Genomic selection models aim at predicting the performance of individuals with the use of genomic markers. In animal breeding, prediction models are seldomly tested for their ability to predict new individuals’ performance under different environmental conditions, despite the changes in management and diet that the industry undergoes. In this study, we propose a method to use milk infrared spectra as descriptors of environmental variation among herds. These descriptors can be incorporated in genomic prediction models similarly to how genomic markers are included. The inclusion of environmental descriptors is shown to improve the predictive ability for new genotypes under new environmental conditions.
Use of Milk Infrared Spectral Data as Environmental Covariates in Genomic Prediction Models for Production Traits in Canadian Holstein / Francesco Tiezzi, Allison Fleming, Francesca Malchiodi. - In: ANIMALS. - ISSN 2076-2615. - ELETTRONICO. - (2022), pp. 1-16. [10.3390/ani12091189]
Use of Milk Infrared Spectral Data as Environmental Covariates in Genomic Prediction Models for Production Traits in Canadian Holstein
Francesco Tiezzi
Conceptualization
;
2022
Abstract
Genomic selection models aim at predicting the performance of individuals with the use of genomic markers. In animal breeding, prediction models are seldomly tested for their ability to predict new individuals’ performance under different environmental conditions, despite the changes in management and diet that the industry undergoes. In this study, we propose a method to use milk infrared spectra as descriptors of environmental variation among herds. These descriptors can be incorporated in genomic prediction models similarly to how genomic markers are included. The inclusion of environmental descriptors is shown to improve the predictive ability for new genotypes under new environmental conditions.File | Dimensione | Formato | |
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