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Abstract

The objective of the study was to assess the farm level economic implications of value-adding genetic selection strategies to improve milk fat composition. Selection based on a quantitative trait (ratio of total saturated to total unsaturated fatty acids in milk) or a known genotype (for the DGAT1 gene) was considered. Technical and economic performance of hypothetical herds were computed by a herd optimization and simulation model. It was assumed that the herds are already bred for the specific milk composition, and the transition period was not considered. Correlated effects of the selection scenarios on milk production, female fertility, and functional longevity traits were accounted for. Results showed that increasing the total unsaturated fatty acids in milk by traditional selection leads to lower net revenue, whereas selection based on DGAT1 genotype results in slightly higher net revenue. Our results, therefore, suggest that genetic selection based on DGAT1 genotype is a more profitable strategy for dairy farmers than selection based on phenotypes for SFA/UFA ratio.

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