggested by Burton (1952), while genetic advance (GA) as percent means and genetic advance as percentage of mean (GA %) was estimated by the formula given by Lush (1949) and Johnson et al. (1955). The estimates of broad-sense heritability were computed as suggested by Allard (1960).




Fourth MBC1F1 1. 260 plants were raisedSeason 2. High fibre strength plants with more recurrent background were selected 2005(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation*

Fifth MBC1F2 1. Individual 432 plants were raisedSeason 2. 51 high fibre strength plants with more recurrent background were selected 2006(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation*





Eighth MBC1F5 1. Individual 23 plant progenies were grown. (10 plants/progeny)Season 2. Homozyous progenies similar to recurrent2009(W) parent with high fibre strength 33 plants were selected based on phenotypic and genotypic data (MAS)


Ninth MBC1F6 1. Individual 33 plant progenies were grown. (10 plants/progeny)Season 2. Homozyous progenies similar to recurrent2010(W) parent with high fibre strength plants 20 were selected based on phenotypic and genotypic data (MAS)




Fourth MBC1F1 1. 281 plants were raisedSeason 2. High fibre strength plants with more recurrent background were selected 2005(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Fifth MBC1F2 1. Individual 251 plants were raisedSeason 2. 14 high fibre strength plants with more recurrent background were selected 2008(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation






Genotyping using SSR Markers F2 mapping populations were developed from the interspecific cross between G.hirsutum (RC 64) and G.barbadense (RC 45SB) for the identification of SSR markers associated with fibre strength trait. Young leaf samples were collected from 475 F2 individuals and DNA was extracted using modified Davis protocol. PCR was conducted in a total volume of 10 μl with 10 ng of cotton DNA, 1 x PCR buffer (without MgCl2), 1.5 mM MgCl2, 0.1 μM dNTPs, 0.2 μM of each primer and 0.5 units of Taq DNA polymerase. The cycling conditions for PCR were as follows: 5 min for 94° C; 35 cycles of 94°C for 45 s, 57°C for 45 s, 72°C for 60 s; 72°C for 5 min; 4°C for preservation. Amplified DNA fragments were resolved in 6% denatured polyacrylamide gel [(acryl amide: bisacrylamide (19:1)] and stained with silver nitrate.

We employed 658 SSR primers including BNL, NAU, JESPR and CIR etc., for the identification of polymorphism between the two parents. The polymorphic primers were used to screen the bulked low and high fibre strength DNA samples and selected primers were subsequently used to genotype the F2 individuals. Only unambiguous distinct bands were scored. QTLs for cotton fibre strength in F2 population were identified using MAPMAKER 2.0 and QTL CARTOGRAPHER (version 1.15) respectively. The SSR markers associated with the fibre strength QTL were used in the backcross and modified backcross breeding program.

Genotyping the BC and MBC Samples Marker-assisted selection was conducted for every generation of backcrossing and modified backcrossing with the markers associated with fibre QTLs based on the F2 population. The markers covering the fibre strength QTLs that were used in MAS are RAS 72, RAS 158, RAS 215, RAS 223, RAS 224, RAS 230, RAS 306 and RAS 304.The selection of plants with high fibre strength trait at every generation was based on the markers and phenotypic data.

RESULTS AND DISCUSSION The first and foremost criterion to be considered in any breeding programme is the magnitude of the genetic variability present in the base population which is prime requirement for starting a judicious breeding programme for combining desirable characters into the elite lines. In the present investigation the estimates of mean, range, phenotypic and genotypic coefficients of variation, heritability and genetic advance as per cent of mean in F2 generation are calculated and presented in Table 2. There were large differences in the variances for most of the characters under study. The high variance (10.2) of fibre strength character in F2 population indicates that the presence of sufficient amount of variability which had been generated in segregating populations (Pradeep and Sumalini, 2003). The distribution of fibre strength in F2 generations is given in Fig. 6. The distribution range of fibre strength in F2 was between 18 g/tex to 36 g/ tex. The 27% of plants out of 475 plants showed moderate fibre strength (26-28 g/tex). Furthermore, 3 plants in F2 showed above 34 g/tex which was higher than the donor parent, suggesting transgressive segregation for the trait. The variation and transgressive segregation observed for fibre strength has practical implication for combining fibre strength in upland cotton.

TABLE 2: THE ESTIMATES OF MEAN, RANGE, HERITABILITY, GENETIC ADVANCE, GENETIC ADVANCE PER CENT OF MEAN, PCV AND GCV OF F2 GENERATION (RC 64 X RC 45 SB)

Characters Mean Range Variance Heritability (h2 %) GA GA% of Mean PCV % GCV% Boll Weight (g) 3.3 1.9-4.6 0.4 84.5 1.3 39.1 19.0 17.5 Number of bolls/plant 67.5 32.0-127.0 445.8 46.9 43.5 64.4 31.3 21.4 Ginning percentage (%) 29.5 22.5-38.7 9.3 56.1 6.3 21.3 10.3 7.7 Lint index 3.8 1.9-6.6 0.6 8.9 1.6 41.5 20.1 6.0 Seed index 9.2 5.4-14.0 2.4 15.1 3.2 34.3 16.7 6.5 2.5% span length (mm) 32.5 26.1-38.1 6.3 83.1 5.2 15.9 7.7 7.0 Fibre strength (g/tex) 43.7 40.6-47.5 10.2 59.1 6.6 24.0 11.6 9.0 Uniformity ratio 27.4 18.4-36.1 1.7 78.4 2.7 6.1 3.0 2.6 Elongation 5.6 4.0-12.0 0.7 65.8 1.7 30.5 14.8 12.0 Micronaire 2.8 2.0-4.2 0.2 39.6 0.9 31.3 15.2 9.6 Seed cotton yield (g)/plant 152.5 82.3-266.7 2482.5 30.1 102.6 67.3 32.7 17.9

Although range can provide a preliminary idea about the variability but coefficient of variation is reliable as it is independent of unit of measurement. The extent of variability as measured by PCV and GCV also gives information regarding the relative amount of variation.


Fig. 5: Frequency Distribution of Fibre Strength Trait in F2 Population (475 Plants)

The estimates of phenotypic coefficients of variation (PCV) ranged from 2.98 for fibre uniformity ratio to 32.68 % for seed cotton yield per plant and the corresponding values for genotypic coefficients of variation (GCV) were 2.64 % for fibre uniformity ratio and 21.83 % for number of bolls per plant (Table 2). The phenotypic coefficient of variation which measures total variation was found to be greater than genotypic coefficient of variation for all the characters indicating some degree of environmental influence on the traits.

It is not the magnitude of variation but the extent of heritable variation, which matters most for achieving gains in selection programme. The coefficient of variation indicates only the extent of variation for a character and does not discriminate the variability into heritable and non-heritable portion. The heritability worked out in broad sense would suggest how far the variation is heritable and selection is effective. A perusal of heritability estimates indicated that the characters such as boll weight, fibre length, uniformity ratio and fibre elongation have high heritability (Table 2). Such high heritability estimates have been found to be helpful in making selection of superior genotypes on the basis of phenotypic performance for quantitative characters. The characters viz., number of bolls per plant, ginning percentage, fibre strength, mircronaire and seed cotton yield per plant had moderate heritability. Though the heritability estimates are the true indicators of genetic potentiality of the genotypes which can be used as a tool for selection, changes in the values of the heritability due to fluctuations of the environmental factors detract for total dependence on such estimates. However, heritability estimates when considered in conjunction with the predicted genetic gain form a reliable tool for selection. They indicate the expected genetic advance of a character in response to the certain selection pressure imposed on them and also provide an idea about the gene action involved in the expression of various polygenic traits involving several QTLs.

High heritability coupled with high genetic advance as per cent of mean was noticed for the characters boll weight and elongation. This indicates that additive gene action was responsible for the inheritance of these traits and the selection in the early generation could be fruitful in improving these characters (Kumaresan, et. al., 2000). In contrast the characters lint index and seed index have low heritability and high genetic advance as per cent of mean. The fibre strength character has moderate heritability and high genetic advance as per cent of mean indicates that success through simple selection could be expected in the early generation as this trait is having the additive gene action.

Marker-Assisted Selection (MAS) using Simple Sequence Repeats (SSR)

Based on limited DNA polymorphism in upland cotton for markers available to date, and limited application of markers for cotton improvement, sound MAS breeding strategy is important for incorporating QTLs associated with fibre traits are successfully used in crop improvement. We have screened 658 SSR primers for the identification of polymorphism between the two parents. Of the 658 primer, 454 primers were polymorphic between the parents, 158 primers were polymorphic between bulked low and high fibre strength samples (Fig. 6). Subsequently 158 polymorphic primers obtained in

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F2

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TABLE 3: THE ESTIMATES OF MEAN, RANGE AND VARIANCE OF BACKCROSS POPULATIONS (RC 64 X (RC 64 X RC45 SB)

Generation Number of bolls/Plant

Boll Weight (g)

Ginning Percentage (%)

Lint Index

Seed Index

2.5% Span Length (mm)

Fibre Strength (g/tex)

Uniformity Ratio

Elongation Micronaire

BC1F1 Mean 58.0 3.8 31.8 5.0 10.7 35.1 27.2 48.9 6.1 3.5 Range 16.0-185.0 2.5-5.5 22.1-38.6 2.3-7.6 5.5-19.2 30.3-38.3 24.4-32.7 43.3-54.4 3.6-9.9 2.4-5.1 Variance 584.1 0.4 7.1 0.7 3.7 2.6 4.9 5.4 1.9 0.3








RC 64 (Recurrent Parent)

Mean 143.0 5.5 33.3 6.4 12.9 31.6 24.1 47.8 5.4 6.7

RC 45SB (Donor Parent)

Mean 127.0 3.6 28.4 4.7 12.0 38.0 33.1 49.7 2.8 4.8

The introgression of fibre strength character into upland cotton utilizing Gossypium barbadense as donor through back cross and modified back cross method was done in the present investigation. Since the fibre strength trait is controlled by several QTLs, the introgression was done by one back cross followed by pedigree method. The mean, range and variance of observed characters for back cross generations are given in the Table 3. The mean values of fibre strength in all the backcross generations (BC1F1 - BC1F8) indicates that the progenies are having high fibre strength (>27 g/tex). The high fibre strength plants in each back cross generations were selected based on phenotypic selection coupled with genotypic selection utilizing identified fibre strength linked SSR markers. The high fibre strength plants with recurrent parent background were selected by utilizing molecular markers and phenotypic data. The distribution range of fibre strength in backcross population (Fig. 9) reveals that in each generation the number of plants fall under the high fibre strength group has been increased by the effective selection of combining phenotypic and genotypic information. In BC1F1 generation the frequency of plants fall under high fibre strength (>30g/tex) is 14 per cent while in the BC1F8 generation the frequency is 60 per cent. Furthermore in BC1F8 generation, the fibre strength values were ranged from 26.9 to 35.7 g/tex and seven plants were having highest fibre strength values of above 34 g/tex. The high fibre strength plants in the advance generations are have high phenotypic similarities to the recurrent parent type and thus the molecular markers are effectively used in the selection of target alleles with high background of recurrent parent.


Fig. 9: Frequency Distribution of Fibre Strength Trait in Backcross Generations

The modified backcross method has been used for pyramiding the multiple traits into upland cotton besides the introgression of fibre strength traits. The three upland cotton lines namely RC 62, RC 67 and RC 92 were utilized as recurrent parent and high fibre strength BC1F1 plants were used as donor plant to develop a three modified back cross population (Figs. 2- 4) The advantage of this proposed modified backcross breeding method was to obtain the more recurrent genome background with high fibre strength as the frequency of the undesirable genes from the donor parents was reduced similar to the reported by Li and Pan, 1990.

