Analysis of genotype x environment interaction and seed yield stability of sesame in Northern Ethiopia

Abstract

The experiment was conducted in Northern Ethiopia from 2011-2013 under rain fed conditions in a total of seven environments vis. E1, E2, E3, E4, E5, E6 and E7. The objective of the study was to evaluate the adaptability and stability of sesame genotypes across environments. 13 sesame genotypes were evaluated and the experiment was laid out in a Randomized Complete Block Design with three replications. The average grain yield of the genotypes was 742.9 Kg/ha with the outstanding genotypes being G4 (926.8 kg/ha), G1 (895.1 kg/ha) and G12 (832.7 kg/ha) respectively, and low the yielding genotype was G9 (614.3 kg/ha). The combined ANOVA for grain yield showed significant effects of the genotypes, environments and genotype x environment interaction. According to the additive main effect and multiplicative interaction bi-plot (AMMI bi-plot) and Genotype x Environment interaction biplot (GGE bi-plot) G12 was the most stable, and G7, G8 and G9 were the unstable genotypes. Furthermore, the Genotype main effects and GGE bi-plot showed E5 as the most discriminating and representative environment. The GGE bi-plot also identified two different growing environments, the first environment containing E4 and E6 (in the Dansha area) with the wining genotype G1; and the second environment encompassing E1, E2, E3, E5 and E7 (in the Humera, Dansha and Sheraro areas) with winning genotype of G4.

AMMI and GGE Biplot Analysis for Seed Yield and Oil Content of Sesame (Sesamum indicum L.) Genotypes in Tigray Northern Ethiopia

“…E3, E10, E6, E4 and E9 were far from the ideal environment and considered as unstable (Figure 4). This result was in line with Yan, et al [32] and Fiseha, et al [12] presented in (Figure 3). The mean oil content of genotypes were inconsistent across locations due to environmental factors.…”

“…Among high yielded genotypes, G1, G7, and G3 showed 18.85%, 7.30% and 1.34% yield advantage over the recently released and 34.25%, 22.75% and 16.75% over the local varieties, respectively. Changing sesame yield performance with environments reported by Fiseha, et al [12], Mekonnen, et al [21] and Mohammed [22] in sesame.…”

“…"which-won-where" pattern), whereby specific genotypes can be recommended to specific mega-environments Yan and Kang [8], 2) genotype evaluation (the mean performance and stability), and 3) environmental evaluation (the power to discriminate among genotypes in target environments). Sabaghnia, et al [9] and Farshadfar, et al [10] in wheat; Munawar, et al [11] and Fiseha, et al [12] in sesame are among the many authors who used GGE bi-plot to identify mega environments, to evaluate the genotypes and to test the environments. GGE bi-plot is able to show the best genotype with the highest yield in a quadrant containing identical locations (Mega-Environments), genotype average performance and stability, ideal genotype and ideal location to increase yield and specific location.…”

Genotype X environment Interaction and Stability of Oil Content of Sesame (Sesamum indicum L.) Genotypes in Northern Ethiopia

“…This study is aimed to identify and supply high yielding and stable oil content sesame variety/ies and investigating the magnitude of GEI. GEI investigation is a challenge and an opportunity for plant breeders (Fiseha et al, 2016). Because it complicates cultivar recommendation due to the inconsistency of high yielding material across different environments.…”

Genotype environment interaction and stability of oil content of sesame (Sesamum indicum L.) genotypes in Northern Ethiopia

“…So this study is important in identifying and supplying with high and stable oil content sesame variety/ies. Genotype x environment interaction (GEI) is both a challenge and an opportunity for plant breeders (Fiseha et al, 2015). Because it complicates cultivar recommendation due to the inconsistency of high yielding material across different environments.…”