您好，欢迎访问江西省农业科学院 机构知识库！

Recognition of Cattle's Feeding Behaviors Using Noseband Pressure Sensor With Machine Learning

文献类型： 外文期刊

作者： Chen, Guipeng 1 ; Li, Cong 1 ; Guo, Yang 1 ; Shu, Hang 2 ; Cao, Zhen 3 ; Xu, Beibei 4 ;

作者机构： 1.Jiangxi Acad Agr Sci, Agr Econ & Informat Inst, Nanchang, Peoples R China

2.Univ Liege, Precis Livestock & Nutr Unit, AgroBioChem, Gembloux Agrobio Tech, Gembloux, Belgium

3.Wageningen Univ & Res, Informat Technol Grp, Wageningen, Netherlands

4.Chinese Acad Agr Sci, Agr Informat Inst, Beijing, Peoples R China

关键词： noseband pressure sensor; machine learning; XGB; behavior classification; feeding behaviors

期刊名称：FRONTIERS IN VETERINARY SCIENCE （ 影响因子：3.471； 五年影响因子：3.821 ）

ISSN：

年卷期： 2022 年 9 卷

页码：

收录情况： SCI

摘要： Automatic monitoring of feeding behavior especially rumination and eating in cattle is important to keep track of animal health and growth condition and disease warnings. The noseband pressure sensor is not only able to accurately sense the pressure change of the cattle's jaw movements, which can directly reflect the cattle's chewing behavior, but also has strong resistance to interference. However, it is difficult to keep the same initial pressure while wearing the pressure sensor, and this will pose a challenge to process the feeding behavior data. This article proposed a machine learning approach aiming at eliminating the influence of initial pressure on the identification of rumination and eating behaviors. The method mainly used the local slope to obtain the local data variation and combined Fast Fourier Transform (FFT) to extract the frequency-domain features. Extreme Gradient Boosting Algorithm (XGB) was performed to classify the features of rumination and eating behaviors. Experimental results showed that the local slope in combination with frequency-domain features achieved an F1 score of 0.96, and recognition accuracy of 0.966 in both rumination and eating behaviors. Combined with the commonly used data processing algorithms and time-domain feature extraction method, the proposed approach improved the behavior recognition accuracy. This work will contribute to the standardized application and promotion of the noseband pressure sensors.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：江西省农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台