TABLE 4: THE ESTIMATES OF MEAN, RANGE AND VARIANCE OF MODIFIED BACKCROSS (I) POPULATIONS

Generation Number of Bolls/Plant

Boll Weight (g)


Lint Index

Seed Index



Uniformity Ratio


MBC1F1 Mean 90.1 4.6 31.1 5.0 11.1 35.6 26.5 44.7 4.8 3.4 Range 56.0-154.0 3.1-5.9 25.8-36.1 3.7-6.0 8.5-

14.1 32.2-38.4 25.0-28.6 43.2-46.6 3.6-6.0 2.6-4.1

Variance 501.1 0.5 5.6 0.4 1.6 2.4 0.5 0.6 0.3 0.2 MBC1F2 Mean 85.4 3.6 31.7 4.5 9.5 32.8 27.1 45.5 5.5 3.1

Range 19.0-176.0 2.1-5.6 2.2-42.4 2.9-6.9 3.55-14.4

29.1-37.5 25.7-30.1 42.8-47.2 4.2-7.2 1.8-4.7


Range 56.0-135.0 2.8-5.4 25.6-39.9 3.8-6.3 7.5-14.4

28.3-38.1 25.9-30.8 42.0-47.2 4.1-7.1 2.6-4.4


Range 45.0-142.0 2.0-6.5 23.4-37.7 2.9-7.0 6.3-14.4

28.7-36.2 25.0-29.9 41.9-47.3 5.0-8.3 2.4-5.3


Range 68.0-116.0 2-5.5 24.7-46.0 3.6-6.9 5-14.25

30.6-35.8 25.7-31.8 44.0-47.2 4.3-6.5 2.6-4.5


Range 19.0-122.0 2.9-5.9 21.4-36.9 4.1-7.4 8.35-16.86

29.2-35.2 25.2-32.3 44.0-47.9 4.6-6.8 2.9-5.1

Variance 457.3 0.3 3.4 0.4 1.8 2.1 1.9 0.6 0.2 0.1 RC 64 (Recurrent Parent)

Mean 143.0 5.5 33.3 6.4 12.9 31.6 24.1 47.8 6.7 5.4


Mean 66.0 4.9 31.3 5.9 12.9 37.2 28.5 47.2 5.9 3.8


Mean 127.0 3.6 28.4 4.7 12.0 38.0 33.1 49.7 2.8 4.8

0102030405060708090

100

18‐20

20‐22

22‐24

24‐26

26‐28

28‐30

30‐32

32‐34

34‐36

36‐38

Freq

uency in %

Range

BC1F1

BC1F2

BC1F3

BC1F4

BC1F5

BC1F6

BC1F7


In the modified backcross generations the high fibre strength has been improved significantly. The mean, range and variance of fibre strength for modified back cross generations are given in the Table 4 to 6. The fibre strength values of modified backcross generations ranged from 27.2 to 37.6 g/tex in MBC1F4 (III), 25.3 to 32.4 g/tex in MBC1F6 (I) and 24.4 to 32.8 g/tex in MBC1F6 (II). The marker based selected advanced progenies in the modified backcross generations are having uniform high fibre strength with high similar phenotypic characters of the recurrent parents. The selected high strength progenies were grouped into different staple length group in order to meet out the textile industry requirement of various counts.

TABLE 5: THE ESTIMATES OF MEAN, RANGE AND VARIANCE OF MODIFIED BACKCROSS (II) POPULATIONS


Boll Weight (g)


Lint Index

Seed Index

2.5% span Length (mm)


Uniformity Ratio


MBC1F1

Mean 92.7 4.6 32.2 5.3 10.9 36.3 44.5 26.9 5.2 3.6 Range 38.0-178.0 3.8-6.5 28.7-36.2 4.3-6.3 5.8-13.3 33.0-39.7 43.2-46.0 26.0-29.3 4.4-7.5 3.0-4.5 Variance 921.6 0.4 3.6 0.3 2.2 3.4 0.5 0.7 0.4 0.2

MBC1F2


MBC1F3


MBC1F4


MBC1F5


MBC1F6


RC 64 (Recur-rent Parent)

Mean 143.0 5.5 33.3 6.4 12.9 31.6 24.1 47.8 6.7 5.4

RC 67 (Recur-rent Parent)

Mean 93.0 5.0 31.8 5.9 12.6 37.0 27.3 47.7 3.3 6.1


Mean 127.0 3.6 28.4 4.7 12.0 38.0 33.1 49.7 2.8 4.8

TABLE 6: THE ESTIMATES OF MEAN, RANGE AND VARIANCE OF MODIFIED BACKCROSS (III) POPULATIONS


Boll Weight (g)


Lint Index

Seed Index



Uniformity Ratio


MBC1F1


MBC1F2 Mean 97.0 4.1 34.2 5.5 10.6 33.3 27.4 45.8 4.8 4.9 Range 75.0-124.0 2.0-6.1 28.0-40.4 3.6-7.8 7.4-14.4 0.5-36.6 26.0-30.7 43.6-47.9 2.7-7.7 2.6-9.2 Variance 270.9 0.7 6.9 0.8 2.8 1.7 1.2 0.8 1.5 3.2

MBC1F3 Mean 74.3 4.2 33.7 5.6 10.9 31.0 29.1 46.9 5.4 4.0 Range 50.0-111.0 2.5-6.0 29.9-38.6 3.1-7.6 7.3-14.4 25.9-36.2 25.8-33.7 44.7-49.9 4.5-6.3 2.5-5.5 Variance 151.5 0.6 5.6 0.8 2.2 4.2 3.0 1.5 0.2 0.6

MBC1F4

Mean 51.5 4.2 33.1 5.8 11.7 31.3 31.4 46.7 5.4 4.9 Range 18.0-98.0 2.6-6.8 26.7-45.3 2.6-7.9 5.9-17.1 26.8-41.3 27.2-37.5 42.7-49.3 4.2-7.4 3.4-5.6

Variance 228.0 0.5 4.7 0.5 2.2 3.3 2.8 0.9 0.3 0.2 Table 6 (Contd.)…


…Table 6 Contd.


Mean 143.0 5.5 33.3 6.4 12.9 31.6 24.1 47.8 6.7 5.4


Mean 78.0 5.6 34.6 7.6 14.3 35.8 28.4 49.2 6.6 3.6


Mean 127.0 3.6 28.4 4.7 12.0 38.0 33.1 49.7 2.8 4.8

The application of DNA markers in backcross breeding program is dependant by the precision of associated markers as well as by the cost effectiveness of marker-assisted selection. Marker-assisted selection was found useful in developing genotypes with combinations of favourable alleles. The main reasons supporting the utilization of molecular markers in cotton breeding programs are the 100% heritability of the markers and their lower cost. Hence, the molecular markers were used in a backcrossing scheme to improve the fibre strength traits in upland cotton efficiently.

Further to the present investigation the selected BC1F8 and MBC1F6 plants will be forwarded to the next generation. The progeny test row may be conducted to select the best uniform high yielding progenies with high fibre strength. Thus the developed introgressed high fibre strength upland cotton line can be utilized for introgressing the fibre strength to improve the available elite parental lines through marker assisted background selection to develop high fibre strength hybrids.

REFERENCES [1] Allard, R.W. 1960. Principles of Plant Breeding. New York: John Willy and Sons, Inc. [2] Burton, G.M. 1952. Quantitative inheritance in grasses. Proc. 6th Int. Grassland Cong., 1: 277-283. [3] Chen, H., N. Qian., W.Z. Guo., Q.P. Song., B.C. Li., F.J. Deng., C.G. Dong and T.Z. Zhang (2009). Using three

overlapped RILs to dissect genetically clustered QTL for fibre strength on Chro.D8 in Upland cotton. Theor. Appl. Genet., 119: 605–612.

[4] Dudley, J.W. and R.H. Moll.1969. Interpretation and use of estimates of heritability and genetic variances in plant breeding. Crop. Sci., 9(3):257-262.

[5] Johnson, H. W., H.F. Robinson and R.E. Comstock. 1955. Genotypic and phenotypic correlation in soybean and their implications in selection. Agron. J., 47 : 477-483.

[6] Kohel, R.J.1999a. Cotton Improvement: A Perspective. Cotton World 1: (in press). [7] Kohel, R.J.1999b. Cotton germplasm resources and the potential for improved fibre production and quality, In: A.S. Basra

(Ed.), Cotton fibres, pp. 167–182. The Haworth Press, Inc, NY. [8] Kumaresan, D., J. Ganesan and S. Ashok. 2000. Genetic analysis of qualitative characters in cotton (Gossypium hirsutum

L.). Crop Res. Ind., 19: 481-484. [9] Lacape, J.M., T.B. Nguyen, B. Courtois, J. L. Belot, M. Giband, J. P. Gourlot, G. Gawryziak, S. Roques and B. Hau. 2005.

QTL analysis of cotton fibre quality using multiple Gossypium hirsutum x Gossypium barbadense backcross generations. Crop. Sci., 45: 123-140.

[10] Li, W.H and J.J. Pan. 1990. Effect of modified backcross in breeding upland cotton cultivars. J. Nanjijng. Agri. univ., 13: 232-235.

[11] Lush, J.N. 1949. Animal breeding plans. The collegiate Press. Amer. Iowa Ed. 3. [12] Pradeep, T. and K. Sumalini. 2003, Impact of mating systems on genetic variability in segregating generation of Asiatic

cotton (Gossypium sp.). Indian J. Genet., 63 : 143-147. [13] Rahman,

S

and T.A. Malik. 2008. Genetic analysis of fibre traits in cotton. Int. J. Agri. Biol., 10: 209–212.

[14] Singh, R.K and B.D. Chawdhury. 1985. Biometrical methods in quantitative genetic analysis, Kalyani Publications, New Delhi.

[15] Zhang, H.B., Y. Li., B. Wang and P.W. Chee.2008. Recent advances in cotton genomics. Int. J. Plant. Genomics., 2008: 742304.

Estimation of Genetic Parameters for Yield and Fibre Quality Traits in Inter-Specific

Crosses of Cotton (Gossypium spp.)

Gunasekaran Mahalingam, Krishnasamy Thiyagu and Nagasamy Nadarajan

Department of Cotton, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore–641003 India

Abstract—To study the nature and magnitude of gene effects for seed cotton yield and fibre quality traits in cotton (Gossypium spp), the generation mean analysis was carried out using the following four crosses of different cotton cultivars: SVPR 2 × Suvin, SVPR 2 × Barbados, TCH 1218 × Suvin and TCH 1218 × Barbados. The P1, P2, F1, F2, B1 and B2 of these generations were studied for yield and fibre quality traits. The analysis showed the presence of additive, dominance and epistatic gene interactions for these characters. Duplicate type epistasis played a greater role than complementary epistasis. To harness the additive gene action, simple selection procedures or pedigree method of breeding is sufficient. Heterosis breeding procedures are effective in harnessing dominance gene action to the full extent. When additive and dominant gene actions are pre-dominant, the bi-parental mating design or reciprocal recurrent selection can be used for further recombination of alleles to produce desirable segregants.

INTRODUCTION

Cotton is an important natural fibre crop of global importance grown commercially in about 111 countries with a global area of 30.29 million hectares accounting for 105.06 million bales (217.724 kgs) of production with a productivity of 755 kg/ha. In India, cotton is cultivated in an area of nearly 10.17 million hectares which is the largest in the world, with a production of 29.20 million bales (2009-10) ranking second next to China. Cotton plays a key role in the national economy by way of its contribution in trade, industry, employment and foreign exchange earnings. The average productivity of cotton in India is the lowest among cotton-growing nations of the world.

Though India is a pioneer in cultivation of hybrids on a commercial scale, the productivity of cotton has been practically stagnant during last few years. In order to increase the yield potential, it is desirable to efficiently utilize the available genetic variability. Genetic analysis of quantitative traits further helps to elucidate the nature and magnitude of genetic variation present in the population. The estimates of gene effects in a plant improvement programme have a direct bearing upon the choice of breeding procedure to be followed. Additive gene effects are useful in the development of pure lines whereas dominance and epistatic effects can be used to exploit hybrid vigour. In tetraploid cotton, various studies have been conducted to study the nature and magnitude of gene effects in the inheritance of different quantitative characters and involvement of both additive and non-additive gene effects have been reported by many workers (Nadarajan et al., 1999; Patel et al., 2007). In the present investigation, additive dominance and epistatic gene effects were estimated by Generation mean analysis for yield and fibre quality traits in four inter-specific crosses involving G. hirsutum and G. barbadense and suggest suitable breeding methods for genetic improvement of cotton.


The genetic materials used in this study consisted of two each of G. hirsutum and G. barbadense genotypes namely SVPR 2 and TCH 1218; and Suvin and Barbados respectively. Two G. hirsutum genotypes have good combiner, good adaptability, jassid resistance, drought tolerance and higher yield and the remaining two G. barbadense genotypes have good fibre length, strength and fineness. The experiment was performed with a set of six generations viz., P1, P2, F1, F2, B1 and B2 in four cross combinations viz., SVPR 2 × Suvin (cross 1), SVPR 2 × Barbados (cross 2), TCH 1218 × Suvin (cross 3)

5

Estimation of Genetic Parameters for Yield and Fibre Quality Traits in Inter-Specific Crosses of Cotton (Gossypium spp.) 29

and TCH 1218 × Barbados (cross 4) to study the presence of interaction effects in governing the traits of seed cotton yield and yield attributes and fibre quality traits. The F1 plants were randomly chosen from each cross and used as male parent for back crossing programme, whereas the concerned parents of each cross were used as female parents to produce B1 (P1 × F1) and B2 (P2 × F1) progenies. Simultaneously, F2 seeds were produced by selfing F1 plants. All these generations were produced during two cropping seasons and, as such, all the six generations had to be grown together during the same cropping season.

