Pérez-Rebolloso Elizabeth, García José E, Morales Juan L, Calderón María G, Alvarado Alan S, Macías-Cruz Ulises, Avendaño-Reyes Leonel, Mellado Miguel
Department of Veterinary Science, Autonomous Agrarian University Antonio Narro, Torreon, Mexico.
Department of Animal Nutrition, Autonomous Agrarian University Antonio Narro, Saltillo, Mexico.
Trop Anim Health Prod. 2025 Mar 19;57(3):134. doi: 10.1007/s11250-025-04388-6.
This study aimed to predict the pregnancy rate (PR) and number of services per pregnancy (SP) in a large high-input dairy herd in a prolonged high ambient temperature zone. Also, the impact of climatic conditions on reproductive performance was assessed. An autoregressive integrated moving average (ARIMA) model was used in data fitting to predict future monthly PR and SP using data from 2014 to 2020. The highest predicted PR for cows was in January (35.3%; 95% CI = 30.5-40.1), and the lowest was in August (12.5%; 95% CI = 7.5-17.6). Temperature-humidity index (THI) and PR were significantly negatively correlated in the same month (r = 0.7) and 2.5 months earlier and 2.5, 5, and 7.5 months later. The predicted highest SP for cows was in September (6.2; 95% CI = 4.8-7.7) and the lowest for March (2.8; 95% CI = 1.3-4.2). The predicted highest PR in heifers was in January (62.2%; CI = 51.6-72.9) and the lowest in May (52.3%; 37.9-66.7). The cross-correlation between THI and PR in heifers was not significantly correlated in the same month, but significantly negative correlations occurred 5, 7.5, and 10 months earlier. SP in heifers were related to seasonality, with the predicted maximum SP occurring in May (1.9; CI = 1.2-2.6) and the minimum in February (1.6; CI = 1.0-2.2). It was concluded that weather strongly influenced the monthly reproductive performance rhythms of Holstein cows and heifers. Also, ARIMA models robustly forecasted reproductive outcomes of dairy cows and heifers in a hot desert climate.
本研究旨在预测高温持续地区一个大型高投入奶牛场的受胎率（PR）和每次妊娠的配种次数（SP）。此外，还评估了气候条件对繁殖性能的影响。采用自回归积分滑动平均（ARIMA）模型进行数据拟合，利用2014年至2020年的数据预测未来每月的PR和SP。奶牛预测的最高PR出现在1月（35.3%；95%置信区间=30.5-40.1），最低出现在8月（12.5%；95%置信区间=7.5-17.6）。温度湿度指数（THI）与当月的PR显著负相关（r=0.7），且在提前2.5个月以及之后的2.5、5和7.5个月也显著负相关。奶牛预测的最高SP出现在9月（6.2；95%置信区间=4.8-7.7），最低出现在3月（2.8；95%置信区间=1.3-4.2）。小母牛预测的最高PR出现在1月（62.2%；置信区间=51.6-72.9），最低出现在5月（52.3%；37.9-66.7）。小母牛的THI与PR在当月无显著相关性，但在提前5、7.5和10个月时呈显著负相关。小母牛的SP与季节有关，预测的最高SP出现在5月（1.9；置信区间=1.2-2.6），最低出现在2月（1.6；置信区间=1.0-2.2）。研究得出结论，天气对荷斯坦奶牛和小母牛的每月繁殖性能节律有强烈影响。此外，ARIMA模型能够可靠地预测炎热沙漠气候下奶牛和小母牛的繁殖结果。
