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Cited article:

Envirotype approach for soybean genotype selection through the integration of georeferenced climate and genetic data using artificial neural networks

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Euphytica 220 (1) (2024)
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Claudio Carlos Fernandes Filho, Sanzio Carvalho Lima Barrios, Mateus Figueiredo Santos, Jose Airton Rodrigues Nunes, Cacilda Borges do Valle, Liana Jank and Esteban Fernando Rios
(2023)
https://doi.org/10.1101/2023.03.20.533513

Complex Trait Prediction from Genome Data: Contrasting EBV in Livestock to PRS in Humans

Naomi R. Wray, Kathryn E. Kemper, Benjamin J. Hayes, Michael E. Goddard and Peter M. Visscher
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Predicting Longitudinal Traits Derived from High-Throughput Phenomics in Contrasting Environments Using Genomic Legendre Polynomials and B-Splines

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G3: Genes|Genomes|Genetics 9 (10) 3369 (2019)
https://doi.org/10.1534/g3.119.400346

Interaction of genotype-environment Nellore cattle using models of reaction

Wéverton José Lima Fonseca, Wéverson Lima Fonseca, Carlos Syllas Monteiro Luz, Gioto Ghiarone Terto e Sousa, Marcelo Richelly Alves de Oliveira, Karen Jamile Viana de Sousa, Mardoqueu Bruno Guimarães Costa, Augusto Matias de Oliveira and Severino Cavalcante de Sousa Júnior
Journal of Animal Behaviour and Biometeorology 3 (3) 86 (2015)
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Quantitative Trait Locus Analysis of Longitudinal Quantitative Trait Data in Complex Pedigrees

Stuart Macgregor, Sara A. Knott, Ian White and Peter M. Visscher
Genetics 171 (3) 1365 (2005)
https://doi.org/10.1534/genetics.105.043828