The F1, F2, B1 and B2 generations of the four crosses were raised along with their parents in a randomized block design (RBD) with two replications during winter 2008–09 at Department of Cotton, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore. Four different crosses were randomized in a block followed by different generations within each cross. The spacing was 90 × 60 cm. Ten plants in a row is same for all the generations of each crosses but the number of rows varied as two rows each for non-segregating population such as P1, P2 and F1; 40 rows for F2 and 20 rows for each of B1 and B2. Since the non-segregating generations represent the homogeneous population while the segregating generations represent the heterogeneous population the sample size (i.e. number of plants analyzed) varied as 20 plants for P1, P2 and F1, 400 plants for F2 and 200 plants in each of B1 and B2. The recommended agronomic practices and need-based plant protection measures were followed to obtain good crop stand. Observations were recorded on number of bolls per plant (NB), boll weight (g) (BW), seed cotton yield per plant (SCY), ginning percentage (%) (GP), 2.5 per cent span length (mm) (SL) and bundle strength (g/tex) (BS).

The generation means were calculated by taking the average over all the replications for each generation. The variance and the corresponding standard errors of the means were calculated from the deviations of the individual values from the pooled mean for each of the generation for every cross. To test the adequacy of the additive-dominance model the individual scaling test given by Mather (1949) as well as joint scaling test by Cavalli (1952) were applied. First, simple additive-dominance model consisting of mean [m], additive [d] and dominance [h] gene effects was tried and the adequacy of the model was tested statistically by examining the goodness of fit between the estimated generation means and the observed generation means from the above three parameters for three degrees of freedom. Wherever the data failed to fit the simple additive dominance non-epistatic-model, the analysis was proceeded further by perfect fit estimate of the six parameters m, [d], [h], additive × additive [i], additive × dominance [j] and dominance × dominance [l] on the assumptions of an additive dominance model with digenic interactions as proposed by Jinks and Jones (1958).


The mean of the six generations with four crosses for six traits are presented in Table 1, with the mean values for the scaling, joint scaling and their interaction effects being presented in Table 2.

Among the parents, P1 generation showing higher performance for boll weight, ginning percentage and seed cotton yield per plant in all the crosses except TCH 1218 × Barbados, where P2 mean was higher for seed cotton yield per plant. With respect to 2.5 per cent span length and bundle strength, P2 was superior than P1 in all the four crosses. Among the different generations all the F1’s performed better for number of bolls per plant and seed cotton yield per plant. With regard to 2.5 per cent span length and bundle strength, F1 mean was lower than the greater parent in all the crosses. Among the segregating generations of F2, B1 and B2, the B1 generation showed higher mean performance in all the crosses for all the traits except 2.5 per cent span length and bundle strength were B2 showed its superiority over B1 generations.

A simple additive dominance model was non-adequate as inferred the significance of any one of the scales and joint scaling test. Hence, an epistatic digenic interaction model was found to be fit for all the six traits. The additive, dominance and epistatic types of gene interaction in each cross for different trait were found to be different from each other.


TABLE 1: MEAN VALUES OF DIFFERENT CHARACTERS OVER SIX GENERATIONS IN SIX CROSSES OF COTTON

Characters and Generations

SVPR 2 × Suvin SVPR 2 × Barbados TCH 1218 × Suvin TCH 1218 × Barbados

Number of Bolls Per PlantP1 26.90 ± 0.50 25.50 ± 0.43 24.70 ± 0.56 23.70 ± 0.56 P2 20.70 ± 0.37 27.80 ± 0.42 16.20 ± 0.53 28.70 ± 0.54 F1 41.70 ± 0.54 45.70 ± 0.73 28.90 ± 0.64 40.80 ± 0.84 F2 23.64 ± 0.31 22.41 ± 0.32 19.69 ± 0.29 26.75 ± 0.38 B1 24.63 ± 0.44 27.00 ± 0.51 20.58 ± 0.39 27.34 ± 0.56 B2 22.77 ± 0.50 25.07 ± 0.50 20.33 ± 0.40 29.42 ± 0.58

Boll Weight (g)P1 4.82 ± 0.09 4.74 ± 0.06 4.68 ± 0.08 4.84 ± 0.05 P2 4.13 ± 0.06 4.01 ± 0.05 4.09 ± 0.04 4.07 ± 0.04 F1 3.73 ± 0.03 3.71 ± 0.05 4.57 ± 0.05 4.55 ± 0.05 F2 2.79 ± 0.04 3.08 ± 0.03 2.77 ± 0.04 3.66 ± 0.04 B1 3.02 ± 0.06 3.44 ± 0.05 3.37 ± 0.05 3.73 ± 0.05 B2 2.74 ± 0.06 2.86 ± 0.04 2.61 ± 0.04 3.51 ± 0.05

Seed Cotton Yield Per PlantP1 104.65 ± 3.32 100.76 ± 2.34 100.37 ± 2.87 95.14 ± 2.21 P2 61.28 ± 2.41 96.53 ± 2.06 56.28 ± 2.28 96.99 ± 1.17 F1 134.97 ± 2.64 149.38 ± 2.92 114.16 ± 2.80 169.78 ± 3.45 F2 50.31 ± 1.19 60.36 ± 1.44 45.49 ± 1.21 81.74 ± 1.92 B1 60.99 ± 1.93 83.60 ± 2.29 54.12 ± 1.60 90.36 ± 2.56 B2 47.38 ± 1.87 62.75 ± 2.06 42.69 ± 1.47 87.73 ± 2.76

Ginning Percentage (%)P1 36.97 ± 0.40 36.31 ± 0.33 34.87 ± 0.47 34.06 ± 0.62 P2 33.77 ± 0.47 32.87 ± 0.32 30.56 ± 0.32 33.99 ± 0.45 F1 33.29 ± 0.35 32.00 ± 0.37 34.07 ± 0.57 33.22 ± 0.38 F2 30.22 ± 0.20 31.54 ± 0.19 30.44 ± 0.17 30.78 ± 0.17 B1 32.93 ± 0.33 33.94 ± 0.30 31.25 ± 0.22 32.75 ± 0.23 B2 29.68 ± 0.29 31.55 ± 0.28 31.67 ± 0.23 30.80 ± 0.26

2.5% Span Length (mm)P1 25.46 ± 0.36 25.36 ± 0.31 30.00 ± 0.42 30.06 ± 0.49 P2 37.28 ± 0.32 34.56 ± 0.29 37.08 ± 0.40 34.54 ± 0.28 F1 34.20 ± 0.24 33.56 ± 0.25 36.26 ± 0.42 35.10 ± 0.37 F2 30.34 ± 0.26 29.49 ± 0.23 31.25 ± 0.35 31.45 ± 0.24 B1 28.47 ± 0.45 28.18 ± 0.38 31.19 ± 0.53 31.28 ± 0.40 B2 34.94 ± 0.16 31.96 ± 0.38 33.60 ± 0.42 32.16 ± 0.38

Bundle Strength (g/tex)P1 18.36 ± 0.21 18.22 ± 0.10 21.18 ± 0.33 21.18 ± 0.33 P2 27.12 ± 0.15 26.94 ± 0.29 27.20 ± 0.15 26.86 ± 0.27 F1 24.26 ± 0.26 25.00 ± 0.35 24.36 ± 0.41 24.70 ± 0.41 F2 22.49 ± 0.26 21.90 ± 0.20 22.91 ± 0.51 23.44 ± 0.23 B1 20.83 ± 0.39 21.06 ± 0.32 21.19 ± 0.66 22.23 ± 0.30 B2 25.48 ± 0.39 25.39 ± 0.33 25.18 ± 0.54 25.50 ± 0.41

Number of Bolls Per Plant

Among the genetic effects, the mean effect was higher in SVPR 2 × Suvin and TCH 1218 × Barbados. The additive effect (d) was found to be positively significant in SVPR 2 × Suvin and TCH 1218 × Suvin, while dominance effect (h) was positive in SVPR 2 × Barbados and TCH 1218 × Barbados. This indicated the pre-dominance of both additive and dominance main effects. In case of interaction effects, the dominance × dominance was positively significant for all the crosses, while the additive × additive interaction effect was positive for all the crosses and significantly positive in SVPR 2 × Barbados and TCH 1218 × Barbados. The additive × dominance effect was negatively significant in TCH 1218 × Suvin and positively significant in SVPR 2 × Barbados. The signs of (h) and (l) were opposite in SVPR 2 × Suvin and TCH 1218 × Suvin, while in the same direction in SVPR 2 × Barbados and TCH 1218 ×


Barbados. This indicated the presence of both complementary and duplicate epistasis for this trait. In general, both additive and dominance main effects, predominant of dominance × dominance and additive × additive interaction effects along with both complementary and duplicate dominance epistasis were noticed for number of bolls per plant. Shanti (1998), Esmail et al. (1999) and Ramalingam and Sivasamy (2003) reported additive, dominance × dominance and additive × additive interaction effects for this trait.

TABLE 2: SCALING TEST AND GENETIC EFFECTS FOR DIFFERENT CHARACTERS IN FOUR CROSSES OF COTTON

Cross A B C D JST m (d) (h) (i) (j) (l) 1 2 3 4 SCY C1 ** ** ** * ** 67.46**

± 7.47 21.69* ±

2.05 -36.10** ±

19.91 15.51* ±

7.19 -8.08* ±

3.38 203.61** ± 13.54

-6.27 157.79 227.20 DE

C2 ** ** ** ** ** 47.36** ± 8.58

2.12 ± 1.56

-50.04* ± 22.47

51.28** ± 8.44

18.74** ± 3.45

152.06** ± 15.13

-23.66 52.16 222.08 DE

C3 ** ** ** - ** 66.67** ± 6.77

22.04** ± 1.83

-132.19** ± 17.38

11.65 ± 6.51

-10.62** ± 2.84

179.68** ± 12.00

-6.00 154.23 201.95 DE

C4 ** ** ** ** ** 66.83** ± 0.82

-0.93 ± 1.25

-43.31 ± 27.79

29.24** ± 0.75

3.56 ± 3.97

146.27** ± 18.43

46.67 44.24 179.07 DE

NB C1 ** ** ** - ** 23.57**

± 1.84 3.10** ±

0.31 -17.84** ±

4.82 0.23 ± 1.82

-1.25 ± 0.74

35.97** ± 3.19

-5.75 20.94 37.45 DE

C2 ** ** ** ** ** 12.14** ± 1.95

-1.15** ± 0.30

7.49 ± 5.15

14.51** ± 1.92

3.08** ± 0.78

26.06** ± 3.52

-6.52 8.64 43.65 CE

C3 ** ** ** - ** 17.40** ± 1.67

4.25** ± 0.39

-2.33 ± 4.32

3.05 ± 1.62

-4.00** ± 0.68

13.84** ± 2.95

-0.55 6.58 20.89 DE

C4 ** ** ** ** ** 19.67** ± 2.26

-2.50** ± 0.39

7.18 ± 5.90

6.53** ± 2.22

0.42 ± 0.89

13.95** ± 4.02

-2.87 9.68 20.9 CE

BW C1 ** ** ** - ** 4.12** ±

0.22 0.34** ±

0.06 -4.94** ±

0.58 0.36 ± 0.21

-0.06 ± 0.10

4.55** ± 0.37

-14.53 5.28 4.98 DE

C2 ** ** ** - ** 4.09** ± 0.19

0.36** ± 0.04

-3.66** ± 0.49

0.28 ± 0.18

0.22** ± 0.08

3.28** ± 0.32

-10.17 4.02 3.78 DE

C3 ** ** ** ** ** 3.50** ± 0.20

0.29** ± 0.05

-4.01** ± 0.51

0.88** ± 0.20

0.47** ± 0.08

5.08** ± 0.33

-13.83 4.30 6.43 DE

C4 ** ** ** - ** 4.63** ± 0.21

0.39** ± 0.03

-3.79** ± 0.55

-0.18 ± 0.21

-0.18* ± 0.08

3.71** ± 0.36

-9.72 4.18 4.07 DE

GP C1 ** ** ** ** ** 31.03**

± 1.23 1.60** ±

0.31 -5.49 ±

3.24 4.34** ±

1.19 1.65** ±

0.54 7.75** ±

2.15 -3.43 7.09 13.74 DE

C2 - * ** ** ** 29.76** ± 1.13

1.72** ± 0.23

4.86 ± 2.97

4.83** ± 1.10

0.67 ± 0.47

-2.62 ± 1.99

2.83 6.58 8.13 DE

C3 ** - ** ** ** 28.63** ± 0.97

2.15** ± 0.28

1.79 ± 2.54

4.08** ± 0.93

-2.57** ± 0.42

3.65** ± 1.92

0.83 3.94 10.3 CE

C4 * * ** ** ** 31.03** ± 1.23

1.60** ± 0.31

-5.49 ± 3.24

4.34** ± 1.19

1.65** ± 0.54

7.75** ± 2.15

-3.43 7.09 13.74 DE

*Significant at 5% level, **Significant at 1% level; C1–SVPR 2×Suvin; C2–SVPR 2×Barbados; C3 –TCH 1218×Suvin; C4–TCH 1218×Barbados; A, B, C, D–Scales; JST–Joint scaling test; m–mid parent; (d)–additive; (h)–dominance; (i)–additive × additive; (j)–additive × dominance; (l)–dominance × dominance; 1–h/d; 2–Total main effect; 3–Total interaction effect; 4–Type of epistasis; CE– Complementary Epistasis; DE–Duplicate Epistasis

Boll Weight

Among the genetic effects estimated, the additive main effect (d) was pre-dominant and showed positively significant values in all crosses and was greater than dominance effects (h) where negatively significant interaction effect was noticed in all the crosses. The dominance × dominance interaction effect (l) was found to be positively significant in all crosses. The additive × dominance interaction effect (j) was positively significant in SVPR 2 × Barbados and TCH 1218 × Suvin, while additive × additive interaction was positively significant in TCH 1218 × Suvin. Duplicate dominance epistasis was confirmed in all the crosses due to the opposite signs of (h) and (l). On the whole, additive gene effects and epistatic effects, especially of dominance × dominance and additive × dominance type were found to


govern this trait along with duplicate type of epistasis. This is in conformity with the results of Sandhu et al. (1992). Rajendra Kumar and Raveendran (2001) reported the presence of additive effects for boll weight. Ramalingam and Sivasamy (2003) expressed dominance × dominance and additive × dominance interaction effect for this trait.

