ASSESSMENT OF GENETIC VARIABILITY PARAMETERS FOR YIELD AND FIBRE QUALITY TRAITS OF COTTON (GOSSYPIUM HIRSUTUM L.) IN F2 POPULATION

K. KEERTHIVARMAN¹*, N. MEENAKSHI GANESAN², N. MANIKANDA BOOPATHI³, S. SUBHASHINI⁴, BANOTH MADHU⁵, K. ARAVIND⁶, G. ARIHARASUTHARSAN⁷, M. AKILAN^8
1Department of Genetics and Plant Breeding, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
²Department of Genetics and Plant Breeding, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
³Department of Biotechnology, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
⁴Sugarcane Breeding Institute, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
⁵Department of Cotton, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
⁶Central Institute for Cotton Research, Regional Station, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
⁷Department of Genetics and Plant Breeding, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
⁸Department of Genetics and Plant Breeding, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
* Corresponding Author : varmankrishnankeerthi@gmail.com

Received : 04-12-2022     Accepted : 27-12-2022     Published : 30-12-2022
Volume : 14     Issue : 12       Pages : 11974 - 11977
Int J Agr Sci 14.12 (2022):11974-11977

Keywords : Variability, Heritability, GCV, PCV, G. hirsutum L. and F2 population
Academic Editor : Saket Kumar, Dr K R Prasad
Conflict of Interest : None declared
Acknowledgements/Funding : Authors are thankful to Department of Cotton; Department of Genetics and Plant Breeding, Tamil Nadu Agricultural University, Coimbatore, 641003, Tamil Nadu, India
Author Contribution : All authors equally contributed

The F2 population of the crosses MCU 5 × KC 3 and MCU 5 × NDLH 1755 were taken for the investigation of variability and heritability studies to understand the gene action contributing to each trait taken under study. The phenotypic coefficient of variation (PCV) in both the crosses were found to have environmental influence as it was greater than the genotypic coefficient of variation (GCV) for all the traits under study. The studies of heritability and genetic advance as percent of mean helps us to identify the trait is additive or epistatic in nature, therefore undergo suitable breeding programmes for the improvement of the population. Among all the characters taken under study, the seed cotton yield per plant alone was found to have additive gene action with high heritability and high genetic advance as percent of mean hence could be involved in direct selection as it is the major trait for improvement of the population of that trait in the cross MCU 5 × KC 3. The cross MCU 5 × NDLH 1755 the traits namely, number of sympodial branches per plant, number of bolls per plant and seed cotton yield per plant had high genetic advance as percent of mean and high heritability hence additive in nature hence could be taken for direct selection for the enhancement of the population. Other traits in both the crosses had non- additive or epistatic gene action with either high heritability with medium or low genetic advance as percent of mean which could be improved through heterosis breeding programmes. Since traits are contributed by complex gene action

1. Mishra P.K., Ram B.R. and Neeraj K. (2015) Turkish Journal of Agriculture and Forestry, 39(3), 451-458.
2. Kumar G.S., Kumar N.M., & Katageri I.S. (2017) Int. J. Curr. Microbiol. App. Sci., 6(11), 453-457.
3. Nadeem K., and Azhar F.M. (2004) Int. J. Agric. Biol., 6(5), 865-868.
4. Ali M.A., & Khan I. A. (2007) J. Agric. Soc. Sci., 3(4), 112-116.
5. Basal H., & Turgut I. (2005) Asian Journal of Plant Sciences, 4(3), 293-298.
6. Ali M.A., Khan, I.A., Awan S.I., Shiraz A., & Shahid N. (2008) Australian Journal of Crop Science, 2(1), 10-17.
7. Ali M.A., & Awan S.I. (2009) Int. J. Agric. Biol., 11(1), 44-48.
8. Ranganatha, H. M., Patil, S. S., Manjula, S. M., & Arvindkumar, B. N. (2013) Molecular Plant Breeding, 4(10).
9. Singh R.K. and Chaudhary B.D. (1977) Biometrical methods in quantitative genetic analysis, Kalyani Publishers, New Delhi, 57-58.
10. Johnson H.W., Robinson H.F. & Comstock R.E. (1955) Agronomy Journal, 47(7), 314-318.
11. Burton G.W. and Devane E.M. (1953) Agronomy Journal, 45, 478-481.
12. Sivasubramanian, S. and M. Menon, 1973) Madras Agric. J., 60, 1139.
13. Robinson H.F., Comstock R.E., Harvey P.H. (1949) Agron. J., 41, 353-359.
14. Lokeshkumar B.M. and Patil B.R. (2018) Int. J. Curr. Microbiol. App. Sci., 7(9), 360-367.
15. Gitte V.K., Misal M.B., Kalpande H.V., & Deshmukh J.D. (2007) Journal of Cotton Research and Development, 21(1), 27-28.
16. Nandhini K., Balu P. A., & Isong A. (2018) Int. J. Pure App. Biosci., 6(2), 1499-1505.
17. Jarwar A.H., Wang X., Wang L., Ma Q. and Fan S. (2018) J Envir Agric Sci., 6, 24-31.
18. Hampannavar M.R., Patil B.R., Katageri I.S., Kumar B.A., & Janagoudar B.S. (2020) Int. J. Curr. Microbiol. App. Sci., 9(1), 493-503.
19. Srinivas B., Bhadru D., Rao M.V., & Gopinath M. (2014) Agricultural Science Digest-A Research Journal, 34(4), 285-288.
20. Khan F.Z., Rehman S.U., Abid M.A., Malik W., Hanif C.M., Bilal M., & Farhan U. (2015) Journal of Green Physiology, Genetics and Genomics, 1(1), 1-10.
21. Pujer S., Siwach S.S., Deshmukh J., Sangwan R.S., & Sangwan O. (2014) Electronic Journal of Plant Breeding, 5(2), 284-289.