Development of a commercial herd management tool based on milk FA profile of individual dairy cows by FTIR spectroscopy

In dairy cattle, the transition period has long been recognized as the most critical physiological stage. Along with hormonal changes, the higher demand of energy and nutrients for the synthesis of colostrum and milk coupled with decreased feed intake force the transition cows to undergo negative energy balance (NEB). The NEB at the onset of lactation has been associated with poor productive and reproductive performance as well as immune dysfunction.

For a few years now, new chemometric models for Fourier Transorm Infrared (FTIR) milk analysis have allowed the prediction of B-hydroxybutyrate (BHB), and more recently, the potential of this technology to predict milk fatty acid (FA) profile has been evaluated. Although gas chromatography (GC) is a very precise and reliable technique for determination of milk FA composition, FTIR is a promising alternative as it offers the opportunity to determine with enough precision some groups of milk FA related to the energy metabolism of the animal. When compared to GC, these tests are fast, cost-effective and could become an interesting management tool easily implemented in practice. However, up to this date, correlations between milk FA composition determined by FTIR and performance of early-lactation cows have not been established.

The objective of the current project is to describe the relationships between milk FA, milk BHB, plasma non-esterified fatty acids (NEFA), productive and reproductive performance of dairy cows, along with their health status. These relationships will be used to develop a new herd management tool for dairy farmers. First, a Danish database (DB) including milk FA profile and productive performance of over 2.5M dairy cows will be used to establish correlations between these variables and to validate the potential of milk FA composition to complement the existing tools available to dairy farmers. In the meantime, predictive FA models will be created and installed on Valacta’s mid-FTIR analyzers, and milk FA composition of individual cows from dairy herds in Quebec will be incorporated in the existing DB which gathers individual records of productive and reproductive performance and health status of dairy cows. Observed correlations will be compared to published literature to explain the possible links between data. Relationships established from the Danish DB will be validated with the Quebec DB. Also, 3000 blood and milk samples will be collected from early lactation cows housed in Quebec commercial dairy farms in order to develop a model to predict the level of NEFA in cow's blood, another biomarker of NEB in dairy cows, based on FTIR milk spectra of individual animals. Finally, a reference method of milk FA determination using fast-GC technology will be created. This method will be as precise as the traditional GC methods, but 10 times faster, which will allow regular calibration and validation of mid-FTIR analyzers locally, at Valacta, for a fraction of the actual cost.