Seed Cotton Yield Per Plant

The perusal of six generations using generation mean analysis indicated that additive gene effects were prevalent for majority of the crosses viz., SVPR 2 × Suvin, SVPR 2 × Barbados and TCH 1218 × Suvin. In SVPR 2 × Suvin and TCH 1218 × Suvin, additive effect was positively significant. The dominance effect (h) was negatively significant in all the crosses except TCH 1218 × Barbados which had negative effect. The dominance × dominance interaction effect (l) was pre-dominant in all the crosses where it was positively significant followed by additive × additive effect which was also positively significant in all the crosses except TCH 1218 × Suvin. The additive × dominance interaction effect (j) was positively significant in SVPR 2 × Barbados and negatively significant in SVPR 2 × Suvin and TCH 1218 × Suvin. The signs of (h) and (l) were opposite in direction in all the crosses. This indicated that seed cotton yield per plant was found to be governed by additive gene effects and interaction effects pre-dominantly of dominance × dominance type followed by additive × additive with duplicate type of epistasis. All the three types of interaction for this trait were reported by Singh and Chahal (2004) and Singh et al. (2008). Shanti (1998) reported additive effect while Esmail et al. (1999) reported additive × additive gene interactions but Jagtap (1995) reported both type of gene actions for this trait.

Ginning Percentage

Among the genetic effects estimated, interaction effects were witnessed in all crosses. In these crosses, the additive genetic effect was positive in TCH 1218 × Barbados and significantly positive in rest of the crosses viz., SVPR 2 × Suvin, SVPR 2 × Barbados and TCH 1218 × Suvin, while the dominance gene effects (h) was found to be positive in SVPR 2 × Barbados and TCH 1218 × Suvin and negative in SVPR 2 × Suvin and TCH 1218 × Barbados. The additive × additive interaction effect was found to be positively significant in all the crosses. The additive × dominance effect (j) was positively significant in SVPR 2 × Suvin and TCH 1218 × Barbados and positive for SVPR 2 × Barbados. The dominance × dominance effect (l) was positively significant in SVPR 2 × Suvin and TCH 1218 × Suvin, positive in TCH 1218 × Barbados and negative in SVPR 2 × Barbados. The signs of (h) and (l) were dissimilar in all crosses except TCH 1218 × Suvin. Hence it appears that, the additive effect along with all the three types of interaction with duplicate dominance epistasis existed pre-dominantly for ginning percentage. Panchal et al. (1994) reported the presence of additive, additive × additive, additive × dominance and dominance × dominance interactions for ginning percentage. Rajendra Kumar and Raveendran (2001) and Shanti (1998) reported additive gene effects and Sandhu et al. (1992) reported all the three types of epistasis gene interactions.

Per Cent Span Length

The mean effect estimated by the perfect fit method for digenic interactions in all the crosses was highly and positively significant. The interaction effects were witnessed in all crosses. In these crosses, the dominance genetic effect was positive in SVPR 2 × Barbados and TCH 1218 × Suvin, positively significant in SVPR 2 × Suvin and negative in TCH 1218 × Barbados, while the additive gene effect (d) was found to be negatively significant in all the four crosses. The additive × additive interaction effect was found to be positively significant in SVPR 2 × Suvin and TCH 1218 × Suvin and positive for the rest of the crosses. The additive × dominance (j) and dominance × dominance effect (l) were positively significant for TCH 1218 × Barbados, positive for SVPR 2 × Barbados and TCH 1218 × Suvin and negative for SVPR 2 × Suvin. Hence it appears that, the dominance effect along with additive × additive gene action followed by additive × dominance and dominance × dominance gene action with duplicate and complementary epistasis exists for 2.5 per cent span length. Mehetre et al. (2003) reported the


presence of dominance, additive × additive and dominance × dominance interaction for 2.5 per cent span length. Thangaraj et al. (2002) and Singh and Chahal (2004) reported additive, dominance and duplicate epistasis for 2.5 per cent span length.

Bundle Strength

The mean effect was positively significant and higher than other genetic effects. The interaction effects were witnessed by significance of scale C in all crosses. The dominance effect (h) was positively significant in SVPR 2 × Barbados and positive for SVPR 2 × Suvin and TCH 1218 × Barbados and negative in TCH 1218 × Suvin. The additive effect (d) was negatively significant in all crosses. The additive × additive effect (i) was positive in all the crosses except SVPR 2 × Barbados, where it was positively significant. The additive × dominance effect (j) was positive in SVPR 2 × Barbados and negative in SVPR 2 × Suvin, TCH 1218 × Suvin and TCH 1218 × Barbados. The dominance × dominance interaction effect (l) was negative in SVPR 2 × Suvin and SVPR 2 × Barbados and positive for rest of the crosses. The signs of (h) and (l) were opposite in all crosses except TCH 1218 × Barbados indicating the presence of duplicate dominance epistasis. To conclude, this trait was controlled by dominance gene effects and interaction effects mainly of additive × additive with duplicate dominance type of epistasis. Mehetre et al. (2003) reported additive, dominance and additive × additive gene effects. Hendawy et al. (1999) reported additive and additive × additive with duplicate type of epistasis for this trait.

CONCLUSION

The gene action analyzed through generation mean analysis indicated that both additive and dominance gene effects were found to control most of the important yield contributing and fibre quality traits viz., number of bolls per plant, boll weight, seed cotton yield per plant and ginning percentage, while dominance gene action was prevalent for the traits viz., 2.5 per cent span length and bundle strength. One or more type of epistatic interaction effects was prevalent for all the characters. Duplicate dominance type of epistasis was witnessed in all characters, while complementary epistasis was also noticed in certain crosses for the traits number of bolls per plant and 2.5 per cent span length.

To harness additive gene action, simple selection procedures or pedigree breeding method is sufficient. But the presence of dominance gene action in most of the characters warrants postponement of selection to later generations after effecting crosses. Heterosis breeding procedures are effective in harnessing dominance gene action to the full extent. Both additive and dominance gene actions play major role in several characters. In such circumstances biparental mating design or reciprocal recurrent selection can be followed which allows further recombination of alleles to produce desirable segregants. These methods can also be well adopted in order to harness the epistatic interactions by way of breaking the undesirable linkages. Diallel selective mating system could also be followed to break such undesirable linkages between two or more genes and to produce desirable recombinants.

REFERENCES [1] Cavalli, L.I. (1952). An analysis of linkage in quantitative inheritance. In: Quantitative inheritance. E.C.R.Reeve and

C.H.Waddington (eds.), HMSO, London. pp135-144. [2] Esmail, R.M., Hendawy, F.A., Rady, M.S. and Abd-El-Hamid, A.M.. (1999). Genetic studies on yield and yield

components in one inter and two intraspecific crosses of cotton. Egyptian J. Agron., 21: 37–51. [3] Hendawy, F.A., Rady, M.S., Abd-El-Hamid, A.M. and Esmail, R.M. (1999). Inheritance of fibre traits in some cotton

crosses. Egyptian J. Agron., 21: 15–36. [4] Jagtap, D.R. (1995). Genetic components of heterosis and selection potential of crosses in generation means of upland

cotton. J. Indian Soc. Cotton Improv., 20(3): 142–148. [5] Jinks, J.L. and Jones , R.M. ( 1958). Estimation of the components of heterosis. Genetics, 43: 223–234. [6] Mather, K. (1949). Biometrical genetics. Dover publication in New York. p58. [7] Mehetre, S.S., Rajput, H.J., Shinde, G.C. and Mokate, A.S. (2003). Genetics of fibre quality traits in intraspecific crosses of

G. hirsutum cotton. J. Indian Soc. Cotton Improv., 28(3): 132–136.


[8] Nadarajan, N., Kumaresan, D., Ponnusamy, K. and Azhuguvel, P. (1999). Genetic analysis of fibre quality characters in upland cotton (Gossypium hirsutum L.). In: International seminar on cotton and its utilization in the 21st century, Dec. 10-12, CIRCOT, Mumbai. p43.

[9] Panchal, S.S., Patel, J.A., Patel, S.A. and Dahal, K.C. (1994). Genetic architecture of lint component characters in interspecific hybrids of cotton. Gujarat Agril. Univ. Res. J., 19(2): 62–64.

[10] Patel, K.G., Patel, R.B., Patel, M.I. and Kumar, V.(2007). Genetic of yield, fibre quality and their implications in breeding of interspecific cross derivatives of cotton. J. Cotton Res. Dev., 21: 153-157.

[11] Rajendra Kumar, P. and Raveendran, T.S. (2001). Genetic evaluation of yield and yield components in upland cotton through triple test cross analysis. Indian J. agric. Sci., 71: 62–64.

[12] Ramalingam, A. and Sivasamy, N. (2003). Genetics and order effects of boll number per plant and boll weight in upland cotton (Gossypium hirsutum). Madras Agric. J., 90(7–9): 472–477.

[13] Sandhu, B.S., Gill, M.S. and Mittal, V.P. (1992). Genetic architecture of Gossypium arboreum. Indian J. Genet., 52(3): 257–260.

[14] Shanti, R.M. (1998). Investigation on genetic potential and biochemical compounds related to resistance of Helicoverpa armigera (Hubner) in the racial and wild species derivatives of Gossypium spp. Ph.D Thesis, Tamil Nadu Agricultural University, Coimbatore, India. (Unpublished)

[15] Singh, P. and Chahal, G.S. (2004). Simultaneous improvement of yield and fibre quality in upland cotton (Gossypium hirsutum L.). Indian J. agric. Sci., 74(12): 643–648.

[16] Singh, P., Chahal, G.S. , Mittal, V.P. and Brar, K.S. (2008). Genetic analysis of yield components and fibre quality characters in upland cotton (Gossypium hirsutum L.). Indian J. Genet., 68(1): 33–37.

[17] Thangaraj, K., Raveendran, T.S. and Jehangir, K.S. (2002). Heterosis and inbreeding depression in interracial derivatives of Gossypium hirsutum L. for fibre quality. J. Indian Soc. Cotton Improv., 27(1): 15–18.

Introgression of Desirable Characters for Growing Cotton in Pakistan

Abid Mahmood, Jehanzeb Farooq and Noor-Ul-Islam

Cotton Research Institute, Ayub Agricultural Research Institute, Faisalabad, Pakistan

Abstract—Cotton crop face both biotic and abiotic stresses. Keeping in view the emerging problems of cotton in Pakistan, a breeding programme was initiated to develop cotton varieties which can withstand under changing environment especially at high temperature and Cotton Leaf Curl Virus (CLCuV) conducive conditions. A series of experiments was conducted to select parental lines which can contribute for high temperature tolerance, low input requirements, earliness, good fibre squality traits, CLCuV tolerance and plants suitable for high density planting. A comprehensive breeding programme was initiated to combine desirable characters in resulting breeding material. Screening of breeding material was carried out in CLCuV hot spot areas. At the same time fibre quality, earliness and high yield were also considered during selection. For low input requirement varieties like FH-113 and FH-942 were developed. For heat and CLCuV tolerance 24 Lines were developed. Some of the lines like MNH-886, FH-142 and MNH-456 showed promising results in this respect. For high density planting of cotton, the line FH-114 showed good performance at densities of 10,0000 plants per hectare. It was recommended that for late sowing of cotton, plant to plant distance of FH-114 may be reduced to 12cm to achieve desirable yield per unit area. The varieties developed during these studies exhibited the highest yield with good fibre quality in CLCuV hot spot areas. It is expected that in future more improved germplasm will be available which will enhance the productivity of cotton in Pakistan.

