Stability analysis of wheat genotypes under rainfed timely sown trials in Northern Hills Zone of India by Additive main & multiplicative interactions (AMMI) analysis observed highly significant effects of the environment, GxE interaction and genotypes during 2018-19 and 2019-20. The ranking of genotypes had altered with utilization of more number of IPCA’s in AMMI and WAASB measures. Environments contributed about 53%, GxE interaction accounted for 30.5% and Genotypes explained only 5.4% of the total sum of squares due to treatments in the first year. Wheat genotypes HS668, VL2035, VL2036 , HS562 had been selected by Analytic measures of adaptability and Superiority indexes. Different quadrants comprised of a cluster of arithmetic, geometric, harmonic means along with corresponding adaptability measures. Superiority Indexes considering averages grouped separately. This group maintained the right angles with a group of MASV & MASV1 measures. Clustering of Adaptability measures as per arithmetic, geometric and harmonic means placed in a quadrant. Second-year reflected VL2041, HS675, HS676 & HS562, HPW471 genotypes selected by adaptability and superiority indexes. About 68% of the total variation with 38.4% and 30.2% contributions by PC1 & PC2. Adaptability measures maintained the right angle with other stability measures, with the exception of Superiority indexes. There is an additional advantage with these measures to assign variable weights to the yield and stability as per the goal of breeding trials. These indexes have the potential to provide reliable estimates of genotypes in future studies as they are considered more number of significant IPCA’s in biplots.
AMMI model, Biplot analysis, MASV, SI, WAASB
Ajay, B. C., Aravind, J., Fiyaz, R. A., Kumar, N., La, l. C., Kona, P., Dagla, M. C. and Bera, S. K. (2019). Rectification of modified AMMI stability value (MASV). Indian J. Genet., 79(4), 726-731
Ajay, B.C., Bera S.K., Singh A.L., Kumar N., Gangadhar K. and Kona, P. (2020). Evaluation of Genotype?×?Environment interaction and yield stability analysis in peanut under phosphorus stress condition using stability parameters of AMMI Model. Agric. Res., 9, 477–486
Annicchiarico, P. (1992). Cultivar adaptation and recommendation from alfalfa trials in northern Italy. Journal of Genetics and Plant Breeding, 46, 269-278
Bocianowski, J., Niemann J and Nowosad, K. (2019). Genotype-by environment interaction for seed quality traits in interspecific cross-derived Brassica lines using additive main effects and multiplicative interaction model. Euphytica, 215(7),1–13
Farshadfar, E. (2008). Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat. Pak J Biol Science 11:1791–1796
Farshadfar, E., Mahmodi N. and Yaghotipoor, A. (2011). AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.). Aust J Crop Science, 5,1837–1844
Gauch, H.G. (2013). A simple protocol for AMMI analysis of yield trials. Crop Science, 53,1860–1869
Kang, M.S. (1993). Simultaneous selection for yield and stability in crop performance trials: Consequences for growers. Agronomy Journal, 85,754-757
Lin, C.S. and Binns, M.R. (1988). A superiority measure of cultivar performance for cultivar x location data. Canadian Journal of Plant Science, 68, 193-198
Mendes, F. F., Guimarães L. J. M., Souza J. C., Guimarães, P. E. O., Pacheco C. A. P., Machado, J. R. de A., Meirelles, W. F., Silva A. R. da and Parentoni, S. N. (2012). Adaptability and stability of maize varieties using mixed model methodology. Crop Breeding and Applied Biotechnology 12(2), 111-117
Mohammadi, M, Sharifi, P., Karimizadeh, R., Jafarby, J.A., Khanzadeh, H., Hosseinpour, T., Poursiabidi, M.M., Roustaii, M., Hassanpour, H.M. and Mohammadi, P.(2015). Stability of grain yield of durum wheat genotypes by AMMI model. Agric For., 61(3), 181-193
Mohammadi, R. and Amri, A. (2008). Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica, 159, 419-432
Olivoto, T., Lucio, A. Dal’Col, Gonzalez, Silva J.A. da and Marchioro, V.S. (2019). Mean performance and stability in multi-environment trials I: Combining features of AMMI and BLUP techniques. Agronomy Journal, 111,1–12
Oyekunle, M., Menkir, A., Mani, H., Olaoye G., Usman, I.S., Ado, S. (2017). Stability analysis of maize cultivars adapted to tropical environments using AMMI analysis. Cereal Res. Commun., 45,336–345
Piepho, H.P., Mo¨hring J., Melchinger, A.E. and Bu¨chse, A. (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica 161(1),209–228
Rao, A.R. and Prabhakaran V.T. (2005). Use of AMMI in simultaneous selection of genotypes for yield and stability. Journal of the Indian Society of Agricultural Statistics, 59,76-82
Resende, M.D.V. (2007). Software Selegen – REML/BLUP: sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Embrapa Florestas, Colombo, 350p.
Resende, M.D.V. and Duarte J.B. (2007). Precision and Quality Control in Variety Trials. Pesquisa Agropecuaria Tropical, 37, 182-194
Zali, H., Farshadfar E., Sabaghpour S.H. and Karimizadeh R. (2012). Evaluation of genotype × environment interaction in chickpea using measures of stability from AMMI model. Ann Biol Res., 3,3126–3136
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