West Central Research and Outreach Center, University of Minnesota, Morris 56267.
West Central Research and Outreach Center, University of Minnesota, Morris 56267.
J Dairy Sci. 2020 Apr;103(4):3529-3544. doi: 10.3168/jds.2019-17269. Epub 2020 Feb 20.
The objective of the study was to develop a grazing algorithm for an ear tag-based accelerometer system (Smartbow GmbH, Weibern, Austria) and to validate the grazing algorithm with data from a noseband sensor. The ear tag has an acceleration sensor, a radio chip, and temperature sensor for calibration and it can monitor rumination and detect estrus and localization. To validate the ear tag, a noseband sensor (RumiWatch, Itin and Hoch GmbH, Liestal, Switzerland) was used. The noseband sensor detects pressure and acceleration patterns, and, with a software program specific to the noseband, pressure and acceleration patterns are used to classify data into eating, ruminating, drinking, and other activities. The study was conducted at the University of Minnesota West Central Research and Outreach Center (Morris, MN) and at Teagasc Animal and Grassland Research and Innovation Centre (Moorepark, Fermoy, Co. Cork, Ireland). During May and June 2017, observational data from Minnesota and Ireland were used to develop the grazing algorithm. During September 2018, data were collected by the ear tag and noseband sensor from 12 crossbred cows in Minnesota for a total of 248 h and from 9 Holstein-Friesian cows in Ireland for a total of 248 h. A 2-sided t-test was used to compare the percentage of grazing and nongrazing time recorded by the ear tag and the noseband sensor. Pearson correlations and concordance correlation coefficients (CCC) were used to evaluate associations between the ear tag and noseband sensor. The percentage of total grazing time recorded by the ear tag and by the noseband sensor was 37.0% [95% confidence interval (CI): 32.1 to 42.0] and 40.5% (95% CI: 35.5 to 45.6), respectively, in Minnesota, and 35.4% (95% CI: 30.6 to 40.2) and 36.9% (95% CI: 32.1 to 41.8), respectively, in Ireland. The ear tag and noseband sensor agreed strongly for monitoring grazing in Minnesota (r = 0.96; 95% CI: 0.94 to 0.97, CCC = 0.95) and in Ireland (r = 0.92; 95% CI: 0.90 to 0.94, CCC = 0.92). The results suggest that there is potential for the ear tag to be used on pasture-based dairy farms to support management decision-making.
本研究的目的是为基于耳标的加速度计系统(Smartbow GmbH,Weibern,奥地利)开发一种放牧算法,并使用鼻带传感器的数据验证该放牧算法。耳标具有加速度传感器、无线电芯片和温度传感器,用于校准,并可监测反刍和检测发情和定位。为了验证耳标,使用了鼻带传感器(RumiWatch,Itin and Hoch GmbH,Liestal,瑞士)。鼻带传感器检测压力和加速度模式,并且,使用特定于鼻带的软件程序,将压力和加速度模式用于将数据分类为进食、反刍、饮水和其他活动。该研究在明尼苏达州西部研究与推广中心(Morris,MN)和 Teagasc 动物与草地研究与创新中心(Moorepark,Fermoy,Co. Cork,爱尔兰)进行。2017 年 5 月和 6 月,使用明尼苏达州和爱尔兰的观测数据开发了放牧算法。2018 年 9 月,在明尼苏达州,使用耳标和鼻带传感器从 12 头杂交奶牛收集了总计 248 小时的数据,从 9 头荷斯坦-弗里生奶牛收集了总计 248 小时的数据。使用双侧 t 检验比较了耳标和鼻带传感器记录的放牧和非放牧时间的百分比。使用 Pearson 相关系数和一致性相关系数(CCC)评估了耳标和鼻带传感器之间的关联。耳标和鼻带传感器记录的总放牧时间百分比分别为 37.0%(95%置信区间:32.1%至 42.0%)和 40.5%(95%置信区间:35.5%至 45.6%),分别在明尼苏达州和 35.4%(95%置信区间:30.6%至 40.2%)和 36.9%(95%置信区间:32.1%至 41.8%),分别在爱尔兰。耳标和鼻带传感器在明尼苏达州(r = 0.96;95%置信区间:0.94 至 0.97,CCC = 0.95)和爱尔兰(r = 0.92;95%置信区间:0.90 至 0.94,CCC = 0.92)对监测放牧具有很强的一致性。结果表明,耳标有可能在基于牧场的奶牛场中用于支持管理决策。