The current cattle selection program for dairy cattle in the Walloon region of Belgium does not consider the relative content of the different fatty acids (FA) in milk. However, interest by the local dairy industry in differentiated milk products is increasing. Therefore, farmers may be interested in selecting their animals based on the fat composition. The aim of this study was to evaluate the feasibility of genetic selection to improve the nutritional quality of bovine milk fat. The heritabilities and correlations among milk yield, fat, protein, and major FA contents in milk were estimated. Heritabilities for FA in milk and fat ranged from 5 to 38%. The genetic correlations estimated among FA reflected the common origin of several groups of FA. Given these results, an index including FA contents with the similar metabolic process of production in the mammary gland could be used, for example, to increase the monounsaturated and conjugated fatty acids in milk. Moreover, the genetic correlations between the percentage of fat and the content of C14:0, C12:0, C16:0, and C18:0 in fat were −0.06, 0.55, 0.60, and 0.84, respectively. This result demonstrates that an increase in fat content is not directly correlated with undesirable changes in FA profile in milk for human health. Based on the obtained genetic parameters, a future selection program to improve the FA composition of milk fat could be initiated.

The aim of this research was to study the potential for selection of cows with a higher nutritional quality of milk fat by studying the differences in fatty acid profiles within and across the following breeds: Dual Purpose Belgian Blue, Holstein-Friesian, Jersey, Montbeliarde, and non-Holstein Meuse-Rhine-Yssel type Red and White. Six hundred milk samples from 275 animals were taken from 7 herds. Several types of fatty acids in milk and milk fat were quantified using midinfrared spectrometry and previously obtained calibration equations. Statistical analyses were made using a mixed linear model with a random animal effect. The variance components were estimated by using REML. Results showed breed differences for the fatty acid profile. The repeatability estimate obtained in the present study may suggest the existence of moderate additive genetic variance for the fatty acid profile within each breed. Results also indicated variation for each analyzed milk component in the whole cow population studied. Genetic improvement of the nutritional quality of milk fat based on fatty acid profiles might be possible, and further research and development are warranted.

The objective of this research was to examine the effects of inbreeding in the population of Holstein cattle in the Walloon region of Belgium. The effects of inbreeding on the global economic index and its components were studied by using data from the genetic evaluations of February 2004 for production, somatic cell score (SCS), computed from somatic cell counts and type. Inbreeding coefficients for 956,516 animals were computed using a method that allows assigning an inbreeding coefficient to individuals without known parents. These coefficients were equal to the mean inbreeding coefficient of contemporary individuals with known parents. The significance of inbreeding effects on the different evaluated traits and on the different indexes were tested using a t-test comparing estimated standard errors and effects. The inbreeding effect was significantly different from zero for the vast majority of evaluated traits and for all of the indexes. Inbreeding had the greatest deleterious effects on production traits. Inbreeding decreased yield of milk, fat, and protein during a lactation by 19.68, 0.96, and 0.69 kg, respectively, per each 1% increase in inbreeding. The regression coefficient of SCS per 1% increase in inbreeding was +0.005 SCS units. The inbreeding depression was thus relatively low for SCS, but inbred animals had higher SCS than non-inbred animals, indicating that inbred animals would be slightly more sensitive to mastitis than non-inbred animals. Estimates of inbreeding effects on evaluated type traits per 1% increase were small. The most strongly affected type traits were chest width, rear leg, and overall development on a standardized scale. For several type traits, particularly traits linked to the udder, the estimates suggested a favorable effect of inbreeding. The global economic index was depressed by around 6.13 € of lifetime profit per 1% increase in inbreeding for the Holstein animals in the Walloon region of Belgium.

The challenge of managing and breeding dairy cows is permanently adapting to changing production circumstances under socio-economic constraints. If managing and breeding address different timeframes of action, both need relevant phenotypes that allow for precise monitoring of the status of the cows, and their health, behavior, and well-being as well as their environmental impact and the quality of their products (i.e., milk and subsequently dairy products). Milk composition has been identified as an important source of information because it could reflect, at least partially, all these elements. Major conventional milk components such as fat, protein, urea, and lactose contents are routinely predicted by mid-infrared (MIR) spectrometry and have been widely used for these purposes. But, milk composition is much more complex and other nonconventional milk components, potentially predicted by MIR, might be informative. Such new milk-based phenotypes should be considered given that they are cheap, rapidly obtained, usable on a large scale, robust, and reliable. In a first approach, new phenotypes can be predicted from MIR spectra using techniques based on classical prediction equations. This method was used successfully for many novel traits (e.g., fatty acids, lactoferrin, minerals, milk technological properties, citrate) that can be then useful for management and breeding purposes. An innovation was to consider the longitudinal nature of the relationship between the trait of interest and the MIR spectra (e.g., to predict methane from MIR). By avoiding intermediate steps, prediction errors can be minimized when traits of interest (e.g., methane, energy balance, ketosis) are predicted directly from MIR spectra. In a second approach, research is ongoing to detect and exploit patterns in an innovative manner, by comparing observed with expected MIR spectra directly (e.g., pregnancy). All of these traits can then be used to define best practices, adjust feeding and health management, improve animal welfare, improve milk quality, and mitigate environmental impact. Under the condition that MIR data are available on a large scale, phenotypes for these traits will allow genetic and genomic evaluations. Introduction of novel traits into the breeding objectives will need additional research to clarify socio-economic weights and genetic correlations with other traits of interest.