Additive main effects and multiplicative interaction and yield stability index for genotype by environment analysis and wider adaptability in Barley

Abstract

Genotype by environment interaction distorts genetic analysis, changes relative ranking of genotypes and a major obstruction for varietal release. AMMI model is a quick and relevant tool to judge environmental behaviour and genotypic stability in comparison to ANOVA, multiplicative model and linear regressions. We evaluated 19 barley genotypes grown at 08 diverse locations to identify discriminating environments and ideal genotypes with dynamic stability. In AMMI ANOVA, the locations and genotype by environment interaction exhibited 66% and 14.7% of the total variation. The initial first two principal components showed significant interaction with 36.0 and 28.4% variation, respectively. AMMI1 biplot showed that the environments Bawal, Ludhiana and Durgapura were high yielding with high IPCA1 scores and located far away from the biplot origin. However, in AMMI1and AMMI2 biplots the locations Hisar, Ludhiana, Karnal, Bathinda and Modipuram were found suitable with low IPCA2 scores. Yield stability index (YSI) was highly useful with ASV ranks and the genotypes DWRB150 and BH1013 and checks BH902, DWRUB52 and DWRB101 were selected for high grain yield and wider adaptability across the locations.

G × E models for yield adaptation and target environment analysis in barley (Hordeum vulgare)

“…Yield stability index (YSI): Yield stability index was calculated (5) as sum of overall yield (R y ) ranks and AMMI stability value (RASV) rank and a genotype with low YSI was considered desirable (Kumar et al 2018).…”

“…The use of GGE biplots has been also extended for diallel analysis, The performance of a genotype in multi-location trials is unpredictable and even response may be at lower rank of a superior genotype over a wide range of environments (Comstock andMoll 1963, Lins et al 1986). This inconsistent performance and differential response warranted plant breeders to study buffering capacity and adaptability of genotypes by any quick, relevant and easy statistical method (Kumar et al 2018). Therefore, a genotype with well buffering capacity and capability of dynamic stability is required for yield maximization and wider acceptance (Becker and Leon 1988).…”

Genotype by environment interaction (GEI) of maize varieties resistant to maize lethal necrosis for mid altitudes of Rwanda

“…The YSI and or the ASVs have been used to identify superior genotypes in several crops (Farshadfar et al 2011;Oliveira et al 2013;Kumar et al 2018) The use of YSI, in this study, has allowed identifying the varieties: RHMM113, RHM1407, RHM1409, and RHM1402 having excellent performance (YSI<10). The varieties RHM113, RHM1407, RHM1409, and RHM1402 were identified as superior genotypes by combing the AMM1 biplot and YSI.…”

Identification of effective sources for spot blotch and stripe rust in barley

“…Barley is one of the oldest crops presumably domesticated nearly ten thousand years ago and further moved from its origin in the 'Fertile Crescent' (Middle East) to the rest of the world (Baik and Ullrich, 2008;Kumar et al, 2018). The uses of the crop are very wide from food and feed to malting and brewing purposes.…”