Department of Animal Science, Texas A&M University, College Station, TX 77843-2471, USA.
Department of Large Animal Clinical Sciences, Texas A&M University, College Station, TX 77843-2471, USA.
J Anim Sci. 2021 Sep 1;99(9). doi: 10.1093/jas/skab232.
The objective of this experiment was to determine if statistical process control (SPC) procedures coupled with remote continuous data collection could accurately differentiate between animals experimentally inoculated with a viral-bacterial (VB) challenge or phosphate buffer solution (PBS). Crossbred heifers (N = 38; BW = 230 ± 16.4 kg) were randomly assigned to treatments by initial weight, average daily gain (ADG), bovine herpes virus 1, and Mannheimia haemolytica serum titers. Feeding behavior, dry matter intake (DMI), animal activity, and rumen temperature were continuously monitored remotely prior to and following VB challenge. VB-challenged heifers exhibited decreased (P < 0.01) ADG and DMI, as well as increased (P < 0.01) neutrophils and rumen temperature consistent with a bovine respiratory disease (BRD) infection. However, none of the heifers displayed overt clinical signs of disease. Shewhart and cumulative summation (CUSUM) charts were evaluated, with sensitivity and specificity computed on the VB-challenged heifers (n = 19) and PBS-challenged heifers (n = 19), respectively, and the accuracy was determined as the average of sensitivity and specificity. To address the diurnal nature of rumen temperature responses, summary statistics (mean, minimum, and maximum) were computed for daily quartiles (6-h intervals), and these quartile temperature models were evaluated separately. In the Shewhart analysis, DMI was the most accurate (95%) at deciphering between PBS- and VB-challenged heifers, followed by rumen temperature (94%) collected in the 2nd and 3rd quartiles. Rest was most the accurate accelerometer-based traits (89%), and meal duration (87%) and bunk visit (BV) frequency (82%) were the most accurate feeding behavior traits. Rumen temperature collected in the 3rd quartile signaled the earliest (2.5 d) of all the variables monitored with the Shewhart, followed by BV frequency (2.8 d), meal duration (2.8 d), DMI (3.0 d), and rest (4.0 d). Rumen temperature and DMI remained the most accurate variables in the CUSUM at 80% and 79%, respectively. Meal duration (58%), BV frequency (71%), and rest (74%) were less accurate when monitored with the CUSUM analysis. Furthermore, signal day was greater for DMI, rumen temperature, and meal duration (4.4, 5.0, and 3.7 d, respectively) in the CUSUM compared to Shewhart analysis. These results indicate that Shewhart and CUSUM charts can effectively identify deviations in feeding behavior, activity, and rumen temperature patterns for the purpose of detecting sub-clinical BRD in beef cattle.
本实验的目的是确定统计过程控制（SPC）程序与远程连续数据采集相结合是否可以准确区分接种病毒-细菌（VB）挑战或磷酸盐缓冲溶液（PBS）的实验动物。杂交奶牛（N=38；BW=230±16.4kg）按初始体重、平均日增重（ADG）、牛疱疹病毒 1 和曼海姆氏菌血清滴度进行随机分组。在 VB 挑战之前和之后，通过远程连续监测奶牛的采食量、动物活动和瘤胃温度。VB 感染的奶牛表现出 ADG 和采食量降低（P<0.01），以及中性粒细胞增加和瘤胃温度升高（P<0.01），与牛呼吸道疾病（BRD）感染一致。然而，没有一头奶牛表现出明显的临床疾病症状。评估了 Shewhart 和累积和（CUSUM）图表，并计算了 VB 感染牛（n=19）和 PBS 感染牛（n=19）的敏感性和特异性，准确性为敏感性和特异性的平均值。为了解决瘤胃温度响应的昼夜性质，计算了每日四分位数（6 小时间隔）的汇总统计数据（平均值、最小值和最大值），并分别评估了这些四分位数温度模型。在 Shewhart 分析中，DMI 是最准确的（95%），可以区分 PBS 和 VB 感染的奶牛，其次是 2 到 3 四分位数的瘤胃温度。休息是最准确的基于加速度计的特征（89%），而进餐持续时间（87%）和料槽访问频率（82%）是最准确的采食行为特征。Shewhart 分析中监测到的第 3 四分位数的瘤胃温度最早（2.5d）发出信号，其次是料槽访问频率（2.8d）、进餐持续时间（2.8d）、DMI（3.0d）和休息（4.0d）。在 CUSUM 中，DMI 和瘤胃温度仍然是最准确的变量，分别为 80%和 79%。在用 CUSUM 分析监测时，进餐持续时间（58%）、料槽访问频率（71%）和休息（74%）的准确性较低。此外，与 Shewhart 分析相比，DMI、瘤胃温度和进餐持续时间的信号日更大（分别为 4.4、5.0 和 3.7d）。这些结果表明，Shewhart 和 CUSUM 图表可以有效地识别采食量、活动和瘤胃温度模式的偏差，用于检测肉牛亚临床 BRD。
