Department of Animal Production, School of Agricultural and Forestry Engineering, University of Cordoba, Campus de Rabanales, Madrid-Cadiz Rd. km 396, 14071 Cordoba, Spain.
Department of Animal Production, School of Agricultural and Forestry Engineering, University of Cordoba, Campus de Rabanales, Madrid-Cadiz Rd. km 396, 14071 Cordoba, Spain.
Animal. 2023 Aug;17(8):100901. doi: 10.1016/j.animal.2023.100901. Epub 2023 Jun 28.
Dystocia is one of the main causes of calf death around calving. In addition, peripartum deaths may occur due to other factors, such as weather or predators, especially in the case of grazing animals. Precision Livestock Farming (PLF) tools aimed at the automatic detection of calving may be useful for farmers, allowing cow assistance in case of dystocia or checking the condition of the cow-calf pair after calving. Such PLF systems are commercially available for dairy cows, but these tools are not suitable for rangelands, mainly due to power and connectivity constraints. Thus, since most commercial PLF tools for rangelands are based on Global Navigate Satellite System (GNSS) technology, the objective of this study was to design and evaluate several indicators built from data gathered with GNSS collars to characterise their potential for the detection of calving on rangelands. Location data from 57 cows, 42 of which calved during the study, were curated and analysed following a standardised procedure. Several indicators were calculated using two different strategies. The first approach consisted of having indicators that could be computed using the data of a single GNSS collar (cow indicators). The second strategy involved the use of data from several animals (herd indicators), which requires more animals to be monitored, but may allow the characterisation of social behaviour. Several indicators, such as the length of the daily trajectory or the sinuosity of cow path, showed significant differences between the pre- and postpartum periods, but no clear differences between calving day and previous days. Herd indicators, such as the distance to herd centroid or to the nearest peer were superior in terms of the detection of calving day, as cows showed isolation behaviour from 24 hours before calving. Relative indicators, i.e., the value of cow or herd indicators for the calving cow in relation to the average value of the same indicators for its herdmates, provided additional information on cow behaviour. For instance, according to the relative indicator for the change in daily trajectory, pregnant cows had a differential exploratory behaviour up to 14 days before calving. In conclusion, data from commercial GNSS collars proved to be useful for the computation of several indicators related to the occurrence of calving on rangelands. Some of those indicators showed changes from baseline values on the day before calving, which could serve to predict the onset of parturition.
难产是围产期犊牛死亡的主要原因之一。此外，由于天气或捕食者等其他因素，围产期也可能发生死亡，特别是对于放牧动物。旨在自动检测分娩的精准畜牧养殖 (PLF) 工具可能对农民有用，以便在发生难产时协助奶牛，或在分娩后检查奶牛-犊牛对的状况。这些 PLF 系统在奶牛场已经商业化，但这些工具不适用于牧场，主要是由于电力和连接性的限制。因此，由于大多数用于牧场的商业 PLF 工具都是基于全球导航卫星系统 (GNSS) 技术，因此本研究的目的是设计和评估几种从 GNSS 项圈收集的数据中构建的指标，以评估它们在牧场检测分娩的潜力。对 57 头奶牛的数据进行了整理和分析，其中 42 头在研究期间分娩。按照标准化程序对数据进行了分析。使用两种不同的策略计算了几种指标。第一种方法是使用单个 GNSS 项圈的数据计算指标（奶牛指标）。第二种策略是使用多只动物的数据（畜群指标），这需要更多的动物进行监测，但可以描述社会行为。一些指标，如每日轨迹的长度或牛路径的弯曲度，在产前和产后期间有显著差异，但在产犊日和前几天之间没有明显差异。畜群指标，如与畜群质心或最近同伴的距离，在检测产犊日方面表现更优，因为奶牛在产犊前 24 小时表现出孤立行为。相对指标，即牛或畜群指标对于产犊牛的值与同群牛的相同指标的平均值之比，提供了有关牛行为的额外信息。例如，根据每日轨迹变化的相对指标，怀孕奶牛在产犊前 14 天表现出不同的探索行为。总之，来自商业 GNSS 项圈的数据证明可用于计算与牧场分娩相关的几种指标。其中一些指标在产犊前一天从基线值发生变化，这可以用来预测分娩的开始。
