季节、月份以及温度-湿度指数与牛奶产量、成分、体细胞计数和微生物负荷之间的定量关联：一项对十个奶牛场全年周期的综合研究。
Quantitative Associations between Season, Month, and Temperature-Humidity Index with Milk Yield, Composition, Somatic Cell Counts, and Microbial Load: A Comprehensive Study across Ten Dairy Farms over an Annual Cycle.
作者信息
Bokharaeian Mostafa, Toghdory Abdolhakim, Ghoorchi Taghi, Ghassemi Nejad Jalil, Esfahani Iman Janghorban
机构信息
Department of Animal and Poultry Nutrition, Animal Science Faculty, Gorgan University of Agricultural Science and Natural Resources, Gorgan 49189-43464, Iran.
Department of Animal Science and Technology, Sanghuh College of Life Sciences, Konkuk University, Seoul 05029, Republic of Korea.
出版信息
Animals (Basel). 2023 Oct 13;13(20):3205. doi: 10.3390/ani13203205.
This current study addresses the knowledge gap regarding the influence of seasons, months, and THI on milk yield, composition, somatic cell counts (SCC), and total bacterial counts (TBC) of dairy farms in northeastern regions of Iran. For this purpose, ten dairy herds were randomly chosen, and daily milk production records were obtained. Milk samples were systematically collected from individual herds upon delivery to the dairy processing facility for subsequent analysis, including fat, protein, solids-not-fat (SNF), pH, SCC, and TBC. The effects of seasons, months, and THI on milk yield, composition, SCC, and TBC were assessed using an analysis of variance. To account for these effects, a mixed-effects model was utilized with a restricted maximum likelihood approach, treating month and THI as fixed factors. Our investigation revealed noteworthy correlations between key milk parameters and seasonal, monthly, and THI variations. Winter showed the highest milk yield, fat, protein, SNF, and pH ( < 0.01), whereas both SCC and TBC reached their lowest values in winter ( < 0.01). The highest values for milk yield, fat, and pH were recorded in January ( < 0.01), while the highest protein and SNF levels were observed in March ( < 0.01). December marked the lowest SCC and TBC values ( < 0.01). Across the THI spectrum, spanning from -3.6 to 37.7, distinct trends were evident. Quadratic regression models accounted for 34.59%, 21.33%, 4.78%, 20.22%, 1.34%, 15.42%, and 13.16% of the variance in milk yield, fat, protein, SNF, pH, SCC, and TBC, respectively. In conclusion, our findings underscore the significant impact of THI on milk production, composition, SCC, and TBC, offering valuable insights for dairy management strategies. In the face of persistent challenges posed by climate change, these results provide crucial guidance for enhancing production efficiency and upholding milk quality standards.
本研究填补了关于季节、月份和温湿度指数（THI）对伊朗东北部地区奶牛场牛奶产量、成分、体细胞计数（SCC）和总细菌计数（TBC）影响方面的知识空白。为此，随机选择了10个奶牛群，并获取了每日牛奶生产记录。牛奶样本在送至乳制品加工设施时从各个牛群中系统采集，以便后续分析，包括脂肪、蛋白质、非脂固形物（SNF）、pH值、SCC和TBC。使用方差分析评估季节、月份和THI对牛奶产量、成分、SCC和TBC的影响。为了考虑这些影响，采用了混合效应模型和限制最大似然法，将月份和THI视为固定因素。我们的调查揭示了关键牛奶参数与季节、月度和THI变化之间的显著相关性。冬季的牛奶产量、脂肪、蛋白质、SNF和pH值最高（<0.01），而SCC和TBC在冬季达到最低值（<0.01）。1月份记录到牛奶产量、脂肪和pH值的最高值（<0.01），而3月份观察到蛋白质和SNF水平最高（<0.01）。12月份的SCC和TBC值最低（<0.01）。在-3.6至37.7的THI范围内，明显的趋势很明显。二次回归模型分别解释了牛奶产量、脂肪、蛋白质、SNF、pH值、SCC和TBC变异的34.59%、21.33%、4.78%、20.22%、1.34%、15.42%和13.16%。总之，我们的研究结果强调了THI对牛奶生产、成分、SCC和TBC的重大影响，为奶牛管理策略提供了有价值的见解。面对气候变化带来的持续挑战，这些结果为提高生产效率和维持牛奶质量标准提供了关键指导。
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