Jorquera-Chavez Maria, Fuentes Sigfredo, Dunshea Frank R, Warner Robyn D, Poblete Tomas, Morrison Rebecca S, Jongman Ellen C
Faculty of Veterinary and Agricultural Sciences, University of Melbourne, VIC 3010, Australia.
Research and Innovation, Rivalea (Australia) Pty. Ltd., Corowa, NSW 2646, Australia.
Animals (Basel). 2020 Mar 9;10(3):451. doi: 10.3390/ani10030451.
Respiratory diseases are a major problem in the pig industry worldwide. Due to the impact of these diseases, the early identification of infected herds is essential. Computer vision technology, using RGB (red, green and blue) and thermal infrared imagery, can assist the early detection of changes in animal physiology related to these and other diseases. This pilot study aimed to identify whether these techniques are a useful tool to detect early changes of eye and ear-base temperature, heart rate and respiration rate in pigs that were challenged with Clinical observations and imagery were analysed, comparing data obtained from animals that showed some signs of illness with data from animals that showed no signs of ill health. Highly significant differences ( < 0.05) were observed between sick and healthy pigs in heart rate, eye and ear temperature, with higher heart rate and higher temperatures in sick pigs. The largest change in temperature and heart rate remotely measured was observed around 4-6 h before signs of clinical illness were observed by the skilled technicians. These data suggest that computer vision techniques could be a useful tool to detect indicators of disease before the symptoms can be observed by stock people, assisting the early detection and control of respiratory diseases in pigs, promoting further research to study the capability and possible uses of this technology for on farm monitoring and management.
呼吸系统疾病是全球养猪业的一个主要问题。由于这些疾病的影响,早期识别受感染猪群至关重要。利用RGB(红、绿、蓝)和热红外图像的计算机视觉技术,可以辅助早期检测与这些及其他疾病相关的动物生理变化。这项初步研究旨在确定这些技术是否是检测受 挑战猪的眼和耳根温度、心率及呼吸率早期变化的有用工具。对临床观察和图像进行了分析,将显示出一些疾病迹象的动物所获得的数据与未显示健康问题迹象的动物的数据进行比较。在患病猪和健康猪之间观察到心率、眼温和耳根温度存在极显著差异(<0.05),患病猪的心率和温度更高。在熟练技术人员观察到临床疾病迹象前约4 - 6小时,观察到远程测量的温度和心率变化最大。这些数据表明,计算机视觉技术可能是一种有用工具,可在饲养人员观察到症状之前检测疾病指标,有助于早期检测和控制猪的呼吸系统疾病,推动进一步研究以探讨该技术在农场监测和管理中的能力及可能用途。