Assessment of yield performances for grain sorghum varieties by AMMI and GGE biplot analyses

Abstract

Grain sorghum is an exceptional source of dietary nutrition with outstanding economic values. Breeding of grain sorghum can be slowed down by the occurrence of genotype × environment interactions (GEI) causing biased estimation of yield performance in multi-environments and therefore complicates direct phenotypic selection of superior genotypes. Multi-environment trials by randomized complete block design with three replications were performed on 13 newly developed grain sorghum varieties at seven test locations across China for two years. Additive main effects and multiplicative interaction (AMMI) and genotype + genotype × environment (GGE) biplot models were adopted to uncover GEI patterns and effectively identify high-yielding genotypes with stable performance across environments. Yield (YLD), plant height (PH), days to maturity (DTM), thousand seed weight (TSW), and panicle length (PL) were measured. Statistical analysis showed that target traits were influenced by significant GEI effects (p < 0.001), that broad-sense heritability estimates for these traits varied from 0.40 to 0.94 within the medium to high range, that AMMI and GGE biplot models captured more than 66.3% of total variance suggesting sufficient applicability of both analytic models, and that two genotypes, G3 (Liaoza No.52) and G10 (Jinza 110), were identified as the superior varieties while one genotype, G11 (Jinza 111), was the locally adapted variety. G3 was the most stable variety with highest yielding potential and G10 was second to G3 in average yield and stability whereas G11 had best adaptation only in one test location. We recommend G3 and G10 for the production in Shenyang, Chaoyang, Jinzhou, Jinzhong, Yulin, and Pingliang, while G11 for Yili.

Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses

“…To visualize the distance between each genotype and the ideal genotype, concentric circles were drawn around the central circle that contains the ideal genotype. This approach helps to understand the relationship between genotypes and their proximity to the ideal genotype [ 30 , 59 , 140 ].…”

Influence of Genotype × Environment Interaction on Yield Stability of Maize Hybrids with AMMI Model and GGE Biplot

“…The GGE biplot can also be used for breeding-specific combining ability and general combining ability evaluation [17], disease evaluations [18], crop qualitative characteristics [19,20], and regional trial evaluations [21]. And the AMMI model GGE biplot has now been applied to cotton [21], oat [22], pigeonpea [23], cowpea [24], bambara groundnut [25], grain sorghum [26], as well as maize [27,28]. In previous studies, the yield of maize in one year was mostly analyzed by the AMMI model and GGE biplot or by a single method, and few were analyzed by combining the two methods for many years [11,[29][30][31][32].…”