Do milk spectrometry phenotypes have a role to play in dairy fertility and health programs?

Genetic selection allows for permanent improvement of dairy cow fertility and health. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10). Hence, indicators have been proven as useful in the prediction of genetic merit for direct fertility and health traits as long as they are easier to measure, heritable, and genetically correlated. Considering that changes in (fine) milk composition over the lactation reflects the physiological status of the cow, the mid-infrared (MIR) analysis of milk opens the door to a whole new range of potential indicator traits of fertility and health. Previous studies investigated the phenotypic and genetic relationships between fertility and MIR-predicted phenotypes, most of them being related to negative postpartum energy balance and body fat mobilization (e.g., fat to protein ratio, urea, fatty acids profile). Results showed that a combination of various fatty acids traits (e.g., C18:1 cis-9 and C10:0) could be used to improve fertility. Furthermore, occurrence of (sub-)clinical ketosis has been related to milk-based phenotypes such as fatty acids and ketone bodies. Hence, MIR-predicted acetone and β-hydroxybutyrate contents in milk were demonstrated as useful for breeding cows less susceptible to ketosis. Although studies investigating the genetic association among mastitis and MIR-predicted phenotypes are scarce, a wide range of traits, potentially predicted by MIR spectrometry, are worth considering. It includes traits related to the disease response of the cow (e.g., lactoferrin), to the reduced secretory activity (e.g., lactose) and to the alteration of blood-milk barrier (e.g., minerals, citrate). Moreover, direct MIR-prediction of fertility and health traits should be further considered. To conclude, MIR-predicted phenotypes have a role to play in the improvement of dairy cow fertility and health. However, further studies are warranted to (1) grasp underlying associations among MIR-predicted indicator and fitness traits, (2) estimate the genetic parameters, and (3) include these traits in broader breeding strategies.