Department of Animal Sciences and Industry, Kansas State University, Manhattan, KS.
Department of Animal and Dairy Science, University of Georgia, Athens, GA.
J Anim Sci. 2018 Dec 3;96(12):5000-5009. doi: 10.1093/jas/sky353.
The primary objectives of the current study were to investigate animal factors associated with core body temperature (CBT) and to determine the time of the day in which CBT assessment best describes the magnitude of hyperthermia throughout the day of heat-stressed dry cows. The secondary objective was to develop a predictive model for CBT of dry cows. Nonlactating Holstein cows (n = 105) with 250 to 260 d of gestation from 2 commercial dairies were enrolled in the study during summer. During 4 consecutive days, CBT from all cows was recorded in 5-min intervals and average CBT was calculated for each cow. In addition, mean, maximum, minimum, and standard deviation of daily CBT were calculated and using these measures cows were categorized as having high temperature (HT) or low temperature (LT) based on the median values. Cows carrying twins had greater (P < 0.01) CBT than cows bearing singletons (39.07 ± 0.07 vs. 38.84 ± 0.03 °C). Average CBT decreased (P < 0.01) 0.015 ± 0.004 °C for each 1-d increase in gestation length. Cows in Dairy A tended (P = 0.09) to have lower CBT than cows in Dairy B (38.91 ± 0.04 vs. 39.00 ± 0.06 °C). Season of birth, lactation number, body condition score category, previous projected 305-d mature equivalent milk yield, days in milk at dry-off, days after dry-off at enrollment, days of gestation at enrollment, and calf sex were not associated (P > 0.12) with CBT. Principal component analyses showed that 71% of the variance of CBT was explained by the first principal component alone, which was correlated with mean CBT (r = 0.99). Among all time points assessed, CBT recorded at 2215 h had the highest correlation with the first principal component (r = 0.93). The best agreement for classifying cows as HT or LT was between mean daily CBT and assessment at 2215 h (k = 0.73). The model that resulted in best predictivity (0.56) of average CBT included the following variables: dairy, gestation length, and twinning. In conclusion, findings from the present study suggest that CBT assessed between 250 and 260 d of gestation is negatively associated with gestation length and cows bearing twins have greater CBT than singletons. Our results indicate that the best time of the day to evaluate severity of heat stress in dry cows is 2215 h. Predictive models for CBT of dry cows should include dairy, twinning, and gestation length.
本研究的主要目的是探讨与核心体温(CBT)相关的动物因素,并确定在热应激干奶牛的一天中评估 CBT 的最佳时间,以描述全天体温升高的程度。次要目标是为干奶牛的 CBT 建立预测模型。本研究招募了来自 2 个商业奶牛场的 250-260 天妊娠期的非泌乳荷斯坦奶牛(n=105)。在 4 天的连续时间里,每隔 5 分钟记录所有奶牛的 CBT,计算每头奶牛的平均 CBT。此外,计算每日 CBT 的平均值、最大值、最小值和标准差,并根据中位数将奶牛分为高温(HT)或低温(LT)。产双胎的奶牛比产单胎的奶牛 CBT 更高(P<0.01)(39.07±0.07°C 比 38.84±0.03°C)。妊娠期每增加 1 天,CBT 平均降低(P<0.01)0.015±0.004°C。在 Dairy A 中,奶牛的 CBT 倾向于(P=0.09)比 Dairy B 中的奶牛低(38.91±0.04°C 比 39.00±0.06°C)。出生季节、泌乳次数、体况评分类别、先前预测的 305 天成熟当量产奶量、干奶时的泌乳天数、干奶后登记时的天数、登记时的妊娠期天数和犊牛性别与 CBT 无关(P>0.12)。主成分分析表明,CBT 的 71%的方差仅由第一主成分解释,该成分与平均 CBT 相关(r=0.99)。在所评估的所有时间点中,2215 h 记录的 CBT 与第一主成分的相关性最高(r=0.93)。将奶牛分类为 HT 或 LT 的最佳一致性是平均日 CBT 与 2215 h 评估之间(k=0.73)。导致平均 CBT 最佳预测性(0.56)的模型包括以下变量:奶牛场、妊娠期和双胞胎。总之,本研究的结果表明,在 250-260 天妊娠期之间评估的 CBT 与妊娠期长度呈负相关,产双胞胎的奶牛的 CBT 高于产单胎的奶牛。我们的结果表明,评估干奶牛热应激严重程度的最佳时间是 2215 h。干奶牛 CBT 的预测模型应包括奶牛场、双胞胎和妊娠期长度。