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Genotype by Environment Interaction and Grain Yield Stability of Striga Resistant Sorghum [<i>Sorghum bicolor</i> (L.) Moench] Genotypes in Ethiopia


Fantaye Belay
Firew Mekbib
Taye Tadesse

Abstract

Forty-nine sorghum varieties (hybrids and open pollinated) were evaluated across five environments during the 2016 main cropping season. The  objectives of this study were to estimate the magnitude and nature of genotype by environment interaction for grain yield and to determine yield  stability of striga resistant sorghum genotypes in the dry lowland areas of Ethiopia. The study was conducted using a simple lattice design with two  replications. The result of the combined analysis of variance for grain yield revealed highly significant (P≤0.001) difference among environment (E),  genotype (G) and genotype × environment interaction (GxE). Environment explained 76.13% of the total variation, whereas G and GxE explained  11.21% and 12.66% of the total variation, respectively. The magnitude of the environment was 6.8 times greater than the genotype, implying that  most of the variation in grain yield was due to the environment. Based on combined analysis of variance over locations, the mean grain yield of  environments ranged from 588 kg ha-1 at Humera to 4508 kg ha-1 at Sheraro. The highest yield was obtained from ESH-1 (3278 kg ha-1), while the  lowest was from K5136 (735 kg ha-1) and the average grain yield of genotypes were 2184 kg ha-1. AMMI and GGE biplot stability models were used  to identify stable genotypes for partitioning the GxE into the causes of variation and the best multivariate models in this study. Thus, AMMI model  was used to identify superior genotypes for specific and wide adaptation. Accordingly, K7439, K7252 and K7437 were specifically adapted to low  environments of Humera, Kobo and Fedis, whereas, ESH-1 and K7233 were the better hybrids for favorable environments of Mehoni and Sheraro,  respectively. Moreover, the GGE biplot identified two different sorghum growing mega-environments for grain yield. The first mega environment  includes higher (Mehoni) to low yielding (Humera, Kobo and Fedis) environments, respectively, with the winner genotype ESH-1 and the second  mega environment containing the highest yielding environment in Sheraro area with winner genotype K7233. Thus, the whichwon- where biplot  showed two winning genotypes in two mega environments. However, the standard hybrid check, ESH-1 won in most of the environments. Therefore,  ESH-1 can be recommended for wider cultivation due to better grain yield and stability performance across the test environments in the  dry lowland areas of Ethiopia.


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print ISSN: 2072-8506