Wheat genotypes as assessed by Additive main & multiplicative interactions (AMMI) and Best linear unbiased prediction (BLUP) for stability analysis under rainfed timely sown trials in Northern Hills Zone of India
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Abstract
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.
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AMMI model, Biplot analysis, MASV, SI, WAASB
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