Developing new quantitative traits related to animal health status using a holistic Big Data Approach

Among the dairy sector's current concerns, the early detection of animal health disorders is a complex challenge as it includes different diseases. This multidimensionality explains why disease detection is often studied separately and, due to financial and ethical issues, using small-scale datasets. Several studies were conducted in the past using the milk mid-infrared (MIR) spectra, for instance, to detect mastitis, lameness or to quantify the contents of citrate, β-hydroxybutyrate (BHB) or acetone in milk. To solve this issue and the small scale data size, we considered a holistic approach using traits obtained from milk recording to detect animal health disorders: milk yield, the somatic cell count and 27 MIR predictions related to the milk composition and animal health status. From 740,054 records collected from first parity Holstein cows in the Southern part of Belgium, we performed repeated unsupervised learnings. The obtained clustering divided the records into five groups. Significant differences of feature means were found between groups, suggesting that one group was related to mastitis and a second group to metabolic disorders. A validation from 87 milk and blood reference records obtained through the Interreg European project GplusE confirmed this interpretation. Moreover, after using a principal components analysis performed on the used features, it appeared that the first and fourth principal components (PC) were strongly related to the two discovered groups of sick animals. From reference values, the first PC had correlations of -0.68 with blood BHB, -0.70 with blood Non-Esterified Fatty Acids, 0.61 with blood Glucose and -0.46 with milk isocitrate. On the other hand, the fourth PC had correlations of 0.51 with milk N-acetyl-β-D-glucosaminidase and 0.55 with milk lactate dehydrogenase. Those results suggest that the obtained PCs reflect directly main health disorders and could be used to monitor dairy farms on large scale data.HappyMo