| Abstract |
For several decades, in many countries, the focus of dairy industry has been on maximizing milk yield, leading to the deterioration of most functional traits. The high producing dairy cows may be affected by mastitis, lameness, cystic ovarian disease, displaced abomasum, ketosis, metritis, milk fever and retained placenta. The new approach to solve these diseases is to detect them at earliest stage, utilizing predictive milk biomarkers. The aim of this study was to discover potential biomarkers in milk to evaluate health status of mammary gland. This work is organized within the FP7 EU funded project GplusE. A total of 241 dairy cows from 6 experimental herds in Denmark, Ireland, United Kingdom, Italy, Belgium and Germany are involved. Milk samples were collected at 7, 14 and 21 days post partum. Lactose, fat, protein content, SCC, ?-hydroxybutyrate, isocitrate, urea, uric acid, glucose, glucose-6-phosphate, lactate dehydrogenase (LHD) and N-acetyl-?-d-glucosaminidase (NAGase) were determined. Furthermore, individual milk MIR spectra were collected at the same DIM, and prediction equations were used to predict mineral and fatty acid contents. Cows were assigned to three groups on the basis of milk SCC values (cells/mL): LOW (? 100,000) in at least two out of the three milk sampling, INTERMEDIATE (101?SCC?400), HIGH (? 401,00). Mammary gland status was monitored during trial period by veterinarian control. Milk parameters were analysed by PROC GLM model in SAS to determinate and compare mean among different lactation day and between the three groups. A canonical discriminant analysis was performed by CANDISC procedure in SAS to obtain new variables that distinguish three health status. Mineral and lactose contents, NAGase, and LDH activity, some fatty acid contents were significantly different between 7vs14vs21 days post partum and in HIGH vs LOW cows. Two new canonical functions that group some of milk parameters (Fat, Na, K, C:16, C18:2, SFA, MCFA, ?6) distinguished LOW vs INTERMEDIATE vs HIGH cows. The sample sizes may constraint, but the identified milk biomarkers will be tested and validated in thousands of cows within the GplusE project. These new milk biomarkers could be use by farmers for an early detection of diseases. |
| Authors |
Marchitelli, C., Signorelli, F., Napolitano, F., Grelet, C., Gengler, N., Dehareng, F., Soyeurt, H., Ingvartsen, K.L., Sørensen, M., Crowe, M., Gpluse Consortium, |
