Deciphering genotype-by-environment interaction for targeting test environments and genotypes resistant to wheat stem rust disease.

Autor: Abate, Fentaw, Mehari, Hailay, Ahmed, Seid, Odong, Thomas, Rubaihayo, Patrick
Zdroj: Journal of Crop Science & Biotechnology; Dec2023, Vol. 26 Issue 5, p585-594, 10p
Abstrakt: Stem rust disease (UG99) caused by the fungus Puccinia graminis f. sp. Tritici has a negative significant impact on the world's wheat production. Host-plant resistance is the most efficient and practical strategy used for managing this disease, hence, breeding for stem rust resistance continues to be an integral part of the genetic improvement of wheat. Twenty-one wheat genotypes including advanced breeding lines, released varieties and a susceptible check (Morocco) were evaluated for their response to stem rust disease across 6 environments in Ethiopia. Genotypes (G), environment (E), and Genotype x environment interactions (GEI) were examined by biplot which partitioned the main effect into G, E, and GEI with significant levels (P ≤ 0.001) being obtained from final rust severity data. The results revealed that genotypes had contributed 58.92% of resistance variation followed by GEI and E with 28.68% and 3.97% of the total effects, respectively. AMMI biplot and GGE biplot techniques enabled us to identify two stable genotypes (G12 and G60) based on their performance across diverse environments, while G31 and G52 showed specifically good resistance performance on Debrezeit and Kulmsa testing environments. The GGE biplot method also identified Lay-Gaint as the ideal test environment with a high representative and better discriminative power for selecting durable rust-resistant genotypes, while Sali was the least desirable test environment. In addition, the GGE biplot analysis identified two distinct mega-environments (ME1 and ME2) for rust severity in Ethiopia. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index