INTRODUCTION

The importance of upland cotton, (Gossypium hirsutum L), is evident from the fact that it is the world’s leading fibre producing species (Dutt et al., 2004; Fryxell, 1992). It contributes 60% in the total foreign exchange through the exports of value added products (Iqbal et al. 2005). Cotton accounts for 8.6 % of the value added in agriculture and about 1.8 % to GDP of Pakistan (Anonymous, 2007). Pakistan is the 4th largest cotton producing country in the world after Peoples Republic of China, USA and India, and 3rd largest consumer of cotton after People Republic of China and India (Akhtar, 2005).

Keeping in view the geographical situation and farming system of Pakistan breeding of cotton for the development of earliness, heat tolerance, low input requirements, CLCuV resistance and better quality traits are the main objectives. These breeding objectives help to protect environment, boost cotton productivity and make cotton production a profitable venture. Most of the cotton growers in Pakistan are poor and cannot afford heavy expenses of inputs like fertilizer, pesticides and irrigation water. Varieties having deep root system and higher stature require less irrigation water thus can meet the needs of the farmer.

Similarly the varieties with Bt gene provide resistance against bollworms thus reduce the cost of pesticides to control these insects. Bt. Cotton provides an alternative by replacing insecticides with a toxin within the plant. According to Layton et al. (1997) overall performance of Bt. Cotton was better than conventional varieties. Transgenic Bt. cotton can effectively control specific lepidopterous species (Arshad et al., 2009).

For the last many years one of the main causes of low per acre yield of cotton in Pakistan is CLCuV attack. In the early nineties cotton varieties like CIM-1100, CIM-448, CIM-446, CIM-443, MNH-552, MNH-554 were developed which were having resistance against CLCuV. Build up of this disease in the recent years resulted in high inoculum pressure under which varieties which were initially showing some tolerance later became susceptible (Mahmood et al., 2003; Shah et al., 2004).

In several districts of Punjab and Sindh severe summer temperatures exceeding 450C cause considerable damage to cotton crop (Rehman et al., 2004). Fruit setting in upland cotton is severely

6


effected if day temperature of >300C remained for a period of 13 hrs or more (Reddy et al., 1992). Further, it is the need of the day to improve fibre quality in the Hirsutum genotypes, to fulfill the requirements of growing textile industry.

Cotton plant sets its bolls (fruit) over a period of about 80 days. Delayed in that period allows various environmental factor to act and effect maturation period (Iqbal et al., 2003). Late maturating types are ultimately affected by a later pest pressure. Cotton fiber quality is primarily influenced by late maturity of the genotype and by environmental conditions as the secondary factors (Subhan et al., 2001). Earliness in cotton is a complex polygenic trait influenced by a number of factors like morphology, phenology, physiology and environmental attributes (Shah et al., 2010). Earliness allows development of crop during period of favorable moisture and timely picking prevent the crop from unfavorable weather (Rauf et al., 2005). The benefit of growing early maturing cotton cultivars is the provision of proper time for rotation of other crops allowing timely sowing of wheat in cotton – wheat – cotton cropping system as in Pakistan (Ali et al., 2003). The cultivation of early maturing cultivars not only minimizes the use of pesticides, but the expenses incurring on other inputs like irrigation water and fertilizer will also be reduced.

In Pakistan under cotton – wheat – cotton rotation system planting of cotton become late due to delayed harvesting of wheat crop. Delayed planting of cotton poses many problems including severe insect pest attack, incidence of CLCuV and poor growth of the plants. To get better yield in late plantings (high plant population) might be beneficial provided that the late sown genotypes be CLCuV tolerant and fit to high population. Close row spacing and high plant populations in ultra-narrow rows lead to more rapid canopy closure than in wider rows (Robinson, 1993), which leads to increased light interception and reduced weed competition (Kreig, 1996).

The main objective of these studies was to develop germplasm having combination of characters including Bt (Cry-1 Ac), earliness, heat tolerance, resistance to CLCuV and less fertilizer requirement. In addition this germplasm should fit in cotton-wheat-cotton rotation system.


In order to combat the threats of cotton bollworms, CLCuV, heat stress and for the development of varieties having less fertilizer requirement comprehensive breeding programme was initiated. For this purpose parents having desirable characters were identified. The detail of characteristics of the parent lines is given in Table 1.

TABLE 1: NAMES AND VARIOUS CHARACTERISTICS OF THE LINES USED AS PARENT IN VARIOUS EXPERIMENTS INCLUDED IN THESE STUDIES

Parents Distinctive Features FH-925 Early sympodial type variety with medium boll. Having tolerance to heat and CLCuV.

Nucot-N33B An Australian line with Bt gene and was used to transfer Bt in local germplasm possessing good fibre and plant traits.

FH-925 Early sympodial type variety with medium boll. Having tolerance to heat and CLCuV.

Nucot-N33B An Australian line with Bt gene and used for transfer it in local germplasm possessing good fibre and plant traits.

FH-900(S) Resistance against CLCuV, relatively tolerant to heat stress, good fiber quality, fitness in cotton-wheat rotation system and adaptability to wider range of environments

CIM-125 Medium in maturity, intermediate in growth habit and possess good fibre traits.

FH-207 Tall with long sympodial branches, moderately resistant to sucking pest and bollworms. Suitable for Low CLCV intensity areas of non-core zone.

MNH-770 Medium tall plant with tolerance to CLCuV and heat. Its distinctive feature is yellow pollen. MNH-609 Medium tall plant with tolerance to CLCuV and heat.

A systematized crossing programme was carried out to combine the desirable characters in resulting breeding material. For this purpose after crossing F1 and F2 were raised. In F2 single plants with desirable characters were selected. Progeny selection was carried out from F3 to F6 on the basis of seed cotton yield and fibre quality. The detail of the selected genotypes included in the studies is given in Table-2.

Introgression of Desirable Characters for Growing Cotton in Pakistan 37

TABLE 2: PEDIGREE AND VARIOUS TRAITS OF LINES INCLUDED IN VARIOUS EXPERIMENTS CONDUCTED AT COTTON RESEARCH INSTITUTE, FAISALABAD

Genotypes Parentage Distinctive Features

FH-113 FH-925 × NuCot-N33B Tall growing Bt variety possesses moderate tolerance to CLCuV. It has strong stem, prolonged flowering duration and require low inputs.

FH-114 FH-925 × NuCot-N33B A compact input intensive Bt variety with high tolerance to CLCuV and heat stress. Best suited to high plant population in late sowing.

FH-942 FH-900(S) × CIM-121 A spreading growth habit variety most suitable for water-scarce areas. Possess good boll size and fibre quality of national standards.

MNH-886 FH-207 × MNH-770 A revolutionary variety with respect to CLCuV. Intermediate to spreading in its growth habit. Boll size of this variety is medium and can tolerate heat stress in core areas of Punjab.

MNH-456 FH-207 x MNH-609 Highly tolerant to CLCuV A series of experiments were carried out in targeted environments and conditions to find out various

lines of cotton. The studies were carried out at experimental area of Cotton Research Institute, Faisalabad. The soil had pH was 8.2, EC 1.3 dSm-1, nitrogen 0.030% and available Phosphorous 7.0 mg kg-1. The detail of experiments is as under.

Experiment 1: Selection of Lines for Low Fertilizer Requirement

These studies were conducted following Split Plot design with 4 replications. The fertilizer doses were randomized as main plots and genotypes as sub-plot. The line to line distance was kept as 75cm and plant to plant distance at 30cm. Each plot was consisted of 5 lines with 5 meter length. Three genotypes viz., FH-113, FH-942 and FH-1000 were included in these studies. Sowing of the genotypes was carried out on May 3 in 2003-04 and on May 12 in 2004-05. The phosphorus and potash were applied basaly at the time of sowing while the nitrogen was applied in three splits i.e., with first irrigation, at the time of start of square formation and at blooming stage. There were three treatments, i.e full doze of recommended fertilizer (NPK, 114:54:62), half dose of fertilizer (NPK, 57:27:31) and control, (where no fertilizer was applied). Before the experiment the soil was exhausted by growing maize crop in the field. All other agronomic practices and insect control measures was carried out as standard procedure. At maturity data of seed cotton yield/ha was recorded. Analysis of variance was carried out and means of genotypes were compared by LSD.

Experiment 2: Selection of CLCuV Tolerant Lines

In this experiment high yielding with good fibre quality character lines were included. Twenty four advance lines of different genetic background were sown in three replications to identify lines tolerant to CLCuV. Each genotype was planted in two rows with row length of 5 meter. Standard agronomic practices were applied. To maximize CLCuV inoculum pressure the pesticide for whitefly was not applied throughout the experiment. Data for CLCuV was recorded following the rating system described by Akhtar et al, 2010. The procedure of rating CLCuV incidence is briefly mentioned in Table 3.

TABLE 3: DISEASE SCALE FOR RATING COTTON LEAF CURL VIRUS DISEASE

Symptoms Disease Index%

Rating Disease Response

Complete absence of symptoms 0 0 Immune Thickening of few small scattered veins or only presence of leaf enations on one or few leaves of a plant observed after careful observations. 0.1–10 1 Highly resistant

Thickening of small group of veins, no leaf curling, no reduction in leaf size and boll setting. 10.1-20 2 Resistant

Thickening of all veins, minor leaf curling and deformity of internode with minor reduction in leaf size but no reduction in boll setting. 20.1-30 3 Moderately

resistant Severe vein thickening, moderate leaf curling followed by minor deformity of internodes and minor reduction in leaf size and boll setting. 30.1-40 4 Moderately

susceptible Severe vein thickening, moderate leaf curling and deformity of internodes with moderate reduction in leaf size and boll setting followed by moderate stunting. 40.1-50 5 Susceptible

Severe vein thickening, leaf curling, reduction in leaf size, deformed internodes and stunting of the plant with no or few boll setting. >50 6 Highly

susceptible Foliar outgrowths (enation) will be marked with ‘‘E’’ where observed.


To calculate severity index (SI) and per cent disease index (PDI) of the genotype under study, Individual symptomatic plant ratings for each genotype was added and divided by the number of infected plants to calculate the corresponding SI. The PDI was calculated using the following formula:

Percent Disease index= Sum of all disease ratings of the selected plants at random × 100 Total no. of plants assessed. 6

Experiment 3: High Density with Late Cotton Sowing Studies

These studies were carried out to find out suitable lines for high density planting of cotton. For this purpose cotton lines with short sympodia (FH-114 and FH-2015) and intermediate sympodia FH-113 were selected. The cotton was sown after the harvesting of wheat. The trial was sown on June 10, 2004-05. All agronomic practices were carried out as standard except line to line distance was kept 37cm and plant to plant was 12cm. Plant population 43000 and 10,0000/ha was maintained. At maturity, data on seed cotton yield and yield components were recorded. Ginning out turn was calculated after ginning of 50 gm sample of seed cotton and other fibre quality traits like staple length, maturity and fineness was measured.

Experiment 4: Heat Tolerance Studies

For the identification of heat tolerant cotton genotypes the same 24 genotypes which were studied in CLCuV screening experiment were included. The genotypes showed maximum boll retention at highest temperature of the flowering period of cotton was identified as heat tolerant. The experiment was sown on April, 15 in 2003-04 and on April, 12 in 2004-05. The data for boll retention was recorded from June 15 to July 15 each year. These studies were carried out at two locations i.e., Faisalabad and Multan. The data of maximum temperature of experimental sites is given in Table 4. The location of Multan was included in this study as it has the highest temperature in Punjab. Boll retention percentage was calculated by dividing the number of retained boll by total number of flowered fruiting sites.

TABLE 4: MAXIMUM TEMPERATURE FOR THE MONTH OF JUNE AND JULY DURING 2003-04 AND 2004-05

Location Month Temperature (0C) 2003-04 Temperature(0C) 2004-05

Multan June 43.50C 430C July 44.50C 440C

Faisalabad June 41.00C 410C July 42.00C 41.50C


The results of the fertilizer trial in two year study i.e. 2003-04 and 2004-05 indicated highly significant differences (P>0.05) for varieties, fertilizer doses and their interaction. On the basis of first year, FH-113 surpassed all varieties by producing a yield of 2860kg/ha at full dose of fertilizer followed by FH-942, (2770kg/ha) and FH-1000 (2133kg/ha). At half dose of fertilizer FH-113 also produced maximum yield of 2470kg/ha followed by FH-942 (2120kg/ha) and FH-1000 (1880kg/ha). At control, FH-113 produced maximum yield of 1560kg/ha. During second year again FH-113 produced maximum yield of 2903kg/ha at full dose of fertilizer than FH-942 (2685kg/ha) and FH-1000 (2237kg/ha). At half dose FH-113 showed its superiority by producing yield of 2575kg/ha which is significantly higher than the other two varieties. It is evident from the results of both years that the variety FH-113 not only performed well at full dose of fertilizer but also produced highest yield at half dose of fertilizer. Khan et al. (1994) and Latif et al. (1994) were of the view that 100 kg N was the optimum N requirement for cotton under Faisalabad and Sakrand conditions, respectively. But in present studies FH-113 produced promising yield at half dose of fertilizer also. The detailed results of analysis of variance and means of the genotypes at three levels of fertilizer are given in Table 5 and 6.


