Using milk based biomarkers to monitor the physiological state of dairy cows in large populations

peer reviewedBased on reference data from 6 GplusE project partner farms, several equations were developed to predict milk/ blood based biomarkers from milk mid-infrared spectra (MIR). Additional existing MIR prediction equations of milk based biomarkers were included in this study. Data included predicted biomarkers for test-days between the 5th and the 49th DIM in the first 5 lactations of 57,240 Holstein cows. MIR spectra used to predict those biomarkers were collected since 2012 in 461 Belgian commercial farms enrolled in the official Walloon milk recording. Genetic parameters for each trait were estimated using single trait multi-lactation animal linear model. Additionnally bivariate models were used to investigate the genetic associations of MIR predicted milk and blood biomarkers. The lowest heritabilities estimates of 0.14, 0.15, and 0.17 were observed for milk urea, blood urea, and milk β-hydroxybutyrate (BHB) respectively. NEFA, BHB, and IGF-1 in blood have moderate heritability estimates (0.20-0.25). The highest heritabilties (0.31-0.35) concerned milk lactate dehydrogenase (LDH), milk glucose-6-phosphate, and blood glucose. Genetic correlations between lactations were relatively strong (≥0.74) for all indicators. Correlations between first- and later-lactations were the lowest (from 0.74 for blood NEFA to 0.90 for blood glucose). Highest correlations were observed between second- and later lactations (0.86 to 0.97 for milk BHB and milk LDH respectively). Urea and BHB in milk have strong genetic correlations with urea and BHB in blood (0.87 and 0.84 respectively). Additional validation of predictions equations in commercial farms and integration of reference data from other populations were needed, nevertheless first results showed value of these non-invasive biomarkers for routine monitoring and for breeding