OUTLINE OF AN OBSERVATIONAL STUDY ON UDDER HEALTH AND MILK QUALITY IN FLANDERS, BELGIUM

In Flanders, a shift of the distribution of mastitis pathogens towards coagulase-negative staphylococci (CNS) and coliforms in dairy cattle has been observed in recent years. This may partially explain the recent problems of increasing bulk milk somatic cell counts, decreasing milk quality or both. To clarify the complex relationships between different factors explaining the mastitis status of cows and quarters and their evolutions in time, the following protocol and research tools were developed and optimized. Ten randomly selected dairy cows of six Flemish dairy herds (n=60) are monitored during one year. For comparison, three farms with and three without former specific coliform problems are included in the study. On this farms udder health is observed and potential environmental or animal related risk factors are monthly assessed at three different levels (farm, cow and quarter). Teat swabs, quarter milk samples and barn samples (air, floor, bedding materials, feces) are cultured for presence of mastitis bacteria. Molecular identification and typing techniques are used to detect CNS strains and to identify the main sources of CNS infections. At farm level the milking process is monitored by on the one hand, a monthly technical review of the milking machine and on the other hand, by a video controlled milking routine registration. Information on additional management factors is registered using a questionnaire. Additionally climatic variations (temperature, humidity, gas concentrations, dust) in the barn are investigated with innovative instruments. At cow level, zootechnical information (age, parity, oestrus, pregnancy, production) is complemented with records of cleanliness, body condition, gait and milking characteristics. At the quarter level, the conformation, teat apex condition and cleanliness of the teats are observed with an image processing program developed in Halcon (Halcon 8.0, MVTec Software GmbH, München, Germany). All of the presented measurement methods have been developed and optimised for routine detection and have been proven to be robust enough for monthly monitoring