Results of the screening experiment against CLCuV revealed that three genotypes viz., MNH-609, MNH-886 and MNH-456 showed resistance to CLCuV by showing disease severity of 1.65, 1.69 and 1.74 respectively and disease index of 17.8, 18.7 and 19.3% respectively (Table 7). These genotypes possess Cry1 Ac gene and hence have no attack of boll worms. However, FH-114, FH-941, FH-942 and BH-168 were among moderately susceptibility genotypes as the disease index of these genotypes was below 50%. Remaining seventeen genotypes showed high susceptibility ranging from 58.35 to 80.12%. The strains resistant to CLCuV sometimes again become susceptible due to the emergence of new strains of virus which ultimately results in resistance break down (Mansoor et al., 2003, Akhtar et al., 2002). In Pakistan, previously successful efforts have been made to develop virus resistant varieties resulted in recovery of production that was improved from 8.04 million bales in 1993-94 to 11.17 million bales in 1999-2000, (Anonymous, 2001). In the present studies resistance to CLCuV exhibited by some lines is encouraging though continued efforts are needed to develop resistant germplasm against CLCuV and various new strains of virus.

For high population studies the genotypes with compact structure, FH-114, FH-2015 and intermediate growth habit (FH-113) were evaluated. The morphological (plant height, sympodia per plant, bolls per plant, boll weight, seed cotton yield) and fibre quality traits like ginning out turn%, fibre length, strength and fineness were studied at population densities of 43000 and 10,0000 plants/ha. FH-114 gave a mean plant height of 96.4cm, 12.8 sympodial per plant, 12.0 bolls per plant, 2.6g boll weight and seed cotton yield of 1300kg/ha at plant population of 43000 but at plant population of 10,0000 the yield was 1900kg/ha. The plant height at this density reduced and remained at 88.7cm. However, boll number and number of sympodia almost remained the same but boll weight reduced to 2.4g. Ginning out turn, fibre length, fibre strength and fibre fineness at plant population of 43000 was recorded at 38.0%, 27.7mm, 97.63tppsi and 4.9µg/inch respectively and at plant population of 10,0000/ha these values remained at 37.5%, 27.5mm, 98.0tppsi and 5.1 µg/inch respectively. The intermediate growth habit variety FH-113 produced a yield of 1050kg/ha at 43000 plants per hectare and at 10,0000 plants per hectare it produced a yield of 1600 kg/ha. It attained a plant height of 100.0 cm at 43000 and 93.0cm at 10,0000 plants/ha. Similarly, for boll weight, almost similar values were found at both plant denstities but boll number reduced at 10,0000 plants/ha. In terms of fiber quality traits same pattern of variation existed with little reduction in all the studied traits (Table 7). FH-2015 another compact variety evaluated at both population densities however it was not successful as it produced a very low yield of 700 and 1100 kg/ha at both populations. Its low yield is evident from less sympodia per plant, less boll number and reduced boll weight. In terms of fibre quality traits it is most affected by the environment and showed poor results. Results at both densities showed that FH-114 can be exploited in late sown conditions as it can tolerate CLCuV to greater extent as compared to other genotypes hence produced more yield. The current results are in conformity with the results of Krishna et al., (2009) who proposed that by growing cotton in narrow rows can produce more seed cotton yield than the wider rows.

The same genotypes that were tested for screening against CLCuV also tested for heat stress tolerance. The genotypes namely, MNH-456, FH-114 and MNH-886 showed boll retention percentage of 82.2, 80.4 and 70.9% respectively (Table 8).These genotypes can tolerate the temperature of 400C and can be grown most successful at high temperature regions. The remaining genotypes showed variable range from 29.3% to 75.4% boll retention (Table 8). High temperature results in poor pollen germination and pollen tube growth affecting yield to greater extent. Temperature beyond 450C severely reduces the growth and development of cotton plant (Khan et al., 2005). The results are encouraging as the genotypes like MNH-886, MNH-456 and FH-114 have been developed by keeping in view the improvement in multi-traits. These varieties not only can cover the threat of CLCuV but also can tolerate heat and have good fiber quality traits. The further studies are underway to develop better varieties which can withstand in CLCV conditions and having heat tolerance, good yield and fiber quality.


TABLE 5: MEAN SQUARES FOR SEED COTTON YIELD

Source DF MS (2003-04) MS (2004-05) Reps 3 135503* 42879* Doses 2 3479470 4134993 Error 6 12754 11215 Varieties 2 836480* 996353* Doses x Varieties 4 66963* 18952* Error 18 16120 16031

TABLE 6: YIELD (KG/HA) PERFORMANCE OF VARIETIES AT DIFFERENT DOSES OF FERTILIZER

Fertilizer Doses Control (0-0-0) Half Dose of Fertilizer(57:27:31) Full Dose of Fertilizer (114:54:62) Varieties 2003-04 Variety Mean FH-113 1560 2470 2860 2297 FH-942 1340 2120 2770 2077 FH-1000 1328 1880 2133 1780 Fertilizer doses mean 1409 2157 2588 Varieties 2004-05 Variety Mean FH-113 1644 2575 2903 2374 FH-942 1390 2237 2685 2104 FH-1000 1160 2010 2250 1807 Fertilizer doses mean 1398 2274 2613 LSD(0.05): For fertilizer doses(2003-04)=112.82 LSD(0.05):For fertilizer doses(2004-05) =106.79

LSD (0.05): For varieties (2003-04) =108.90 LSD (0.05): For varieties (2004-05) =106.60

TABLE 7: PER CENT DISEASE INDEX (PDI), SEVERITY INDEX (SI) AND DISEASE REACTION OF VARIOUS GENOTYPES TESTED AT COTTON RESEARCH INSTITUTE, FAISALABAD

Region Genotypes PDI (%) SI Disease Reaction

Faisalabad

FH-113 63.73 3.82 HS FH-114 39.27 2.47 S FH-941 44.84 3.12 S FH-942 48.05 2.88 S FH-1067 80.12 4.81 HS

Sahiwal SLH-284 70.97 4.26 HS SLH-317 76.12 4.57 HS

Bahawalpur

BH-162 58.85 3.53 HS BH-167 62.98 3.78 HS BH-168 49.49 3.06 S BH-197 74.78 4.49 HS

Multan

MNH-93 58.35 3.5 HS MNH-149 67.09 4.02 HS MNH-253 57.55 3.45 HS MNH-456 19.32 1.74 R MNH-609 17.82 1.65 R MNH-700 68.23 4.04 HS MNH-752 75.25 4.51 HS MNH-784 63.9 3.83 HS MNH-787 64.77 3.89 HS MNH-789 63.14 3.79 HS MNH-886 18.67 1.69 R

Vehari VH-144 65.43 3.93 HS VH-278 76.06 4.56 HS

TABLE 8: PERFORMANCE OF VARIETIES AT DIFFERENT PLANT POPULATION FOR VARIOUS MORPHOLOGICAL AND FIBRE TRAITS

Varieties Plant Population

ha-1

Plant Height (cm)

Sympodia Per plant

Bolls Per

Plant

Boll Weight

(g)

Seed Cotton Yield

(kg/ha)

GOT%

Fibre Length (mm)

Fibre Strength (tppsi)

Fibre Fineness (µg/inch)

FH-114 43000 96.4 12.84 12.08 2.61 1200 38.0 27.7 99.6 4.9 10,0000 88.72 11.68 11.48 2.36 1900 37.5 27.5 98.0 5.1

FH-113 43000 100.08 11.04 7 3.32 1050 38.3 28.5 97.3 5.1 100000 93 13 10 3 1600 38 28.0 96.5 5

FH-2015 43000 75.4 7 7 2.10 700 37.0 27.6 94.7 5.2 10,0000 70.4 6 5 1.90 1100 36.3 27.3 94.2 5.4


TABLE 9: BOLL RETENTION PERCENTAGES OF VARIOUS GENOTYPES TESTED FOR HEAT TOLERANCE

Region Genotypes Boll Retention (%)

Faisalabad Region

FH-113 65.0 FH-114 80.4 FH-941 50.0 FH-942 55.2 FH-1067 71.0

Sahiwal SLH-284 67.2 SLH-317 50.0

Bahawalpur

BH-162 54.4 BH-167 62.1 BH-168 54.1 BH-197 42.2

Multan

MNH-93 45.1 MNH-149 31.7 MNH-253 65.0 MNH-456 82.2 MNH-609 40.0 MNH-700 70.0 MNH-752 42.6 MNH-784 29.3 MNH-787 40.9 MNH-789 65.3 MNH-886 70.91

Vehari VH-144 75.4 VH-278 50.4

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characters in upland cotton. Online J. Bio. Sci. 3(6): 585-590. [11] Iqbal, M., Iqbal, M.Z., Khan, R.S.A. and Hayat, K. (2005). Comparison of obsolete and modern varieties in view to

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exploited for breeding of better yielding cultivars under high temperature regimes. Pak. J Bot. (40)5 2053-2058. [13] Khan, R., Soomro, A.W. and Arain, A.S. (1994). Evaluation of different sources and rate of nitrogenous fertilizers on

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[22] Rahman, H., Malik, S.A. and Saleem, M. (2004). Heat tolerance of upland cotton during the fruiting stage evaluated using cellular membrane thermostability. Field Crop Res. 85: 149-158.

[23] Rauf S., Shah, K.N. and Afzal, I. (2005). A genetic study of some earliness related characters in cotton (Gossypium hirsutum L.).Caderno de Pesquisa Ser. Bio., Santa Cruz do Sul. 17 (1): 81–93.

[24] Reddy, K.R., Hodges, H.F. and Reddy, V.R. (1992). Temperature effects on cotton fruit retention. Agron. J. 84: 26–30. [25] Robinson, J.R.C. (1993). Narrow row cotton: economics and history. p. 133–137. In Proc. Beltwide Cotton Conf., New

Orleans, LA. 10–14 Jan. 1993. Natl. Cotton Counc. Am., Memphis, TN. [26] Shah, H., Khalid, S., Naqvi, S.M.S. and Yasmin, T. (2004). A simple method for screening cotton germplasm against cotton

leaf curl virus. Sarhad J. Agric., 20(3):453-458. [27] Shah, M. K. N., Malik, S.A., Murtaza, N., Ullah, I., Rahman, H. and Younis, U. (2010). Early and rapid flowering coupled

with shorter boll maturation period offers selection criteria for early crop maturity in upland cotton. Pak. J. Bot. 42(5): 3569-3576.

[28] Subhan, M., Khan, H.U. and Ahmed, R.O. (2001). Population analysis of some agronomic and technological characteristics of upland cotton (Gossypium hirsutum L.). Pakistan J. Biol. Sci. 1:120-123.

[29] Yuan, Y.L., Zhang, T.Z., Guo, W.Z., Pan, J.J. and Kohel, R.J. (2005). Diallel analysis of superior fibre quality properties in selected upland cottons. Acta Genetica Sinica 1: 79-85.

Temporal Changes in Metabolically Important Enzymes and Solutes act as Trigger for Epidermal

Cell Conversion to Fibre Initials in Cotton

Gopalakrishnan N.1, A.H. Prakash2 and Y.L. Balachandran3

1Assistant Director General (Commercial Crops), ICAR, New Delhi, India 2Central Institute for Cotton Research, Regional Station, Coimbatore, India

3Department of Biotechnology, Bharathiyar University, Coimbatore, India

Abstract—As one of the longest single-cell seed trichomes, cotton fibres act as an excellent model for unraveling fundamental biological processes such as cell differentiation, cell expansion and cell wall biosynthesis. In order to probe better cotton fibre production through effective fibre development processes, temporal changes in the oxidative enzymes and solute contents were studied in near isogenic lines of linted cotton cv. MCU 5 and its lintless mutant MCU5 LL. The ovules were quantified for Peroxidase (POD), Catalase (CAT), Ascrobate peroxidase (APX) and Superoxide dismutase (SOD) from ten days pre anthesis to six days post anthesis (DPA). The POD activity in MCU 5 was maintained around 0.06 units per /g fresh weight ovules pre anthesis and enhanced to 0.08 at anthesis and further to 0.1 units at 2 DPA and later declined, while in MCU 5LL, the POD activity reduced to 0.01units 3 days prior to anthesis and later increased to 0.04 units at anthesis and further to 0.05 till 6 DPA. The CAT and APX activities were very low in MCU 5 LL ovules all through, while the MCU 5 ovules had higher activities during pre anthesis (around 1.6 units) and 0.8 units post anthesis. The SOD activity shot up to 4.0 units at anthesis and later maintained at 3.0 units during the fibre initiation process, while MCU 5 LL ovules showed a marginal increment in SOD activity. Biochemical analysis of the lintless mutant ovules revealed a marked reduction in the synthesis of reducing sugars, total free amino acids and total soluble protein content, while there was no effect on the proline and phenol content of ovules from 0 to 5 DPA. The RAPD analysis revealed that two primers were found non-polymorphic with two extra bands at 2040±10 bp and 630 ±10 bp in MCU 5. The failure to trigger the production of anti-oxidants and synthesis of solutes at anthesis can be assigned as crucial factors for non-conversion of epidermal cells to fibre initials in lintless mutant and provide enough clues as biochemical determinants for better fibre development process in cotton.

