The skin-deep beauty of dairy cows : Investigation of metabolic disorders by using morphological traits quantified with 3-Dimensional vision

Song, Xiangyu


Dairy farmers aim to produce high-quality products and meanwhile to ensure the health of their cows. To remain healthy, dairy cows need to eat well. If cows cannot have sufficient food and nutrients to support their daily lives, they could become sick and start changing their physical appearances, such as getting thinner. It is important for farmers to find sick cows as early as possible to offer timely treatment and to prevent further loss. Finding all the sick cows on farms manually based on their physical appearances , however, can cost farmers a great deal of time or money. With the goal of helping farmers, this dissertation has developed an automated system to monitor dairy cows’ physical appearance changes in the whole body and the rumen by using 3D cameras. The automated measurements were compared with expert assessments, and the differences were neglectable. Moreover, the 3D vision system has been applied on a commercial farm to regularly monitor individual cows for a period, where their feeding was changed from silage to fresh grass. Cows responded quickly to this feeding change, and these responses were successfully captured by the 3D vision system. This 3D vision system is automated, non-invasive, and animal-friendly and, hence, it has great potential to be widely used on commercial farms. The automatically measured physical appearances are not only the ‘skin-deep’ beauty of dairy cows but also essential indicators to help farmers in their daily health and feeding management to reach a high-quality production.