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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.