INTRODUCTION

Cotton fibre quality improvement is of vital importance to textile industry. The fiber elongation and secondary deposition of cellulose are highly sensitive to immediate surroundings. Cotton fibres are a subset of single epidermal cells that elongate from the seed coat to produce cellulose strands or lint. As one of the longest single-cell seed trichomes, fibers provide an excellent model for studying fundamental biological processes such as cell differentiation, cell expansion and cell wall biosynthesis. The molecular and metabolic mechanisms associated with differentiation of epidermal cells of ovules to trichomes are still a mystery. In order to enhance the quality attributes of cotton fiber, there is an imperative need to study the regulation of cotton fiber cell expansion, a vital process controlled by genetic, environmental and hormonal factors.

Cotton fiber cells are tubular outgrowth of single celled trichomes which arise in near synchrony from the epidermis of the ovule and may elongate at peak rates in excess of 2 mm per day during the rapid polar expansion phase of development (Basra and Malik, 1984). Developing cotton seeds are an excellent system to study diverse patterns of carbon partitioning including cellulose, starch and oil biosynthesis (Ruan and Chourey, 1998). There has been a substantial progress in our understanding of cellulose synthesis in developing cotton fibers. However, little is known about the early events controlling fibre cell initiation. Morphologically, the initiation of each fiber cell is associated with the spherical expansion and protrusion of one epidermal cell above the ovular surface during anthesis (Basra and Malik, 1984). Genetic variation between plants for a trait controlled by a single or a few genes inherited in a single Mendelian fashion is easy to manipulate through breeding. There has been a number of reliable markers such as protein or, more specifically, allelic variants of several characters such as

7


lipid or sugars must be considered (Prakash et al. 2002). Isozyme numbers are limited and their expression is often restricted to a specific developmental stage of tissues; and their presence can be determined by electrophoresis and specific staining.

There are numerous in vitro studies which have thrown light on the basic processes of fiber initiation and the factors that may have a role thereon. Fiber initiation and development are known to be influenced by the age of the ovule (Graves & Stewart, 1988), temperature (Xie et al., 1993), plant growth regulators (DeLonge, 1986) and inorganic nutrients (Eid et al., 1973) in the culture medium. Plant growth regulators like indole-acetic acid, gibberellic acid, ethylene and abscisic acid play a decisive role in fiber development (Prakash et al., 2002; Kosmidou-Dimitropoulou, 1986). In the present study, the metabolic process, biochemical constituents and the RAPD technique were used to study the factors associated in differentiation of ovular epidermal cells into fiber initials using a normal cotton genotype and its lintless mutant, as they provide contrasting genetic material for studying the molecular events specific for fibre development.

The present work aims at investigating the enzymatic changes in the pre and post anthesis period from -10 to + 6 days anthesis and accumulation of biochemicals in post anthesis for + 60 DAA. Furthermore RAPD profile technique was used to study the factors associated in differentiation of ovular epidermal cells into fiber initials using a normal cotton genotype and its lintless mutant, as they provide contrasting genetic material for studying the molecular events specific for fibre development.


Plant Materials

Cotton (Gossypium hirsutum L.) near isogenic lines-MCU 5, and its lintless mutant MCU 5LL were grown under field conditions with optimum agronomic practices at Central Institute for Cotton Research, Regional Station, Coimbatore. The initiated squares were tagged and the ovules were excised at different growth stages. Harvested ovules at various developing stages were frozen in liquid nitrogen till extraction. Developing seeds and fibers were analyzed at regular intervals for reducing sugar (Somogyi, 1952), soluble proteins (Lowry et al., 1951) and total phenols (Bray and Thorpe, 1965). The whole ovules were used for biochemical analysis.

Isolation of Genomic DNA from the Ovules

Fresh ovules (100 mg) were isolated and ground to fine powder with liquid nitrogen and the genomic DNA was extracted following CTAB method (Doyle and Doyle, 1984). The cotton ovules had higher polyphenolic compounds which initially interfered in the yield of the DNA which was later removed by the addition of the PVP- 40 in the extraction buffer which increased the yield and the purity of the DNA obtained (Porebski et al., 1997). Additional precipitation steps with isopropanol helped in removal of protein and polysaccharides (Padmalatha & Prasad., 2006.).

RAPD - PCR Analysis

RAPD analyses were carried out according to Sambrook & Russell (2001). One hundred 10 – mer oligonucleotides (Sigma Aldrich) were selected for initial screening of gene specific sequences. 20 primers were selected for the final RAPD – PCR analysis (Table 1). Amplification reactions were performed in a 20 µl reaction mixture containing 1.5 μl of Taq DNA polymerase (Bangalore Genei, Bangalore), 0.2 mM dNTPs, 2µL of 10X PCR buffer with MgCl2, 0.4 µM of 10-base primer and 50 ng of DNA as the template. Amplifications were performed in a Gradient Mastercycler (Eppendorf, Germany.) by the following program: initial denaturation temperature of 94oC for 5 min; 30 cycles each with denaturing at 94oC for 30s, annealing at 55oC for 30s and extension at 72oC for 1 minute; and final extension at 72oC for 5 min. Reaction products were then loaded on to 1.4% agarose gel for electrophoresis. Gels were documented under UV following EtBr staining with Alpha Imager systems, UK. A negative control, without DNA, was included in all reactions.

Temporal Changes in Metabolically Important Enzymes and Solutes act as Trigger for Epidermal Cell Conversion 45

TABLE 1: LIST OF 10-MER PRIMES USED FOR RAPD ANALYSIS OF 2 DAYS POST ANTHESIS OVULES OF MCU 5 AND MCU 5LL.

S. No. Primer Sequence 1 TGAGGGCCGT 2 TCGTTCACCC 3 CATAGAGCGG 4 CCACCACTTC 5 CCTGTCAGTG 6 GGGGAAGACA 7 GTGTCAGTGG 8 CTGGCTCAGA 9 TGCCACGAGG

10 CTGAAGCGCA 11 AAGACCGGGA 12 CCGAGCAATC 13 TGTGGACTGG 14* GAGAGGCTCC 15* TCCGTGCTGA 16 TGCCTGGACC 17 GGCAGGTTCA 18 CTGGTGCTGA 19 GACAGTCCCT 20 TGGTCGGGTG

ESTIMATION OF ENZYMES

Peroxidase activity (POD) was determined by using the method described by Shannon et al. (1966). The change in absorbance was recorded at 470 nm at an interval of 15 sec for 2 min. The enzyme activity was expressed as units (mg protein)-1. Ascorbate peroxidase (APX) activity was assayed by monitoring the ascorbic acid-dependent reduction of H2O2, as described by Anderson et al. (1992). Ascorbate peroxidase activity was expressed as nmol ascorbate oxidised (mg protein) –1min–1. Catalase activity (CAT) was estimated by the method of Aebi (1984). The absorbance was recorded at 240nm at an interval of 15 sec for 2 minutes immediately after the addition of enzyme extract. The enzyme activity was expressed as mmol H2O2 decomposed (mg protein)–1min–1. The superoxide dismutase (SOD) enzyme activity was assayed by the method of Giannopolitis and Ries (1977). The absorbance was read at 560 nm. One unit of SOD was defined as the level of enzyme activity that inhibited the photoreduction of NBT to blue formazan by 50 % (expressed as units SOD mg protein–1).


The normal phenological boll development in MCU 5 and its lintless mutant has been depicted in (Figure 1A& 1B)). Boll bursting stage shows the clear picture of seeds bearing the lint and lintless. Morphology difference between the bolls at the later stages of anthesis is evident. The difference could be caused due to the elongation of the fibers in the cultivar MCU 5 in the later stages of the days post anthesis.

Fig. 1: Digital Images of the Various Stages of the Bolls from the Cultivar (a) MCU 5 and its Mutant (b) MCU 5LL


To explore the biochemical changes among the two cultivars MCU 5 and its mutant variety MCU 5LL, total soluble proteins and antioxidant enzymes peroxidase (POD), ascorbate peroxidase (APX), catalase (CAT) and superoxide dismutase (SOD) were studied in ovules from 10 days prior anthesis to 6 days after thesis. The analysis was done upto 6 days after anthesis based on the earlier observations made by Hovav et al 2008 and Chaudhary et al 2008, that the oxidant and antioxidant genes are up- or down-regulated early in fiber development, but not later. Highest number of genes were up-regulated in the early stage (2 days after anthesis), where at later stages of fiber development, there were only few such genes (Chaudhary et al 2008).

The total soluble protein concentration was low from -2 days to + 2 days of anthesis in the mutant variety (MCU 5LL), while MCU 5 showed higher levels at – 4, 0 and + 2 days after anthesis and remained low in -2 and + 4 days anthesis (Fig-2). There was significantly lower level of soluble protein content in the ovules at anthesis in the lintless mutant (26.36 mg.g-1FW) as compared to MCU 5 (46.71 mg.g-1FW). With progress in time, the protein content in the mutant seeds increased and by 10 DPA, it was on par with the normal seeds (Gopalakrishnan et al., 2010). Turley and Ferguson (1996) made a comparative analysis of the fls mutant SL 171 against an unrelated FLS inbred using two dimensional PAGE analysis of the total ovular protein. Of the numerous Coomassie blue-stained spots, only five polypeptides are unique to the mutant. Hence, it is difficult to assign any physiological significance to these differences because these proteins are of an unknown nature. Similarly, even though there was a distinct reduction in the protein synthesis in lintless mutant (MCU 5 LL), it is difficult to pin point the type of protein. Hence, the genomic DNA from the ovules was extracted and subjected further for the PCR based RAPD.

Fig. 2: Changes in the Total Soluble Proteins in the Cultivars MCU 5 and MCU 5LL

In our study, PCR based RAPD technique was used with randomly generated synthetic oligonucleotides of 10 bases. The high sensitivity of the method applied to pre-digest DNA permitted the tagging of specific locus for some characters in nearly isogenic lines of cotton (Arshad & Haidar, 2000). RAPD PCR analysis among the MCU 5 and its mutant MCU 5LL was initially done with 100 primers. Majority of the primers failed to amplify in both the genotypes (data not shown) and only 20 primers gave the best banding pattern. The band size ranged from 2800 bp to 100 bp. The amplified products of the primer 3` GAGAGGCTCC 5` gave two additional bands of the size of 2040(± 10) bp and 630 (± 10) bp, while a band sized 1160 (± 10) bp of the primer sequence 3`TCCGTGCTGA 5’ in the MCU 5 which are lacking in the MCU 5LL (Figure – 4a). All the other eighteen primers gave similar banding pattern and 100 % polymorphism among the genotypes (Table - 1).

Though many RAPD studies in cotton are done to find their genetic diversity among the cultivar identification of cotton (Rana & Bhat 2004), there are few studies done to differentiate among the mutants using RAPD. In the present study, a different banding pattern in two of the primers which gave extra bands in linted genotype that were absent in the lintless genotype. From the result, we can infer that these extra bands may have an important role in the fiber initiation and in early fiber elongation process from 0 days to 5 days of the development of the fibers. Compared with the Arabidopsis trichome, little is


known about the molecular control of the cotton fiber development. So far, a number of genes differentially expressed during different stages of fiber development have been identified, but their roles in cotton development are not yet clear (Hu¨lskamp et al., (1994). Ji et al (2003) studied on the genes which preferably expressed during the early fiber development through cDNA microarray analysis of 0 to 10 DPA ovules, which showed that 172 genes were significantly up-regulated during the course and are involved in energy metabolism, cell turgor generation and primary and secondary wall biogenesis, which again showed that turgor pressure is crucial for fibre initiation.

