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Genotype × environment interaction and grain yield stability of quality protein maize hybrids under stress and non-stress environments

Authors :
Bitew Tilahun Engida
Amsal Tarekegne
Dagne Wegary
Angeline Van Biljon
Maryke T. Labuschagne
Source :
Cogent Food & Agriculture, Vol 10, Iss 1 (2024)
Publication Year :
2024
Publisher :
Taylor & Francis Group, 2024.

Abstract

AbstractEvaluation of maize varieties under multiple environments, including drought and low nitrogen (N) stressed sites is an important breeding approach, to identify well adapted and stable maize varieties. This study was undertaken to identify new quality protein maize (QPM) hybrids that have good agronomic performance and assess the presence of genotype by environment (G × E) interaction and grain yield stability of QPM hybrids under different environment conditions. Forty-five hybrids, including two QPM, two non-QPM and one local check were evaluated across 34 environments under stress and non-stress conditions in Ethiopia, Zimbabwe, Zambia, Mozambique, and Malawi during 2018 to 2020. Additive Main Effects and Multiplicative Interaction (AMMI) and Genotype main effects plus G × E interaction (GGE) bi-plots were used for stability analysis. Environment, genotype and G × E interaction effects were significant for grain yield and other traits in all management conditions. The top yielding hybrids were 44 (QS7646) 12 (CZH15099Q) under optimum; 14 (CZH15142Q), 44 (QS7646) and 23 (CZH17192Q) under random stress; 9 (CZH142237Q) and 10 (CZH142238Q) under managed drought; and 14 (CZH15142Q) and 34 (CZH17203Q) under low N conditions. Among these, 10 (CZH142238Q) and 14 (CZH15142Q) were the most stable hybrids and can be recommended for release in sub-Saharan Africa to improve food and nutritional security of smallholder farmers who depend on maize. Kwekwe (KWE), Bindura (BIN), Chokwe (CHO) and Bako (BK2) were identified as the most discriminating and representative for optimum, random stress, managed drought and low N environments, respectively and help to identify superior hybrids.

Details

Language :
English
ISSN :
23311932
Volume :
10
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Cogent Food & Agriculture
Publication Type :
Academic Journal
Accession number :
edsdoj.34b6653b1fc84498a45b1d8907867d5f
Document Type :
article
Full Text :
https://doi.org/10.1080/23311932.2024.2324537