Author

M. Pastina

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Open access Sep 2026

Genomic selection using random regression to predict hybrid performance in untested environments by leveraging environmental data

Genotype‐by‐environment interaction (G×E) remains one of the major challenges to achieving genetic gains in tropical maize ( Zea mays L.) breeding. To address this, we implemented the geographic information system–factor analytic (GIS‐FA) framework, which integrates factor‐analytic (FA) models with environmental...

Thiago C. Brommonschenkel, M. Pastina, Márcio F. R. Resende et al. · Crop science · 0 citations

Open access Aug 2026

Multi-Environment Multi-Locus Association Mapping Reveals Genomic Regions for Drought-Related Traits in Tropical Maize.

Maize grain yield is frequently constrained by water scarcity, particularly in tropical regions characterized by irregular rainfall patterns. Dissecting the genetic basis of drought-related traits remains challenging because their expression is strongly influenced by environmental conditions. In this study, we applied...

Carina de Oliveira Anoni, Kaio Olímpio das Graças Dias, Martin P. Boer et al. · G3 · 0 citations