Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-22T03:09:08.098Z Has data issue: false hasContentIssue false

Assessment of genetic divergence in diploid cotton (Gossypium arboreum L.) germplasm using fibre quality traits

Published online by Cambridge University Press:  04 November 2020

A. Manivannan*
Affiliation:
ICAR-Central Institute for Cotton Research, Regional Station, Coimbatore641003, India
V. N. Waghmare
Affiliation:
ICAR-Central Institute for Cotton Research, Nagpur441108, India
*
*Corresponding author. E-mail: [email protected]

Abstract

Cotton is one of the most important crops among natural fibres. Fibre quality determines the spinning ability, which is negatively correlated with yield and yield-contributing traits. Limited efforts have been made to improve fibre quality and yield in diploid cotton. Therefore, screening a large panel of germplasm lines can help identify genotypes with better fibre quality and yield. We evaluated 712 desi cotton genotypes for fibre quality traits. The genotypes showed a significant difference for all the traits, suggesting considerable variability for fibre quality improvement. Fibre length and strength showed high phenotypic and genotypic coefficients of variation. Heritability was high for fibre strength, length, and elongation. Fibre length and strength were positively correlated; however, micronaire was negatively correlated with these two traits. Superior accessions were identified for fibre length (11), strength (20), uniformity (7), and elongation (25) among genotypes. Most of the desi lines (71%) had medium micronaire values. Twenty accessions identified were ideal for spinning, showing the fibre strength-to-length ratio of one. Cluster analysis based on Euclidean distance grouped all 712 accessions into four major clusters. Principal component analysis biplot revealed that accessions AC3418, 360-SP1, AC3522B, Kanpur A, Gao16CB-9, and AC3370 were genetically diverse. The superior accessions for fibre quality identified in this study are potential lines for the diploid cotton improvement programme.

