Genotype-environment interaction and stability analysis in hybrid rice: an application of additive main effects and multiplicative interaction

Abstract

Genotype-environment interaction and stability performance were investigated on amylase, protein and grain yield with 13 hybrid rice promising combinations in five environments. The combined ANOVA showed that the mean sum of square due to genotype (G), environment (E) and G × E interaction were significant for amylose content, protein content and grain yield. This suggests a number of variabilities among the genotypes and environments as and the indicated genotypes interacted significantly with environments. The Additive Main Effects and Multiplicative Interaction (AMMI) biplot for yield clearly indicated that the hybrids BR10A/BR12R, II32A/BR15R, II32A/BR16R, II32A/BR10R, BR9A/BR15R, BRRI hybrid dhan2 and BRRI hybrid dhan3 were high yielding, stable and had general adaptability at all locations. The AMMI estimation had a profound effect in producing sharp and stratified ranking patterns and on this basis BRRI hybrid dhan2 would be considered more adapted to a wide range of environments than the rest of the genotypes. The biplot technique was used to identify appropriate genotype to special locations. This consideration on the basis of average yield for specific genotype to the specific location. The hybrid combination II32A/BR12R was more suitable for Gazipur location and the hybrid combination BR10A/BR13R was considered for Comilla region. Barisal was more stable site than other location for grain yield due to IPCA score near zero which had no interaction effect.

G x E INTERACTION OF YIELD AND YIELD CONTRIBUTING CHARACTERS IN CHILLI (Capsicum frutescens L.) USING AMMI MODEL

“…BD-2122 showed negative Pi, significant bi and insignificant S 2 di indicated their suitability to the poor environment. These results are in agreement with Kulsum et al (2013).…”

“…Suryamukhi showed negative phenotypic index, significant Bi and insignificant deviation from regression indicated the suitability to the poor environment. These results agreed with the findings of Kulsum et al (2013), Silveira and Vencovsky (1983) in case of rice grain yield. Pi = Phenotypic index, bi = Regression coefficient, S 2 di = Deviation from regression, * indicates slopes significantly different from the slope for the overall regression which is 1.0 Environmental indices (Ij) in Table 3 indicate that, Env-2 was highly favorable for chili production for all the traits where Env-4 was found poor.…”

“…The genotypes showing positive phenotypic index (Pi) with insignificant regression coefficient (bi) and deviation from regression (S 2 di), indicates the stability of genotypes over the environments (Kulsum et al, 2013). Kalo Dhawna morich showed positive Pi, significant bi and insignificant S 2 di indicating the high responsiveness to the rich environments.…”

Genotype and environment interaction of drought tolerant rice genotypes evaluated in drought prone areas of Bangladesh

“…Hence, IR82635-B-B-145-1 was identified as specially adapted to Lalmonirhat (E3) and this environment was considered as the wide range suitable environment for the genotype. Similar outcome has reported by Das et al, (2010) and Kulsum et al, (2013). Since, Lalmonirhat (E3) had positive IPCA1 score and nearest to zero from other environments and hence had medium interaction effects indicating that all the genotypes performed well in these locations.…”

“…IR83376-B-B-130-2, BRRI dhan57 (Ck) and BINA dhan7 (Ck) were also adapted to favorable environments. Asenjo et al, (2003), Das et al, (2010) and Kulsum et al, (2013) analyzed G × E interaction in rice by AMMI model. They found significant G × E interaction for grain yield and stated the usefulness of AMMI analysis for selection of genotypes for specific location/environment.…”