Laurindo Geovani Marques, Ferraz Gabriel Araújo E Silva, Damasceno Flavio Alves, Nascimento Joao Antônio Costa do, Santos Gabriel Henrique Ribeiro Dos, Ferraz Patrícia Ferreira Ponciano
Agricultural Engineering Department, School of Engineering, Federal University of Lavras, Lavras 37200-000, MG, Brazil.
Engineering Department, School of Engineering, Federal University of Lavras, Lavras 37200-000, MG, Brazil.
Animals (Basel). 2022 Aug 28;12(17):2214. doi: 10.3390/ani12172214.
The compost barn system has become popular in recent years for providing greater animal well-being and quality of life, favoring productivity and longevity. With the increase in the use of compost barn in dairy farms, studies related to the thermal environment and behavior are of paramount importance to assess the well-being of animals and improve management, if necessary. This work aimed to characterize the thermal environment inside a compost barn during the four seasons of a year and to evaluate the standing and lying behavior of the cows through images. The experiment was carried out during March (summer), June (autumn), August (winter), and November (spring). Dry bulb temperature (, °C), dew point temperature (, °C), and relative humidity (RH,%) data were collected every 10 minutes during all analyzed days, and the temperature and humidity index (THI) was subsequently calculated. In order to analyze the behavior of the cows, filming of the barn interior was carried out during the evaluated days. Subsequently, these films were analyzed visually, and in an automated way to evaluate the behavior of these animals. For the automated analysis, an algorithm was developed using artificial intelligence tools, YOLOv3, so that the evaluation process could be automated and fast. It was observed that during the experimental period, the highest mean values of THI were observed during the afternoon and the autumn. The animals' preference to lie down on the bed for most of the day was verified. It was observed that the algorithm was able to detect cow behavior (lying down or standing). It can be concluded that the behavior of the cows was defined, and the artificial intelligence was successfully applied and can be recommended for such use.
近年来,堆肥舍系统因能提升动物福祉和生活质量、有利于提高生产力和延长寿命而受到欢迎。随着奶牛场堆肥舍使用量的增加,与热环境和行为相关的研究对于评估动物福祉以及在必要时改进管理至关重要。这项工作旨在描述一年四个季节中堆肥舍内的热环境,并通过图像评估奶牛的站立和躺卧行为。实验在3月(夏季)、6月(秋季)、8月(冬季)和11月(春季)进行。在所有分析日期间,每隔10分钟收集一次干球温度(,℃)、露点温度(,℃)和相对湿度(RH,%)数据,随后计算温度湿度指数(THI)。为了分析奶牛的行为,在评估日期间对牛舍内部进行了拍摄。随后,对这些影片进行了目视分析,并以自动化方式评估这些动物的行为。对于自动化分析,使用人工智能工具YOLOv3开发了一种算法,以便评估过程能够自动化且快速。观察到在实验期间,下午和秋季的THI平均值最高。证实了动物在一天中的大部分时间里更喜欢躺在床上。观察到该算法能够检测奶牛的行为(躺下或站立)。可以得出结论,奶牛的行为已明确,人工智能得到了成功应用,可推荐用于此类用途。