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Survey and future prospects in precision dairy farming

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  10th International Livestock Environment Symposium (ILES X)  .(doi:10.13031/iles.18-053)
Authors:   Hugo FM Milan, Kristen M Perano, Kifle G Gebremedhin
Keywords:   Dairy cows, precision livestock farming, machine learning, computer vision.

Abstract. Precision dairy farming is a growing field that uses modern technology to monitor animals individually, with the potential for better animal health, comfort, and production. This paper discusses (1) the intrinsic variability of the physiological responses of animals (which motivates monitoring cows individually), (2) what variables should be monitored for precision dairy farming and why, and (3) how to monitor these variables. For example, through monitoring individual cows' responses to heat stress, cows that are more susceptible to the negative effects of heat stress could be identified and subsequently managed in barns with higher cooling capacities while cows that are more tolerant to heat stress could be managed in barns with less cooling capacities. Cows are complex biological systems that consume feed and water, self-regulating under the given environmental conditions, and produce outputs and indicators for animal comfort (e.g., milk, core body temperature, and behavior). By monitoring the input and outputs, it is possible to infer the health, comfort, and production status of cows. Recent technologies to monitor animals are based on machine learning and computer vision algorithms. A brief introduction to these algorithms is given in this paper followed by a discussion on how these techniques and novel technologies could be used to monitor internal-core and surface temperatures, respiration rate, sweating rate, walking pattern, behavior, physical dimensions, weight, and body-condition score of dairy cattle. The paper also discusses future needs and concerns for advancement of precision dairy farming such as data management, processing, and sharing.

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