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Assessing genotype-by-environment interactions for maydis leaf blight disease in maize (Zea mays L.) germplasm and identification of stable donors for breeding resistant hybrid varieties

By: Contributor(s): Material type: ArticleArticleLanguage: English Publication details: Cambridge University Press, 2024. United Kingdom :ISSN:
  • 1479-2621
  • 1479-263X (Online)
Subject(s): In: Plant Genetic Resources In pressSummary: This study investigates the impact of environmental factors and genotype-by-environment interactions (GEI) on the expression of maydis leaf blight (MLB) resistance in a diverse maize germplasm comprising 359 genotypes. Extensive field trials were conducted, involving artificial inoculations and disease scoring across two locations over two years. Using genotype and genotype-environment (GGE) biplot analysis based on the site regression model (SREG), we identified stable MLB-resistant 10 donors with consistent genotypic responses. These inbred lines, which consistently exhibited disease scores of <= 3 across locations, are recommended as potential parents for breeding MLB-resistant varieties. Furthermore, the identification of a non-crossover interaction and high correlations among testing locations allowed us to define a single mega-environment for the initial screening of MLB resistance in a large set of maize germplasm. This study suggests that initial screenings can be efficiently conducted in one representative location, with validation of resistant lines at multiple sites during advanced breeding stages. This approach optimizes the use of land, labour and resources in MLB resistance testing.
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This study investigates the impact of environmental factors and genotype-by-environment interactions (GEI) on the expression of maydis leaf blight (MLB) resistance in a diverse maize germplasm comprising 359 genotypes. Extensive field trials were conducted, involving artificial inoculations and disease scoring across two locations over two years. Using genotype and genotype-environment (GGE) biplot analysis based on the site regression model (SREG), we identified stable MLB-resistant 10 donors with consistent genotypic responses. These inbred lines, which consistently exhibited disease scores of <= 3 across locations, are recommended as potential parents for breeding MLB-resistant varieties. Furthermore, the identification of a non-crossover interaction and high correlations among testing locations allowed us to define a single mega-environment for the initial screening of MLB resistance in a large set of maize germplasm. This study suggests that initial screenings can be efficiently conducted in one representative location, with validation of resistant lines at multiple sites during advanced breeding stages. This approach optimizes the use of land, labour and resources in MLB resistance testing.

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