Optimization of maize hybrids in the Brazilian Northeast: a multi-trait selection and envirotyping techniques in multi-environment trials
ABSTRACT: The objective of this study was to apply the envirotyping methodology to delineate macroenvironments (MEs) in the Brazilian Northeast. Multivariate analyses were conducted to investigate the relationship between genotype × environment interaction (G × E), stability, and the average perform...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidade de São Paulo
2025-05-01
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| Series: | Scientia Agricola |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162025000101105&lng=en&tlng=en |
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| Summary: | ABSTRACT: The objective of this study was to apply the envirotyping methodology to delineate macroenvironments (MEs) in the Brazilian Northeast. Multivariate analyses were conducted to investigate the relationship between genotype × environment interaction (G × E), stability, and the average performance of maize genotypes, to enhance corn adaptation to diverse environmental conditions. Twenty corn hybrids were cultivated across ten environments over two harvest seasons, with the following characteristics assessed in each environment: grain yield (GY), plant height (PH), ear height (EH), plant density (PD), and number of ears (NE). The target regions were characterized based on 19 environmental covariates (ECs) and a 23-year climatological series (2001-2023), which resulted in the identification of four MEs with similar climatic features. The interaction between genotype × macroenvironment × year significantly influenced the evaluated traits. The top five genotypes for each ME were identified using the multi-trait mean performance and stability index (MTMPS) which demonstrated favorable average performance and stability across multiple years seasons. The hybrids G03 and G04 were selected in three out of four MEs, indicating their stability and adaptability as hybrids. Envirotyping revealed a robust correlation between environments, enhancing the precision with which cultivars can be recommended for various locations within the same ME. The multivariate approach utilizing MTMPS proved effectively identified productive and stable genotypes tailored to each ME. |
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| ISSN: | 1678-992X |