This study conducted a retrospective analysis of historical Meat Standard Australia (MSA) carcass data in combination with Bureau of Meteorology (BOM) weather data, to evaluate the relationship between climatic conditions prior to feedlot departure on the incidence of dark cutting grain-fed beef. Data records for 2,795,754 carcasses from 17 commercial feedlots over a 6-year period were evaluated within this study. Carcasses were consigned to 16 abattoirs. Weather data from BOM were recorded at 30-min intervals and were obtained from weather stations with the closest proximity to each feedlot. These data were used to calculate the Temperature Humidity Index (THI). Climatic data were amalgamated into daily observations and a series of predictors including ambient temperature (T_A, °C), relative humidity (RH, %), wind speed (WS, m/s), rainfall (mm) and THI. In addition, lag interactions from 24 h out to 28 days prior to exiting the feedlot were generated. The incidence of dark cutting was determined as percentage per cohort with an ultimate pH > 5.7. Data were analysed using three models: model 1 included feedlot, abattoir, hormone growth promotant status and sex as fixed effects. Model 2 incorporated the fixed effects within model 1 and minimum, maximum and standard deviation (SD) of T_A and RH, daily range in T_A, average WS and rainfall as random effects. Model 3 incorporated minimum, maximum, range and SD of THI, average WS and rainfall as random effects in addition to the fixed effects of model 1. The incidence of dark cutting within feedlot had a 10.1% range in estimated means with the lowest incidence was observed at feedlot 17 (0%) and highest incidence at feedlot 10 (10.1%). The inclusion of the climatic variables in model 2 and model 3 accounted for an additional 0.1 to 0.2% of the incidence of dark cutting carcasses. Higher maximum T_A, RH and THI in the 3 to 28 days prior to consignment were all associated with an increased incidence of dark cutting (P < 0.05), but not in the 48 h preceding consignment (P > 0.05). Low minimum T_A and low THI were also associated with an increase the incidence of dark cutting across all lag periods (P < 0.05). Increased variation in THI and T_A in the 48 h prior to consignment increased dark cutting (P < 0.05) while increased standard deviation (SD) of temperature and THI range also increased dark cutting in the 14 and 28 day prior to feedlot exit (P < 0.05). Smaller minimum ranges in T_A in the 28 days prior to consignment also reduced dark cutting (P < 0.05). Climatic conditions accounted for a further 0.1 to 0.2% of the incidence of dark cutting, whereas animal management factors, feedlot and abattoir were able to account for 21% of dark cutting. These data suggest that climatic conditions appear to have an inherent role in the incidence of dark cutting, albeit a small impact. Regardless, understanding the influence of climatic conditions on dark cutting allows for the implementation of management strategies within the supply chain to further reduce the impact of climatic conditions on grain-fed cattle.

本研究结合气象局 (BOM) 的天气数据对澳大利亚肉类标准 (MSA) 的历史屠体数据进行了回顾性分析，以评估饲养场离开前的气候条件与深色切割谷饲牛肉发生率之间的关系。本研究评估了 6 年内来自 17 个商业饲养场的 2,795,754 头屠体的数据记录。尸体被送往 16 个屠宰场。来自 BOM 的天气数据每隔 30 分钟记录一次，并且是从离每个饲养场最近的气象站获得的。这些数据用于计算温湿度指数 (THI)。气候数据被合并为日常观测和一系列预测指标，包括环境温度（T _A, °C)、相对湿度 (RH, %)、风速 (WS, m/s)、降雨量 (mm) 和 THI。此外，在离开饲养场前 24 小时到 28 天之间产生了滞后相互作用。黑暗切割的发生率以最终 pH > 5.7 的每个队列的百分比确定。使用三个模型分析数据：模型 1 包括饲养场、屠宰场、激素生长促进剂状态和性别作为固定效应。_{模型 2 结合了模型 1 中的固定效应以及 T A}和 RH的最小、最大和标准偏差 (SD)，T _A中的每日范围，平均 WS 和降雨作为随机效应。模型 3 除了模型 1 的固定效应外，还结合了 THI 的最小值、最大值、范围和 SD、平均 WS 和降雨作为随机效应。饲养场内暗刈的发生率在估计平均值中具有 10.1% 的范围，最低发生率是在饲养场 17 (0%) 观察到，在饲养场 10 (10.1%) 发生率最高。模型 2 和模型 3 中包含的气候变量占深色切割屠体发生率的额外 0.1% 至 0.2%。托运前3～28天最大_TA、RH和THI均与暗扦插发生率增加有关（P  <0.05），但与托运前48小时无关（P  >0.05）。低最低 T _A低 THI 也与所有滞后期的暗切发生率增加有关（P  < 0.05）。托运前 48 小时THI 和 T _A的变化增加了暗切（P  < 0.05），而温度和 THI 范围的标准偏差（SD）增加也增加了饲养场退出前 14 天和 28 天的暗切（P  < 0.05)。_{托运前 28 天内 T A}的较小最小范围也减少了暗切（P < 0.05)。气候条件进一步占暗割发生率的 0.1% 至 0.2%，而动物管理因素、饲养场和屠宰场能够占暗割发生率的 21%。这些数据表明，气候条件似乎对暗砍的发生具有内在作用，尽管影响很小。无论如何，了解气候条件对黑暗切割的影响有助于在供应链中实施管理策略，以进一步减少气候条件对谷饲牛的影响。