Predicting the Feed Intake of Cattle Based on Jaw Movement Using a Triaxial Accelerometer

作者：Luyu Ding, Yang Lv, Ruixiang Jiang, Wenjie Zhao, Qifeng Li, Baozhu Yang, Ligen Yu, Weihong Ma, Ronghua Gao, Qinyang Yu · 发表于：Agriculture · 年份：2022 · DOI：10.3390/agriculture12070899 · 被引用次数：28 · 研究领域：Animal Behavior and Welfare Studies、Effects of Environmental Stressors on Livestock、Meat and Animal Product Quality

The use of an accelerometer is considered as a promising method for the automatic measurement of the feeding behavior or feed intake of cattle, with great significance in facilitating daily management. To address further need for commercial use, an efficient classification algorithm at a low sample frequency is needed to reduce the amount of recorded data to increase the battery life of the monitoring device, and a high-precision model needs to be developed to predict feed intake on the basis of feeding behavior. Accelerograms for the jaw movement and feed intake of 13 mid-lactating cows were collected during feeding with a sampling frequency of 1 Hz at three different positions: the nasolabial levator muscle (P1), the right masseter muscle (P2), and the left lower lip muscle (P3). A behavior identification framework was developed to recognize jaw movements including ingesting, chewing and ingesting–chewing through extreme gradient boosting (XGB) integrated with the hidden Markov model solved by the Viterbi algorithm (HMM–Viterbi). Fourteen machine learning models were established and compared in order to predict feed intake rate through the accelerometer signals of recognized jaw movement activities. The developed behavior identification framework could effectively recognize different jaw movement activities with a precision of 99% at a window size of 10 s. The measured feed intake rate was 190 ± 89 g/min and could be predicted efficiently using the extra trees regressor (ET...