A multi-level hierarchic Markov process with Bayesian updating for herd optimization and simulation in dairy cattle.

Herd optimization models that determine economically optimal insemination and replacement decisions are valuable research tools to study various aspects of farming systems. The aim of this study was to develop a herd optimization and simulation model for dairy cattle. The model determines economically optimal insemination and replacement decisions for individual cows and simulates whole-herd results that follow from optimal decisions. The optimization problem was formulated as a multi-level hierarchic Markov process, and a state space model with Bayesian updating was applied to model variation in milk yield. Methodological developments were incorporated in 2 main aspects. First, we introduced an additional level to the model hierarchy to obtain a more tractable and efficient structure. Second, we included a recently developed cattle feed intake model. In addition to methodological developments, new parameters were used in the state space model and other biological functions. Results were generated for Dutch farming conditions, and outcomes were in line with actual herd performance in the Netherlands. Optimal culling decisions were sensitive to variation in milk yield but insensitive to energy requirements for maintenance and feed intake capacity. We anticipate that the model will be applied in research and extension.

Relationships between milk protein composition, milk protein variants, and cow fertility traits in Dutch Holstein-Friesian cattle.

Selective breeding can change milk protein composition to improve the manufacturing properties of milk. However, the effects of such breeding strategies on other economically important traits should be investigated before implementation. The objectives of this study were to examine the association between cow fertility traits and (1) milk protein composition and (2) milk protein variants (ß-lactoglobulin, ß-casein, κ-casein, and ß-κ-casein) in commercial Dutch Holstein-Friesian cattle. Data on 1,644 first-lactation cows were analyzed by fitting linear mixed models. Greater relative concentration of α(S1)-casein within total milk protein had a positive phenotypic relationship with nonreturn rates and calving rate after first insemination. Furthermore, results showed virtually no significant relationship between cow fertility and concentration of other milk proteins or milk protein variants. Results of this study can be used to assess the correlated effects of breeding for improved milk protein composition on reproduction, thereby allowing for better evaluation of breeding programs before implementation. Our findings suggest that selecting cows based on milk protein composition or milk protein variants for improved manufacturing properties would have no negative influence on reproductive performance.

Effects of milk fat composition, DGAT1, and SCD1 on fertility traits in Dutch Holstein cattle.

Recently, selective breeding was proposed as a means of changing the fatty acid composition of milk to improve its nutritional quality. Before implementing such breeding objectives, effects on other economically important traits should be investigated. The objectives of this study were to examine 1) the effect of milk fat composition, and 2) the effect of polymorphisms of DGAT1 and SCD1 genes on female fertility in commercial Dutch Holstein-Friesian cattle. Data on 1,745 first-lactation cows were analyzed by fitting linear mixed models. We found that higher concentrations of trans fatty acids within total milk fat negatively affected reproductive performance. Furthermore, results suggested a potential effect of the DGAT1 polymorphism on nonreturn rates for insemination 28 and 56 d after the first service. Our results can be used to assess the correlated effects of breeding for improved milk fat composition on reproduction, thereby allowing for better evaluation of breeding programs before implementation.