Stability analysis of candidate bollgard bt cotton (Gossypium hirsutum L.) genotypes for yield traits
Paper Details
Stability analysis of candidate bollgard bt cotton (Gossypium hirsutum L.) genotypes for yield traits
Abstract
During varietal development process, multi-location trials are conducted to evaluate the performance of new cotton lines for yield potential and stability. Multi-location trials consisting of 89 candidate cotton genotypes were carried out at 10 locations under different agro-climatic zones. Presence of Cry1Ac gene of Mon-531 event was verified using isolated DNA and event-specific primers in PCR. Toxic cry protein was identified using qualitative strip test from ten randomly selected plants. To assess genotype by environment interaction and to evaluate the stability and adaptability, data were analyzed using GGE-biplot approach. Two mega environments were found and Ghotki (SG) was ideal location with maximum discriminative and representative properties. Genotype, MNH-1026 (1) performed best in all locations and proved to be an ideal genotype with maximum stability and adoptability followed by GH-Deebal (2). Hence, this information will be very useful for cotton breeders who intend to develop high yielding, widely adopted and stable genotypes, and be helpful for variety registration/approval departments for giving general and specific recommendations.
Ali I, Naqib UK, Fida M, Muhammad AI, Ammad A, Farhatullah, ZB, Sardar A, Ibni AK, Sheraz A, Mehboob R. 2017. Genotype by environment and GGE-biplot analyses for seed cotton yield in upland cotton. Pakistan Journal of Botany49, 2273-2283.
Baloch M, Baloch W, Baloch MK, Mallano A, Baloch M, Baloch NJ, Abro S. 2015. Association and heritability analysis for yield and fibre traits in promising genotypes of cotton (Gossypium hirsutum L.). Sindh University Research Journal 47, 303-306.
Blanche SB, Myers GO, Zumba JZ, Caldwell D, Hayes J. 2006. Stability comparisons between conventional and near-isogenic transgenic cotton cultivars. Journal of Cotton Science 10, 17-28.
Farias FJC, Carvalho LP, Silva Filho JL, Teodoro PE. 2016. Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. Genetics and Molecular Research 15, gmr15028009. https://doi.org/10.4238/gmr.15028009
Gomez KA, Gomez AA. 1984. Statistical Procedures for Agricultural Research (2nd ed.). John Wiley & Sons Inc. New York. USA.
Hicks CR. 1982.Fundamental concepts in the design of experiments. CBS College Publ. New York.
Maleia MP, Afonso R, Leonel DM, Jaime OT, Fátima C, Edson J, Joaquim ND, Badrodine AA. 2017. Stability and adaptability of cotton (Gossypium hirsutum L.) genotypes based on AMMI analysis. Australian Journal of Crops Science 11, 367-372. https://doi.org/10.21475/ajcs.17.11.04.pne60
Mukoyi F, Mubvekeri W, Kutywayo D, Muripira V, Mudada N. 2015. Development of elite medium staple cotton (G. hirsutum L.) genotypes for production in middle veld upland ecologies. African Journal of Plant Science 9, 1-7. https://doi.org/10.5897/AJPS2014.1236
Orawu M, Gladys A, Lastus S, George O, Chris O. 2017. Yield stability of cotton genotypes at three diverse agro-ecologies of Uganda. Journal of Plant Breeding and Genetics 5, 101-114.
Pretorius MM Allemann J, Smith MF. 2015. Use of the AMMI model to analyse cultivar-environment interaction in cotton under irrigation in South Africa. African Journal of Agriculture2, 76-80.
Rogers SO, Bendich AJ. 1985. Extraction of DNA from milli-gram amounts of fresh, herbarium and mummified plant tissues. Plant Molecular Biology5, 69–76. https://doi.org/10.1007/BF00020088
Tukamuhabwa P, Asiimwe M, Nabasirye M, Kabayi P, Maphosa M. 2012. Genotype by environment interaction of advanced generation soybean lines for grain yield in Uganda. African Crop Science Journal20, 107-115.
Xu N, Fok M, Zhang G, Li J, Zhou Z. 2014. The application of GGE Bi-plot analysis for evaluating test locations and mega-environment investigation of cotton regional trials. Journal of Integrative Agriculture 13, 1921-1933. https://doi.org/10.1016/S2095-3119(13)60656-5
Yan W. 2015. Mega-environment analysis and test location evaluation based on unbalanced multiyear data. Crop Science 55, 113-122. https://doi.org/10.2135/cropsci2014.03.0203
Yan W, Kang MS. 2003. GGE Bi-plot analysis: A graphical tool for Breeders, Geneticists and Agronomists. Florida, USA: CRC, Press.
Yan W, Hunt LA, Sheng QL, Szlavnics Z. 2000. Cultivar evaluation and mega-environment investigation based on GGE bi-plot. Crop Science 40, 596-605. https://doi.org/10.2135/cropsci2000.403597x
Yan W, Kang MS, Ma B, Woods S, Cornelius PL. 2007.GGE Bi-plot vs. AMMI Analysis of Genotype-by-Environment Data. Crop Science 47, 643-655. https://doi.org/10.2135/cropsci2006.06.0374
Yan WK. 2001. GGE biplot-A windows application for graphical analysis of multi-environment trial data other types of two-way data. Agronomy Journal 93, 1111-1118. https://doi.org/10.2134/agronj2001.9351111x
Yang L, Pan A, Zhang K, Yin C, Qian B, Chen J, Huang C, Zhang D. 2005. Qualitative and quantitative PCR methods for event-specific detection of genetically modified cotton Mon1445 and Mon531.Transgenic Research 14, 817-3. https://doi.org/10.1007/s11248-005-0010-z
Zeng L, Meredith WR, Campbell BT, Dever JK, Zhang J, Glass KM, Jones AS, Myers GO, Bourland FM. 2014. Genotype-by-Environment Interaction Effects on Lint Yield of Cotton Cultivars across Major Regions in the U.S. Cotton Belt. The Journal of Cotton Science18, 75-84.
Muhammad Zaffar Iqbal, Shahid Nazir, Sajid-ur-Rahman, Muhammad Younas, 2018. Stability analysis of candidate bollgard bt cotton (Gossypium hirsutum L.) genotypes for yield traits. Int. J. Biosci., 13(5), 55-63.
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