Heat stress is a significant challenge in dairy farming systems. Dairy cows under heat stress will encounter impaired welfare leading to production losses. As the frequency and magnitude of heat stress events increase in the coming decades, a focus on heat stress reduction studies becomes important. Modelling and on-farm experiments have been used to assess the effects of heat stress on livestock over the last few decades. Mitigation solutions including optimal shed structure, ventilation, feeding regimes, farm management and genetic selection have all been explored. However, under different farm conditions, the heat tolerance and coping ability of dairy cows can vary significantly. Until now, the results from different mathematical models have provided a variety of heat stress thresholds for on-farm use. In practice, it is still costly to determine an accurate heat stress level in order to identify the mitigation requirements. This review summarises previous studies on the effects of heat stress on intensively reared dairy cows and different mitigation approaches. We have undertaken a comparative analysis of thermal indices, animal responses, and mitigation approaches. Recommendations are then given for developing a framework to enhance the measurement, assessment and mitigation of heat stress. Robust monitoring systems, big data analyses and artificial intelligence algorithms are needed for the future development of dynamic, self-calibrating model-based systems, which could provide real-time assessment and minimisation of heat stress.

中文翻译：

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测量、评估和减轻奶牛热应激的综述

热应激是奶牛养殖系统的重大挑战。处于热应激状态的奶牛会遭遇福利受损，从而导致生产损失。随着未来几十年热应激事件的频率和幅度增加，关注减少热应激的研究变得很重要。在过去的几十年里，建模和农场实验已被用于评估热应激对牲畜的影响。包括最佳棚屋结构、通风、饲养制度、农场管理和遗传选择在内的缓解解决方案都已被探索。然而，在不同的农场条件下，奶牛的耐热性和应对能力可能会有很大差异。到目前为止，不同数学模型的结果为农场使用提供了各种热应激阈值。在实践中，确定准确的热应力水平以确定缓解要求的成本仍然很高。本综述总结了先前关于热应激对集约化饲养奶牛的影响和不同缓解方法的研究。我们对热指数、动物反应和缓解方法进行了比较分析。然后就制定框架以加强热应激的测量、评估和缓解提出建议。动态、自校准基于模型的系统的未来发展需要强大的监测系统、大数据分析和人工智能算法，这些系统可以提供实时评估和热应力最小化。本综述总结了先前关于热应激对集约化饲养奶牛的影响和不同缓解方法的研究。我们对热指数、动物反应和缓解方法进行了比较分析。然后就制定框架以加强热应激的测量、评估和缓解提出建议。动态、自校准基于模型的系统的未来发展需要强大的监测系统、大数据分析和人工智能算法，这些系统可以提供实时评估和热应力最小化。本综述总结了先前关于热应激对集约化饲养奶牛的影响和不同缓解方法的研究。我们对热指数、动物反应和缓解方法进行了比较分析。然后就制定框架以加强热应激的测量、评估和缓解提出建议。动态、自校准基于模型的系统的未来发展需要强大的监测系统、大数据分析和人工智能算法，这些系统可以提供实时评估和热应力最小化。然后就制定框架以加强热应激的测量、评估和缓解提出建议。动态、自校准基于模型的系统的未来发展需要强大的监测系统、大数据分析和人工智能算法，这些系统可以提供实时评估和热应力最小化。然后就制定框架以加强热应激的测量、评估和缓解提出建议。动态、自校准基于模型的系统的未来发展需要强大的监测系统、大数据分析和人工智能算法，这些系统可以提供实时评估和热应力最小化。