Amaral, L.d.O.; Miranda, G.V.; Souza, J.d.S.; Moitinho, A.C.R.; Cristeli, D.S.; Silva, H.K.d.; Anjos, R.S.R.d.; Alliprandini, L.F.; Unêda-Trevisoli, S.H.
Application of Artificial Neural Networks to Predict Genotypic Values of Soybean Derived from Wide and Restricted Crosses for Relative Maturity Groups. Agronomy 2023, 13, 2476.
https://doi.org/10.3390/agronomy13102476
AMA Style
Amaral LdO, Miranda GV, Souza JdS, Moitinho ACR, Cristeli DS, Silva HKd, Anjos RSRd, Alliprandini LF, Unêda-Trevisoli SH.
Application of Artificial Neural Networks to Predict Genotypic Values of Soybean Derived from Wide and Restricted Crosses for Relative Maturity Groups. Agronomy. 2023; 13(10):2476.
https://doi.org/10.3390/agronomy13102476
Chicago/Turabian Style
Amaral, LÃgia de Oliveira, 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, and Sandra Helena Unêda-Trevisoli.
2023. "Application of Artificial Neural Networks to Predict Genotypic Values of Soybean Derived from Wide and Restricted Crosses for Relative Maturity Groups" Agronomy 13, no. 10: 2476.
https://doi.org/10.3390/agronomy13102476
APA Style
Amaral, L. d. O., Miranda, G. V., Souza, J. d. S., Moitinho, A. C. R., Cristeli, D. S., Silva, H. K. d., Anjos, R. S. R. d., Alliprandini, L. F., & Unêda-Trevisoli, S. H.
(2023). Application of Artificial Neural Networks to Predict Genotypic Values of Soybean Derived from Wide and Restricted Crosses for Relative Maturity Groups. Agronomy, 13(10), 2476.
https://doi.org/10.3390/agronomy13102476
