International Journal of Innovative Approaches in Agricultural Research
Abbreviation: IJIAAR | ISSN (Online): 2602-4772 | DOI: 10.29329/ijiaar

Original article    |    Open Access
International Journal of Innovative Approaches in Agricultural Research 2019, Vol. 3(2) 193-201

Qualitative Assessment of Reaction Norm of New Cotton Lines (G. hirsutum L.)

Minka Koleva, Valentina Dimitrova & Ana Stoilova

pp. 193 - 201   |  DOI:

Published online: June 30, 2019  |   Number of Views: 48  |  Number of Download: 518


The qualitative side of reaction norm of eight promising cotton lines and of standard cultivar was studied. The lines were obtained by intra-specific and remote hybridization of the G. hirsutum L. species with some wild diploid species of the genus Gossypium L. The type of their dynamic regression (of their regression curve) and the structure of ecological environments in their dynamic rows were determined in order to characterize the reaction norm. The years of the study (2014-2017) appeared to be as different ecological environments. Four qualitative characters - seed cotton yield, boll weight, fiber length and fiber lint percentage were analyzed. It was found that in most cases the studied lines had reaction norm which considerably differed from that of the standard cultivar. The specificity of the lines reaction was less pronounced in its type (in ½ of cases) and stronger (in more than 7/8 of cases) in the structure of ecological environments in its dynamic row. By the index type of reaction line № 457 was closest to the standard cultivar, while line № 449 was furthest from it. For the individual characters, the line reaction norm was manifested to varying degrees, from very high - for the boll weight, where similarity  with the standard cultivar was missing, to average - for the seed cotton yield, where for this character half of the lines were similar to the standard cultivar.

Keywords: Cotton, G. hirsutum L., Agronomic traits, Regression curves, Dynamic rows

How to Cite this Article

APA 6th edition
Koleva, M., Dimitrova, V. & Stoilova, A. (2019). Qualitative Assessment of Reaction Norm of New Cotton Lines (G. hirsutum L.) . International Journal of Innovative Approaches in Agricultural Research, 3(2), 193-201. doi: 10.29329/ijiaar.2019.194.5

Koleva, M., Dimitrova, V. and Stoilova, A. (2019). Qualitative Assessment of Reaction Norm of New Cotton Lines (G. hirsutum L.) . International Journal of Innovative Approaches in Agricultural Research, 3(2), pp. 193-201.

Chicago 16th edition
Koleva, Minka, Valentina Dimitrova and Ana Stoilova (2019). "Qualitative Assessment of Reaction Norm of New Cotton Lines (G. hirsutum L.) ". International Journal of Innovative Approaches in Agricultural Research 3 (2):193-201. doi:10.29329/ijiaar.2019.194.5.

  1. Balakrishna, B., V. Chenga Reddy and M. Lal Ahamed M. (2016). Stability analysis for seed cotton yield & its component traits in inter-specific hybrids of cotton (G. hirsutum × G. barbadense). Green Farming,  7 (5), 1013-1018.   [Google Scholar]
  2. Becker, H.C. and J. Leon (1988). Stability analysis in plant breeding. Plant Breed., 101, 1-23. [Google Scholar]
  3. Eberhart, S.A. and W.A. Russell, (1966). Stability parameters for comparing varieties. Crop Sci., 6, 36-40. [Google Scholar]
  4. Farias, F.J., L. P. Carvalho, J.L. Silva Filho and P.E.  Teodoro (2016). Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. Genet. Mol. Res., 15 (2), gmr.15028009  [Google Scholar]
  5. Fasoula V.A. (2013). Prognostic breeding: A new para¬digm for crop improvement. Plant Breeding Rev., 37, 297–347.  [Google Scholar]
  6. Finlay, K.W. and G.N. Wilkinson (1963). The analysis of adaptation in a plant-breeding programme. Aust. J. Agric. Res., 14, 742-754. [Google Scholar]
  7. Francis, T.R. and L.W.Kannenberg (1978). Yield stability in short-season maize. I. A descriptive method for grouping genotypes. Con. J. Plant Sci., 58, 1029-1034. [Google Scholar]
  8. Gauch, H.G., Jr. and R.W. Zobel (1988). Predictive and postdictive success of statistical analyses of yield trials. Theor. Appl. Genet., 76, 1-10.  [Google Scholar]
  9. Greveniotis, V.,  E. Sioki  and C. G. Ipsilandis (2018). Estimations of Fibre Trait Stability and Type of Inheritance in Cotton. Czech J. Genet. Plant Breed., 54, (1), 00–00 Short Communication [Google Scholar] [Crossref] 
  10. Güvercin, R.Ș.,  E. Karademir ,  Ç. Karademir ,  N. Özkan,  R. i and G.  Borzan  (2017). Adaptability and stability analysis of some cotton (Gossypium hirsutum L.) cultivars in East Mediterranean and GAP region (South-Eastern Anatolia Project) conditions. Harran Tarım ve Gıda Bilimleri Dergisi/ Harran J. Agric. Food Sci., 21 (1): 41-52.  [Google Scholar]
  11. Kang, M. S. (1993). Simultaneous selection for yield and stability and yield statistic. Agron. J., 85, 754-757. [Google Scholar]
  12. Lidanski, T., and N. Naydenova (1993). Qualitative assessment of the norm of reaction of genotypes. Genetics and Breeding (Bg), 4. [Google Scholar]
  13. Lin, C. S., M. R. Binns, and L. P.  Lefkovich (1986). Stability analysis: Where do we Stand. Crop Sci., 26,  894-900. [Google Scholar]
  14. Maleia, M.P., A. Raimundo, L. D. Moiana, J. O. Teca, F. Chale, E. Jamal, J. N. Dentor and B. A. Adamugy (2017). Stability and adaptability of cotton (Gossypium hirsutum L.) genotypes based on AMMI analysis. Aust. J. Crop Sci., 11 (4), 367-372. [Google Scholar]
  15. Orawu, M., G. Amoding, L. Serunjogi, G. Ogwang, C. Ogwang (2017). Yield stability of cotton genotypes at three diverse agro-ecologies of Uganda. J. Plant Breeding Genet., 5 (3), 101-114. [Google Scholar]
  16. Perkins, J.M. and J.L. Jinks (1968). Environmental and genotype-environmental components of variability. III. Multiple lines and crosses. Heredity, 23, 339-356. [Google Scholar]
  17. Plaisted, R. L. and L. C. Paterson (1959). A technique for evaluating the ability of selections to yield consistently in different locations or seasons. Am. Patato J., 36, 381-385. [Google Scholar]
  18. Shukla, G. K. (1972). Some statistical aspects of partitioning genotype–environmental components of variability. Heredity, 29, 237-245. [Google Scholar]
  19. Singh S., V.V. Singh and A.D. Choudhary (2014). Genotype × environment interaction and yield stability analysis in multienvironment. Trop. Subtrop. Agroecosyst., 17, 477 – 482. [Google Scholar]
  20. Xu, N., M. Fok., G. Zhang., J. Li. and Z. Zhou (2013). The application of GGE Bi-plot analysis for evaluating test locations and mega-environment investigation of cotton regional trials. J. Integr. Agric. Adv. 13(9), 1921-1923. [Google Scholar]
  21. Westcott, B (1986). Some methods of analysing genotype - environment interaction. Heredity, 56, 243-253. [Google Scholar]
  22. Yan, W., L. A.Hunt, Q. Sheng and Z. Szlavnics (2000). Cultivar evaluation and mega-environment Investigation based on the GGE biplot. Crop Sci., 40, 597-605.    [Google Scholar]