Abstract
Animals with high production potential and simultaneously high resilience to environmental challenges are vital for sustainable livestock production. A simulation study was carried out to: (1) evaluate the influence of genomic data, statistical models, and phenotyping strategies on prediction accuracies for resilience and production potential; and (2) assess the impact of different selection strategies on genetic improvement in these traits. Prediction accuracies were found to be compromised when families were clustered in similar environments or when the environmental challenge level was unknown. Selection on individuals’ performance alone could simultaneously improve resilience if performance records of individuals were obtained across a wide range of environments, whereas a narrow range may decrease resilience. Simultaneous genetic improvement in resilience and production potential strongly benefits from the use of genomic evaluations, reaction norm models, and phenotyping in a wide range of environments.
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