The relationship between the fiber initiation and antioxidant response was studied in ovules from -10 days pre anthesis to + 6 days post anthesis. The highest activity was observed in the -4 and +2 days anthesis ovules and the lowest with -2 days anthesis ovules Fig-3a). Lintless mutant shows low level of peroxidase than that of the MCU 5. Maximum decrease in the peroxidase content -2 days anthesis was seen and recovering in 0 and 2 days to slightly higher levels. Similar pattern of ascorbate peroxidase activity as such as POD was noticed with MCU 5 (Figure 3b). Increase levels in APX enzymes in days -4 and + 2 days anthesis, with minimal level of APX in days -2 and 0 days anthesis was seen. To the contrary, lintless mutant showed higher level of APX in days -2 and 0 anthesis, while rest of the ovule stages displayed somewhat similar levels with not much different changes (Figure 3b). Mutant variety MCU 5LL showed a low level CAT activity at -10 days anthesis and later increased till 0 days anthesis (Figure 3c). There was a decline in the activity in +2 and +4 days of anthesis and normalized by +6 days post anthesis. The CAT activity in MCU 5 showed slight increase during 0 to +2 post anthesis. The mutant MCU 5LL showed decreased antioxidant enzymes activity during the fiber initial process. Most of the enzymes maintained low activity after anthesis, while MCU 5 showed higher enzyme activity during anthesis. The increase of antioxidant activity could be due to the increase in the production H2O2 level. The increase of H2O2 levels has been shown to enhance antioxidant content and antioxidant enzymes in many plants (Mitler and Tel-Or, 1992 and Lechno et al 1997). Low levels of H2O2 stimulate expression of necessary genes for the onset of secondary wall cellulose biosynthesis. The elevated levels of the H2O2 would result in the accumulation of H2O2- dependent reaction products which could trigger the programmed cell death response, eventually this could trigger the activation of a cell-death process, which for the cotton fiber cells constitutes a form of terminal differentiation (Potikha et al 1999). The role of APX in regulation of intracellular ROS levels by reduction of H2O2 to water using ascorbate as an electron donor and multiple fold increases in the cotton APX genes was seen till + 5 days anthesis., The increase in the expression of genes corresponding to POD and APX in + 2 days post anthesis which are associated with ROS metabolism has also been reported (Chaudhary et al 2009). These reports are in concurrence to our results, where the highest peroxidase and ascrobate activity was seen in + 2 days anthesis ovules in MUC 5. Lower levels of these antioxidant enzymes may result in the higher level of the H2O2 in the ovules resulting in destruction of the cells that trigger fiber initiation and elongation process.

Fig. 3: Differential Antioxidant Enzyme Activity in Different Ovular Stages form -10 Days Pre Anthesis to + 6 Days Post Anthesis from of MCU 5 and MCI 5LL Mutant. (a) POD, (b) APX, (c) CAT, and (d) SOD. Values are the Means of Three sets of Observations


Fig. 4: (a) 0.8% Agarose Gel Picture of Genomic DNA of + 2 Days Post Anthesis Ovules of lint (Lane 2 -L) and its lintless (Lane 3-LL) mutant. The lane 1 M Corresponds to the Size Marker DNA (ECorI / Hind III Double Digested). (b) The RAPD Profile of MCU 5( L) and its Mutant MCU 5LL(LL). The White Arrow

Mark Indicated the Extra Band. 10kbp (Lane 1) and 1kbp(Lane 2) Marker DNA are used as the Ladder

Biochemical accumulation of reducing sugars, total free amino acids, proline and total phenols in ovules from 0 days anthesis to boll bust was studied in MCU 5 and its lintless mutant 5LL and similar biochemical compounds were studied in fibers from day anthesis to boll bust in MCU 5. Characteristic accumulation of reducing sugars (Fig 5a) and total free amino acids (Fig 5b)was noticed in developing seeds of lintless mutant as compared to linted MCU 5. It has been reported that of larger amount of sugar molecules is synthesied during secondary wall formation (Fukuda, 1991, 1996). The secondary wall of developing cotton fiber consists of nearly pure cellulose and is devoid of hemicellulose and lignin (Basra and Malik, 1984; Ryser, 1985). Rates of cellulose synthesis increase was reported to occur abruptly to about 100-fold at around 24 days post anthesis of secondary wall formation (Meinert and Delmer, 1977). Furthermore, development occurs synchronously for nearly all fibers within a boll, with the transition to secondary wall formation beginning abruptly in varieties of cotton at about 14 to 16 DPA, which is a few days prior to the cessation of fiber elongation (Meinert and Delmer, 1977). The higher activity in day 25 of ovules and day 15 for fibers of MCU 5 observed in our study is consistent with the above literature reports. Proline in lintless mutant showed elevated levels in 30 post anthesis. It is reported that the proline-rich proteins accumulate in later stages during active secondary cell wall formation, indicating possible regulation at the translational level and function in the secondary cell wall assembly. The proline content (Fig 5c) was high and ranged around 55 to 65 mg.g-1 till 15 DAA and there after lesser accumulation was observed in both fibre (0.5-2.0 mg.g-1) and ovules (20-50 mg.g-1).

Fig. 5: Measurement of Biochemical Constituents during 0- 60 Days Post Anthesis in Ovules of MCU 5 and MCU 5LL. Changes in Bio-constituents (a)

Reducing Sugars, (b) Total Free Amino Acids, (c) Proline, and (d) Total Phenols in Ovules


CONCLUSION

The process of modification of epidermal cells to fibre initials starts 4-6 days before anthesis that has been clearly shown by the up and down regulation of biochemical constituents as observed in MCU 5 and its mutant (MUC 5 LL). The final trigger is provided at anthesis where the solutes help in fibre initiation and elongation processes accounting for the involvement of multiple components. The failure to trigger the production of anti-oxidants and synthesis of solutes at anthesis can be assigned as crucial factors for non-conversion of epidermal cells to fibre initials in lintless mutant and provide enough clues as biochemical determinants for better fibre development process in cotton.

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Study of Interspecific Hybrids (Gossypium hirsutum x G. barbadense) for Heterosis and Combining Ability

K.P.M. Dhamayanthi

Central Institute for Cotton Research, Regional Station, Coimbatore-641 003, India

Abstract—Forty nine inter-specific F1 combinations were made using two tetraploid cotton species Gossypium hirsutum and G. barbadense. Observations on seed cotton yield, its component traits and ginning per cent were recorded on parental lines and F1 hybrids during the year 2007-08 and 2008-09. Among the females BRS-53-53 was found to be good general combiner for boll per plant and seed cotton yield. Amongst the male parents, ICB-260 and Pima S4 were found to be the best general combiner on the basis of seed cotton yield and it’s per se performance, however B-4 was the best for the majority of the yield components. Five crosses were identified as the best crosses on the basis of per se performance, combining ability and heterosis. High heterotic crosses viz., which have shown more than 40% heterosis for seed cotton yield and its component traits could be exploited for increasing yield in inter-specific cotton hybrids.

INTRODUCTION

Cotton the king of fibre is a premier cash crop of our country grown in about 9 million hectares, which represent 29 per cent of the world cotton area. India is a pioneer country for the cultivation of cotton hybrids on commercial scale. Exploiting heterosis is one of the methods to increase cotton yields that have stagnated in recent years. It has the potential of increasing yield from 10 to 20% and of making improvements in fibre properties. Increased yield and fibre qualities are vital to keep Indian cotton competitive with synthetics and foreign production. In India, 40% of cotton production is derived from intra-specific hybrids of G. hirsutum, and 8% of its production is from G. hirsutum x G. barbadense hybrids (Singh and Chaudhry, 1997). Yield increase of hybrids over the better parent or best commercial cultivar (useful heterosis) has been documented earlier showed an average useful heterosis of 21.4% for F1 hybrids (Singh et al., 2003). In recent years, breeding progress for increased yield has greatly decreased. Research on plant breeding needs to address all possibilities to increase yield, including the use of heterosis. In hybrid development programme, improving the qualitative and quantitative characters are possible by better commercial exploitation of hybrid vigour (Rajamani et al., 2009). The concept of combining ability is important in designing the plant breeding programmes. It is highly useful to study and compare the performance of lines in hybrid combinations. Information concerning to different types of gene action, relative magnitude of genetic variance and combining ability estimates are significant markers to shape the genetic make up of a crop like cotton. This important information could prove an essential strategy to the cotton breeders in screening of better parental combinations for further enhancement. Cotton breeders have the challenge of finding good combiners by the use of heterosis.

In cotton, high heterosis has been reported at inter-specific and intra-specific levels both in diploid and tetraploid cotton (Singh and Kalsey, 1983). In recent past, there are hundreds of long and medium staple hybrids being cultivated in South and Central zone. But in extra long staple category, hybrids are very limited and the current production of extra long staple cotton is not sufficient to meet the domestic textile requirement of our country. There is a need to develop suitable high yielding extra long staple hybrids with desirable fibre qualities to cater the need of the Indian Textile Industry. Hence, in the course of developing extra long staple inter-specific hybrids, an attempt was made to find out the extent of heterosis for seed cotton yield and its components in 49 inter-specific F1 hybrids obtained from seven diversified G. hirsutum female parent and seven elite male genotypes of G. barbadense.


8


Seven diversified female genotypes of Gossypium hirsutum viz. BRS-53-53, CCH-510-4, CCH-724, CCH-4, TK-36, ENT- 4, LK-18, and seven male genotypes of G. barbadense viz. B-4, B-5, ICB-20, ICB-74, ICB-201, ICB-260 and Pima S-4 were identified for better fibre properties to generate 49 hybrids in a line x tester mating design along with 14 parents and a check hybrid DCH-32 in a randomized block design with three replications. Two rows of each parents and crosses were sown at a spacing of 90 cm between rows and 60 cm between plants during August 2006. Ten plants were chosen from two rows of each genotype to record data on seed cotton yield (g), plant height(cm), number of monopodia/plant, number of sympodia/plant, boll weight (g), number of bolls/plant, ginning outturn, 2.5 percent span length (mm), fibre strength (g/tex) and fibre fineness (µ/inch). Heterobeltiosis over better parent and standard heterosis over check DCH-32 were calculated by the following formula;

Heterobeltiosis over BP = (F1-BP/BP) x 100; Standard heterosis = (F1-SH/SH) x 100 Where F1 = Mean value of the F1; BP = Mean value of the better parent of the particular cross SH= Mean value over replication of standard hybrids


The analysis of variance showed highly significant differences among the progenies, hybrids and parents (Table 1). The partioning of hybrid mean square indicated that the variance due to males and females and an interaction of males x females was significant for all the characters indicating the manifestation of parental genetic variability in their crosses. Mean, range, coefficient of variation for important ten characters were studied and presented in Table 2. The maximum variability of 16.38 % was recorded for seed cotton yield followed by 14.31% of sympodial branches/plant. The coefficient of variability for the plant height was 12.34 %.

TABLE 1: ANALYSIS OF VARIANCE FOR DIFFERENT CHARACTERS IN INTER-SPECIFIC HYBRIDS (GOSSYPIUM HIRSUTUM L X G. BARBADENSE L )

Source of variation d.f. Pt. Height Boll wt. Bolls/pt. Seed Cotton Yield/pt. GOT % Replication 2 4.24 0.01 3.17 27.18 0.51 Progenies 62 507.60** 17.08** 78.20** 168.19** 5.33** Hybrids 48 148.26** 9.27** 82.64** 132.60** 5.27** Parents vs hybrids 1 7218.03** 173.91** 293.91** 55.18** 3.81** Lines -females 6 178.63** 147.67** 133.62** 147.27** 1.97** Tests-male 6 619.34** 28.33 255.13** 543.07** 87.41** Line x Testers 36 86.29** 162.13** 33.41 97.32** 22.69** Errors 124 18.29 0.43 11.64 27.56 0.33

*significant at 0.01 level of probabilty

The coefficient of variation among the qualitative characters, ginning outturn, bundle strength and micronaire value expressed the least value of 2.67, 2.46 and 1.55 respectively. Highest percentage of heterosis (91.35%) over best parent was recorded in number of bolls/plant followed by seed cotton yield (73.61%) and number of monopods/plant (73.33%).

TABLE 2: MEAN, RANGE, COEFFICIENT OF VARIATION AND HETEROSIS FOR VARIOUS CHARACTERS OF INTER-SPECIFIC HYBRIDS (G. HIRSUTUM X G. BARBADENSE)

Characters Mean ± SE CV Range Heterosis Over Best Parent Seed cotton yield (kg/ha) 984.54 ± 127.42 16.38 719-2435 73.61 Plant height (cm) 119.01 ± 13.56 12.34 110-17-124.60 16.31 Monopods/plant 3.33 ± 0.49 9.60 1.30-6.00 73.33 Sympods /plant 9.41 ± 1.65 14.31 5.13-15.3 31.27 Boll wt. (g) 3.86 ± 0.12 8.32 3.5-5.61 23.81 Bolls/plant 57.66 ± 2.53 9.16 41.24-77.20 91.35 Ginning outturn (%) 30.07 ± 1.03 2.67 28.14-36.01 7.26 2.5% span length (mm) 35.24 ± 0.08 3.5 2 34.23-37.20 4.11 Strength (g/tex) 30.05 ± 0.23 2.46 27.34-33.01 -24.05 Micronaire (µ/inch) 3.62 ± 0.03 1.55 3.05-4.1 35.37

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