AMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environments

Kibreab Yosefe Wodebo; Taye Tolemariam; Solomon Demeke; Weyessa Garedew; Tessema Tesfaye; Muluken Zeleke; Deribe Gemiyu; Worku Bedeke; Jane Wamatu; Mamta Sharma

doi:10.3390/plants12173064

AMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environments

Plants (Basel). 2023 Aug 25;12(17):3064. doi: 10.3390/plants12173064.

Authors

Affiliations

¹ College of Agriculture and Veterinary Medicine, Jimma University, Jimma P.O. Box 307, Ethiopia.
² Bonga Agricultural Research Center, Bonga P.O. Box 101, Ethiopia.
³ Arba Minch Agricultural Research Center, Arba Minch P.O. Box 2228, Ethiopia.
⁴ International Centre for Agricultural Research in Dry Areas, Addis Ababa P.O. Box 5689, Ethiopia.
⁵ South Agricultural Research Institute (SARI), Hawassa P.O. Box 06, Ethiopia.
⁶ International Crops Research Institute for the Semi-Arid Tropics, Hyderabad P.O. Box 502324, India.

Abstract

This paper reports an evaluation of eleven oat genotypes in four environments for two consecutive years to identify high-biomass-yielding, stable, and broadly adapted genotypes in selected parts of Ethiopia. Genotypes were planted and evaluated with a randomized complete block design, which was repeated three times. The additive main effect and multiplicative interaction analysis of variances revealed that the environment, genotype, and genotype-environment interaction had a significant (p ≤ 0.001) influence on the biomass yield in the dry matter base (t ha^-1). The interaction of the first and second principal component analysis accounted for 73.43% and 14.97% of the genotype according to the environment interaction sum of squares, respectively. G6 and G5 were the most stable and widely adapted genotypes and were selected as superior genotypes. The genotype-by-environment interaction showed a 49.46% contribution to the total treatment of sum-of-squares variation, while genotype and environment effects explained 34.94% and 15.60%, respectively. The highest mean yield was obtained from G6 (12.52 kg/ha), and the lowest mean yield was obtained from G7 (8.65 kg/ha). According to the additive main effect and multiplicative interaction biplot, G6 and G5 were high-yielding genotypes, whereas G7 was a low-yielding genotype. Furthermore, according to the genotype and genotype-environment interaction biplot, G6 was the winning genotype in all environments. However, G7 was a low-yielding genotype in all environments. Finally, G6 was an ideal genotype with a higher mean yield and relatively good stability. However, G7 was a poor-yielding and unstable genotype. The genotype, environment, and genotype x environment interaction had extremely important effects on the biomass yield of oats. The findings of the graphic stability methods (additive main effect and multiplicative interaction and the genotype and genotype-environment interaction) for identifying high-yielding and stable oat genotypes were very similar.

Keywords: AMMI; GGE; GXE Interaction; biomass yield; oat (Avena sativa L.).

Grants and funding

The current work was funded by South Agricultural Research Institute, Bonga Agricultural Research Center, and International Centre for Agricultural Research in Dry Areas.