Data from: Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials

Kaio Olímpio Das Graças Dias, Salvador Alejandro Gezan, Claudia Teixeira Guimarães, Alireza Nazarian, Luciano Da Costa E Silva, Sidney Netto Parentoni, Paulo Evaristo De Oliveira Guimarães, Carina De Oliveira Anoni, José Maria Villela Pádua, Marcos De Oliveira Pinto, Roberto Willians Noda, Carlos Alexandre Gomes Ribeiro, Jurandir Vieira De Magalhães, Antonio Augusto Franco Garcia, João Cândido De Souza, Lauro José Moreira Guimarães & Maria Marta Pastina
Breeding for drought tolerance is a challenging task that requires costly, extensive and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here we evaluated the accuracy of genomic selection of additive (A) against additive+dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multi-environment trials. Phenotypic data of five drought-tolerance traits...
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