Multivariable time series classification for clinical mastitis detection and prediction in automated milking systems

Xiu, Fan; Watters, R.D.; Nydam, D.V.; Virkler, P.D.; Wieland, Matthias; Reed, K.F.

doi:10.3168/jds.2022-22355

Cited by 6 publications

(1 citation statement)

References 66 publications

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“…The result showed that combining the DT-based ensemble models with oversampling techniques achieved relatively high sensitivity (82%) and specificity (95% for CM detection and 93% for CM prediction). Creating models using AMS data from the past seven to nine milkings (approximately 3 d) is recommended for identifying positive CM cases for farmers [75].…”

Section: Mastitis Detectionmentioning

confidence: 99%

A Review on Information Technologies Applicable to Precision Dairy Farming: Focus on Behavior, Health Monitoring, and the Precise Feeding of Dairy Cows

Liu,

Qi,

et al. 2023

Agriculture

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Milk production plays an essential role in the global economy. With the development of herds and farming systems, the collection of fine-scale data to enhance efficiency and decision-making on dairy farms still faces challenges. The behavior of animals reflects their physical state and health level. In recent years, the rapid development of the Internet of Things (IoT), artificial intelligence (AI), and computer vision (CV) has made great progress in the research of precision dairy farming. Combining data from image, sound, and movement sensors with algorithms, these methods are conducive to monitoring the behavior, health, and management practices of dairy cows. In this review, we summarize the latest research on contact sensors, vision analysis, and machine-learning technologies applicable to dairy cattle, and we focus on the individual recognition, behavior, and health monitoring of dairy cattle and precise feeding. The utilization of state-of-the-art technologies allows for monitoring behavior in near real-time conditions, detecting cow mastitis in a timely manner, and assessing body conditions and feed intake accurately, which enables the promotion of the health and management level of dairy cows. Although there are limitations in implementing machine vision algorithms in commercial settings, technologies exist today and continue to be developed in order to be hopefully used in future commercial pasture management, which ultimately results in better value for producers.

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Section: Mastitis Detectionmentioning

confidence: 99%