Application of Artificial Neural Networks to Predict Genotypic Values of Soybean Derived from Wide and Restricted Crosses for Relative Maturity Groups

Application of Artificial Neural Networks to Predict Genotypic Values of Soybean Derived from Wide and Restricted Crosses for Relative Maturity Groups

The primary objective of soybean-breeding programs is to develop cultivars that offer both high grain yield and a maturity cycle tailored to the specific soil and climatic conditions of their cultivation. Therefore, predicting the genetic value is essential for selecting and advancing promising geno...

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Bibliographic Details
Main Authors: Lígia de Oliveira Amaral, Glauco Vieira Miranda, Jardel da Silva Souza, Alyce Carla Rodrigues Moitinho, Dardânia Soares Cristeli, Hortência Kardec da Silva, Rafael Silva Ramos dos Anjos, Luis Fernando Alliprandini, Sandra Helena Unêda-Trevisoli
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Agronomy
Subjects:
variance components
<i>Glycine max</i>
machine learning
mixed models
REML/BLUP
Online Access:https://www.mdpi.com/2073-4395/13/10/2476

Internet

https://www.mdpi.com/2073-4395/13/10/2476

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