Genotype and genotype by environment interaction and grain yield stability of medium maturity groups of soybean [Glycine max (L.) Merrill] varieties in Western Oromia, Ethiopia

Abstract

The objectives of this study were to identify high yielding and stable medium maturity soybean varieties across environment and examine the influence of genotype × environment interaction (GEI) on grain yield of soybean varieties in western Oromia. Seven early soybean varieties were evaluated at five locations (Bako, Gute, Billo, Chewaka and Uke) using randomized complete block design (RCBD) with three replications for two consecutive years (2016 and 2017). Combined analysis of variance showed that grain yield was significantly (P<0.01) affected by environments, genotypes and GEI. The environment, genotype and genotype by environment interaction accounted for 57.4, 20.9 and 19.8% variations, respectively. The first two principal components (IPCA 1 and IPCA 2) were used to create a two-dimensional genotype and genotype by environment interaction (GGE) biplot and explained 68.9 and 15.6% of the total sums of squares of GEI, respectively. According to the average environment coordination (AEC) views of the GGE-biplot, soybean variety Didhessa and Hawassa-04 were identified as the most stable and high yielding varieties. In addition, Didhessa and Hawassa-04 also showed better stability performance according to AMMI stability value (ASV), genotypic selection index (GSI), Wricke's ecovalence and cultivar superiority measure among the evaluated varieties whereas variety Davis and AFGAT were identified as the least stable and low yielding variety. Therefore, among medium maturing soybean varieties, Didhessa, Hawassa-04 and Cheri were recommended for further production in most soybean growing areas of western Oromia.

AMMI and GGE-biplot Analysis of the Yield Performanceand Stability of Medium-Mature Soybean [Glycine max (L.) Merrill] Genotyped Plantsin Southern and Northwestern Ethiopia

“…As a result, stable genotypes for a particular environment could be generated. This result is consistent with many studies that have shown a signi cant interaction between soybean genotypes and their environment [11,12]. Given that the genotypes exhibited different grain yield rankings across environments, the G*E interaction crossover (qualitative type) has strong implications for breeding for a particular adaptation [13] (Table 3).…”

AMMI and GGE-biplot Analysis of the Yield Performance and Stability of Medium-Mature Soybean [Glycine max (L.) Merrill] Genotypes in Southern and Northwestern Ethiopia

“…As a result, stable genotypes for a particular environment could be generated. This result is consistent with many studies that have shown a signi cant interaction between soybean genotypes and their environment [11,12]. Given that the genotypes exhibited different grain yield rankings across environments, the G*E interaction crossover (qualitative type) has strong implications for breeding for a particular adaptation [13] (Table 3).…”

Grain yield stability of soybean (Glycine Max (L.) Merrill) for different stability models across diverse environments of Ethiopia

“…In Ethiopia, the application of AMMI and site regression model GGE models for explaining and analyzing the performance of genotypes and the tested environments have been very frequent among plant breeder in recent years. Various studies have been conducted in Ethiopia to analyze the effects of GEI on soybean genotypes (Gurmu et al., 2009; Asfaw et al., 2009; Adane et al., 2018), but only a few studies use the GGE biplot model. The studies on BLUP models and that of its graphics WAASB index has not been reported so far.…”