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Article

Deep kernel and deep learning for genome-based prediction of single traits in multienvironment breeding trials

Crossa, J.; Martini, J.W.R.; Gianola, D.; Perez-Rodriguez, P.; Jarquín, D.; JULIANA P.; Montesinos-Lopez, O.A.; Cuevas, J. (Frontiers, 2019)

Article

Deep kernel for genomic and near infrared predictions in multi-environment breeding trials

Cuevas, J.; Montesinos-Lopez, O.A.; Juliana, P.; Guzman, C.; Perez-Rodriguez, P.; González-Bucio, J.; Burgueño, J.; Montesinos-Lopez, A.; Crossa, J. (Genetics Society of America, 2019)

Kernel methods are flexible and easy to interpret and have been successfully used in genomic-enabled prediction of various plant species. Kernel methods used in genomic prediction comprise the linear genomic best linear ...

Article

Joint use of genome, pedigree, and their interaction with environment for predicting the performance of wheat lines in new environments

Howard, R.; Gianola, D.; Montesinos-Lopez, O.A.; Juliana, P.; Singh, R.P.; Poland, J.A.; Shrestha, S.; Perez-Rodriguez, P.; Crossa, J.; Jarquin, D. (Genetics Society of America, 2019)

Genome-enabled prediction plays an essential role in wheat breeding because it has the potential to increase the rate of genetic gain relative to traditional phenotypic and pedigree-based selection. Since the performance ...

Article

Modeling genotype × environment interaction using a factor analytic model of on-farm wheat trials in the Yaqui Valley of Mexico

Vargas Hernández, M.; Ortíz-Monasterios, I.; Perez-Rodriguez, P.; Montesinos-Lopez, O.A.; Montesinos-Lopez, A.; Burgueño, J.; Crossa, J. (American Society of Agronomy, 2019)

On‐farm trials of bread and durum wheat in the Yaqui Valley region of southern Sonora, Mexico, were established for three cropping seasons (2012, 2013, and 2015) using the management practices implemented by farmers. The ...

Article

Genomic prediction with genotype by environment interaction analysis for kernel zinc concentration in tropical maize germplasm

Mageto, E.K.; Crossa, J.; Perez-Rodriguez, P.; Dhliwayo, T.; Palacios-Rojas, N.; Lee, M.; Rui Guo; San Vicente, F.M.; Zhang, X.; Hindu, V. (Genetics Society of America, 2020)

Article

Additive genetic variance and covariance between relatives in synthetic wheat crosses with variable parental ploidy levels

Puhl, L.; Crossa, J.; Munilla, S.; Perez-Rodriguez, P.; Cantet, R. (Oxford University Press, 2021)

Article

Bayesian regularized quantile regression: a robust alternative for genome-based prediction of skewed data

Perez-Rodriguez, P.; Montesinos-Lopez, O.A.; Montesinos-Lopez, A.; Crossa, J. (Elsevier, 2020)

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Deep kernel and deep learning for genome-based prediction of single traits in multienvironment breeding trials

Deep kernel for genomic and near infrared predictions in multi-environment breeding trials

Joint use of genome, pedigree, and their interaction with environment for predicting the performance of wheat lines in new environments

Modeling genotype × environment interaction using a factor analytic model of on-farm wheat trials in the Yaqui Valley of Mexico

A review of deep learning applications for genomic selection

Target population of environments for wheat breeding in India: definition, prediction and genetic gains

Application of multi-trait Bayesian decision theory for parental genomic selection

Genomic prediction with genotype by environment interaction analysis for kernel zinc concentration in tropical maize germplasm

Additive genetic variance and covariance between relatives in synthetic wheat crosses with variable parental ploidy levels

Bayesian regularized quantile regression: a robust alternative for genome-based prediction of skewed data

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Deep kernel and deep learning for genome-based prediction of single traits in multienvironment breeding trials

Deep kernel for genomic and near infrared predictions in multi-environment breeding trials

Joint use of genome, pedigree, and their interaction with environment for predicting the performance of wheat lines in new environments

Modeling genotype × environment interaction using a factor analytic model of on-farm wheat trials in the Yaqui Valley of Mexico

A review of deep learning applications for genomic selection

Target population of environments for wheat breeding in India: definition, prediction and genetic gains

Application of multi-trait Bayesian decision theory for parental genomic selection

Genomic prediction with genotype by environment interaction analysis for kernel zinc concentration in tropical maize germplasm

Additive genetic variance and covariance between relatives in synthetic wheat crosses with variable parental ploidy levels

Bayesian regularized quantile regression: a robust alternative for genome-based prediction of skewed data