谷仓
热应力
奶牛
环境科学
贝叶斯多元线性回归
乳品工业
计算机科学
多元统计
多项式回归
回归分析
动物科学
统计
数学
工程类
生物
土木工程
食品科学
作者
Hanwook Chung,Hien Vu,Younghyun Kim,Christopher Y. Choi
标识
DOI:10.1016/j.biosystemseng.2023.10.001
摘要
Heat stress remains one of the greatest threats to the economic viability of the dairy industry. The threat becomes even greater during warm and humid conditions, especially for those larger farms seeking to expand their operations. This study sought to develop and test a reliable and timely method that allows dairy farmers to monitor the body temperatures of their animals, using a compact, lightweight ear tag device, including a wirelessly rechargeable battery. The device is also capable of wirelessly transmitting a cow's subcutaneous temperature in real-time by means of an injectable, passive RFID biosensor. The outcomes showed that subcutaneous ear-base temperature (EBT) can synchronously follow the core body temperature (CBT) while also producing a comparable temperature gradient. That is, on average, the difference between a CBT and an EBT is 0.68 ± 0.35 °C. Based on regression models, the CBT of a cow can be accurately predicted based on EBT, with an average error of around 0.20 °C and as low as 0.11 °C by using a multivariate polynomial regression model, which includes external environmental conditions as well as the cow's health information, including milk production. The outcomes indicate that there is a consistent, predictable time lag between increases in microenvironmental conditions and increases in a cow's body temperature. These findings should enable dairy barn designers to develop and employ automated control-loop systems that utilise physiological feedback to improve management practices aimed at detecting heat stress and mitigating its effects in a timely manner, while minimising energy use.
科研通智能强力驱动
Strongly Powered by AbleSci AI