Type
Research Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of NIAB

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ali, MA, Khan, IA and Nawab, NN (2009) Estimation of genetic divergence and linkage for fibre quality traits in upland cotton. Journal of Agricultural Research 47: 229236.Google Scholar
Burton, GW and Davane, EM (1952) Estimating heritability in fall fescue (Festuca Arundiancea L.) from replicated clonal material. Agronomy Journal 45: 478481.CrossRefGoogle Scholar
Campbell, BT and Jones, MA (2005) Assessment of genotype×environment interactions for yield and fiber quality in cotton performance trials. Euphytica 144: 6978.CrossRefGoogle Scholar
Chandra, M and Sreenivasan, S (2011) Studies on improved Gossypium arboreum cotton: part I – fibre quality parameters. Indian Journal of Fibre and Textile Research 36: 2434.Google Scholar
Chaudhary, R (2000) Fibre length: achievements and new challenges. The International Cotton Advisory Committee Recorder 18: 3.Google Scholar
Chen, Y, Liu, G, Ma, H, Song, Z, Zhang, C, Zhang, J, Zhang, J, Wang, F and Zhang, J (2018) Identification of introgressed alleles conferring high fiber quality derived from Gossypium barbadense L. in secondary mapping populations of G. hirsutum L. Frontiers in Plant Science 9: 1023.CrossRefGoogle ScholarPubMed
Clement, JD, Constable, GA, Stiller, WN and Liu, SM (2012) Negative associations still exist between yield and fibre quality in cotton breeding programs in Australia and USA. Field Crops Research 128: 17.CrossRefGoogle Scholar
Gadissa, F, Tesfaye, K, Dagne, K and Geleta, M (2020) Morphological traits based genetic diversity assessment of Ethiopian potato (Plectranthus edulis (Vatke) Agnew) populations from Ethiopia. Genetic Resources and Crop Evolution 67: 809829.CrossRefGoogle Scholar
Hammer, O, Harper, DAT and Ryan, PD (2001) PAST: paleontological statistics software package for education and data analysis. Palaeontologia Electronica 4: 19.Google Scholar
Han, YJ, Cho, YJ, Lambert, WE and Bragg, CK (1998) Identification and measurement of convolutions in cotton fibre using image analysis. Artificial Intelligence Review 12: 201211.CrossRefGoogle Scholar
Hanen, G, Ghith, A and Benameu, T (2017) Open-end yarn properties prediction using hvi fibre properties and process parameters. Alexandria Science Exchange Research Journal 17: 611.Google Scholar
Hanson, CH, Robinson, HF and Comstock, RE (1956) Biometrical studies of yield in segregating populations of Korean lespediza. Agronomy Journal 48: 268272.CrossRefGoogle Scholar
Hequet, E, Wyatt, B and Abidi, N (2006) Creation of a set of reference material for cotton fiber maturity measurements. Textile Research Journal 76: 576586.10.1177/0040517506064710CrossRefGoogle Scholar
Hovav, R, Udall, JA, Chaudhary, B, Hovav, E, Flagel, L, Hu, G and Wendel, JF (2008) The evolution of spinnable cotton fiber entailed prolonged development and a novel metabolism. PLoS Genetics 4: e25.CrossRefGoogle Scholar
Ibrahim, AE (2019) Effect of fiber length and short fiber per cent in cotton on fiber and yarn quality. Alexandria Science Exchange Journal 39: 663667.CrossRefGoogle Scholar
Johnson, HW, Robbinson, HF and Comstock, RE (1955) Estimates of genetic and environmental variability in soya bean. Agronomy Journal 47: 314318.CrossRefGoogle Scholar
Karademir, C, Karademir, E and Gencer, O (2011) Yield and fiber quality of f1 and f2 generations of cotton (Gossypium hirsutum L.) under drought stress conditions. Bulgarian Journal of Agricultural Science 17: 795805.Google Scholar
Koebernick, JC, Liu, S, Constable, GA and Stiller, WN (2019) Parental selection strategy for improving fibre strength and maintaining lint yield in cotton. Industrial Crops and Products 129: 585593.CrossRefGoogle Scholar
Kranti, KR (2015) Desi cotton return? Cotton Statistics and Newsletter 15: 14.Google Scholar
Kumar, SK, Nidagundi, JM and Hosamani, AC (2017) Association analysis for seed cotton yield and fiber quality improvement in intra specific crosses of cotton (Gossypim hirsutum L). International Journal of Pure and Applied Bioscience 5: 282284.CrossRefGoogle Scholar
Li, F, Fan, G, Wang, K, Sun, F, Yuan, Y, Song, G, Li, Q, Ma, Z, Lu, C, Zou, C, Chen, W, Liang, X, Shang, H, Liu, W, Shi, C, Xiao, G, Gou, C, Ye, W, Xu, X, Zhang, X, Wei, H, Li, Z, hang, G, Wang, J, Liu, K, Kohel, RJ, Percy, RG, Yu, JZ, Zhu, YX, Wang, J, Yu, S (2014) Genome sequence of the cultivated cotton Gossypium arboreum. Nature Genetics 46: 567572. https://doi.org/10.1038/ng.2987CrossRefGoogle ScholarPubMed
McCouch, S, Baute, GJ, Bradeen, J, Bramel, P, Bretting, PK, Buckler, E, Burke, JM, Charest, D, Cloutier, S, Cole, G, Dempewolf, H, Dingkuhn, M, Feuillet, C, Gepts, P, Grattapaglia, D, Guarino, L, Jackson, S, Knapp, S, Langridge, P, Lawton-Rauh, A, Lijua, Q, Lusty, C, Michael, T, Myles, S, Naito, K, Nelson, RL, Pontarollo, R, Richards, CM, Rieseberg, L, Ross-Ibarra, J, Rounsley, S, Hamilton, RS, Schurr, U, Stein, N, Tomooka, N, van der Knaap, E, van Tassel, D, Toll, J, Valls, J, Varshney, RK, Ward, J, Waugh, R, Wenzl, P, Zamir, D (2013) Agriculture: feeding the future. Nature 499: 2324.CrossRefGoogle ScholarPubMed
Miyazaki, J, Stiller, WN, Truong, TT, Xu, Q, Hocart, CH, Wilson, LJ and Wilson, IW (2014) Jasmonic acid is associated with resistance to two spotted spider mites in diploid cotton (Gossypium arboreum). Functional Plant Biology 41: 748757.CrossRefGoogle Scholar
Parsi, RD, Kakde, MV, Pawar, K and Patil, RSP (2016) Influence of fibre length on ring spun yarn quality. International Journal of Research and Scientific Innovation 3: 154156.Google Scholar
Pearson, K (1901) On lines and planes of closest fit to systems of points in space. Philosophical Magazine 2: 559572.Google Scholar
Perrier, X and Jacquemoud-Collet, JP (2006) DARwin software. Available at http://darwin.cirad.fr/Google Scholar
Rahman, M (2016) Cotton improvement for environmentally stressed economies. The International Cotton Advisory Committee Recorder 34: 12.Google Scholar
Rathinavel, K (2018) Principal component analysis with quantitative traits in extant cotton varieties (Gossypium hirsutum L.) and parental lines for diversity. Current Agriculture Research Journal 6: 5464.CrossRefGoogle Scholar
Romeu-Dalmau, C, Bonsall, M, Willis, K, Dolan, L. (2015) Asiatic cotton can generate similar economic benefits to Bt cotton under rainfed conditions. Nature Plants 1: 15072. https://doi.org/10.1038/nplants.2015.72CrossRefGoogle ScholarPubMed
Ruan, YL, Xu, SM, White, R and Furbank, RT (2004) Genotypic and developmental evidence for the role of plasmodesmatal regulation in cotton fibre elongation mediated by callose turnover. Plant Physiology 136: 41044113.CrossRefGoogle ScholarPubMed
Singh, B (2001) Plant Breeding: Principles and Methods, 6th edn. New Delhi, India: Kalyani Publishers.Google Scholar
Subramaniam, S and Madhav, M (1973) Inheritance of short stature in rice. Madras Agriculture Journal 60: 11291133.Google Scholar
Wang, F, Zhang, C, Liu, G, Chen, Y, Zhang, J and Qiao, Q (2016) Phenotypic variation analysis and QTL mapping for cotton (Gossypium hirsutum L.) fiber quality grown in different cotton-producing regions. Euphytica 211: 169183.CrossRefGoogle Scholar
Ward, JH (1963) Hierarchical grouping to optimize an objective function. The Journal of the American Statistical Association 58: 236244.CrossRefGoogle Scholar
Wendel, JF, Flagel, LE and Adams, KL (2012) Jeans, genes, and genomes: cotton as a model for studying polyploidy. In: Soltis, P and Soltis, D (eds) Polyploidy and Genome Evolution, pp. 181–207. Berlin, Heidelberg: Springer.Google Scholar
Yu, J, Zhang, K, Li, S, Yu, S, Zhai, H, Wu, M, Li, X, Fan, S, Song, M, Yang, D, Li, Y, Zhang, J (2013) Mapping quantitative trait loci for lint yield and fiber quality across environments in a Gossypium hirsutum×Gossypium barbadense backcross inbred line population. Theoretical and Applied Genetics 126: 275287.CrossRefGoogle Scholar
Supplementary material: File

Manivannan and Waghmare supplementary material

Manivannan and Waghmare supplementary material

Download Manivannan and Waghmare supplementary material(File)
File 71.4 KB