Automated measurement of cattle surface temperature and its correlation with rectal temperature.
Automated measurement of cattle surface temperature and its correlation with rectal temperature.
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牛体表温度的自动测量及其与直肠温度的相关性
DOI：
10.1371/journal.pone.0175377
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Wang D
中科院分区：
文献类型：
--
作者：
Kou H;Zhao Y;Ren K;Chen X;Lu Y;Wang D
牛的体温随着繁殖周期和疾病状态而有规律地变化。建立一种自动监测体温的方法可能有助于更好地管理牛的繁殖和疾病控制。本课题研制了一套牛体表温度自动测量系统（AMSCST），通过安装一个适合牛后腿解剖结构的特殊外壳，实现了对跖骨温度的测量。用AMSCST连续测量了三个季节、一天24小时、间隔1小时的后肢跖骨表面温度。分别以AMSCST和水银温度计检测的ST和直肠温度（RT）为基础，以时间点和季节因素为固定效应，建立线性混合模型。一元线性相关和Bland-Altman分析结果表明，AMSCST法测得的温度与水银温度计测得的温度相关性很好（R2 = 0.998），表明AMSCST法是一种准确可靠的牛体温检测方法。统计学分析表明，三个季节之间、不同时间点之间的ST差异有显著性（P<0.05），不同时间点之间的RT差异也有显著性（P<0.05）。混合模型的预测精度通过10折交叉验证进行了验证。实测RT与预测RT之间的平均差值为0.10 ± 0.10°C，相关系数为0.644，表明该模型用于牛体温测量的可行性。因此，通过发明最佳装置和建立AMSCST系统，实现了精确测量牛体温的自动化技术。
The body temperature of cattle varies regularly with both the reproductive cycle and disease status. Establishing an automatic method for monitoring body temperature may facilitate better management of reproduction and disease control in cattle. Here, we developed an Automatic Measurement System for Cattle’s Surface Temperature (AMSCST) to measure the temperature of metatarsus by attaching a special shell designed to fit the anatomy of cattle’s hind leg. Using AMSCST, the surface temperature (ST) on the metatarsus of the hind leg was successively measured during 24 hours a day with an interval of one hour in three tested seasons. Based on ST and rectal temperature (RT) detected by AMSCST and mercury thermometer, respectively, a linear mixed model was established, regarding both the time point and seasonal factors as the fixed effects. Unary linear correlation and Bland-Altman analysis results indicated that the temperatures measured by AMSCST were closely correlated to those measured by mercury thermometer (R2 = 0.998), suggesting that the AMSCST is an accurate and reliable way to detect cattle’s body temperature. Statistical analysis showed that the differences of STs among the three seasons, or among the different time points were significant (P<0.05), and the differences of RTs among the different time points were similarly significant (P<0.05). The prediction accuracy of the mixed model was verified by 10-fold cross validation. The average difference between measured RT and predicted RT was about 0.10 ± 0.10°C with the association coefficient of 0.644, indicating the feasibility of this model in measuring cattle body temperature. Therefore, an automated technology for accurately measuring cattle body temperature was accomplished by inventing an optimal device and establishing the AMSCST system.