Rajiv Gandhi Institute of Veterinary Education and Research, Kurumbapet, Puducherry 605009, India.
ICAR-National Institute of Animal Nutrition and Physiology, Adugodi, Bangalore 560030, India.
Sensors (Basel). 2024 Sep 11;24(18):5890. doi: 10.3390/s24185890.
Heat stress impacts ruminant livestock production on varied levels in this alarming climate breakdown scenario. The drastic effects of the global climate change-associated heat stress in ruminant livestock demands constructive evaluation of animal performance bordering on effective monitoring systems. In this climate-smart digital age, adoption of advanced and developing Artificial Intelligence (AI) technologies is gaining traction for efficient heat stress management. AI has widely penetrated the climate sensitive ruminant livestock sector due to its promising and plausible scope in assessing production risks and the climate resilience of ruminant livestock. Significant improvement has been achieved alongside the adoption of novel AI algorithms to evaluate the performance of ruminant livestock. These AI-powered tools have the robustness and competence to expand the evaluation of animal performance and help in minimising the production losses associated with heat stress in ruminant livestock. Advanced heat stress management through automated monitoring of heat stress in ruminant livestock based on behaviour, physiology and animal health responses have been widely accepted due to the evolution of technologies like machine learning (ML), neural networks and deep learning (DL). The AI-enabled tools involving automated data collection, pre-processing, data wrangling, development of appropriate algorithms, and deployment of models assist the livestock producers in decision-making based on real-time monitoring and act as early-stage warning systems to forecast disease dynamics based on prediction models. Due to the convincing performance, precision, and accuracy of AI models, the climate-smart livestock production imbibes AI technologies for scaled use in the successful reducing of heat stress in ruminant livestock, thereby ensuring sustainable livestock production and safeguarding the global economy.
在这种气候崩溃的情况下，热应激会对不同水平的反刍家畜生产造成影响。全球气候变化引起的热应激对反刍家畜的剧烈影响，要求对动物性能进行建设性评估，接近有效的监测系统。在这个气候智能的数字时代，采用先进和发展中的人工智能 (AI) 技术正因其在评估生产风险和反刍家畜对气候的适应能力方面的广阔前景而受到关注。由于在评估反刍家畜生产风险和气候适应能力方面具有广阔的前景，人工智能已经广泛应用于对气候敏感的反刍家畜行业。随着新型人工智能算法的采用，反刍家畜的性能评估取得了显著的改善。这些基于人工智能的工具具有强大的功能和能力，可以扩展动物性能的评估，并有助于减少反刍家畜热应激带来的生产损失。通过基于行为、生理和动物健康反应的自动监测反刍家畜的热应激，实现了先进的热应激管理，这些技术包括机器学习 (ML)、神经网络和深度学习 (DL) 等技术的发展。基于人工智能的工具涉及自动数据收集、预处理、数据整理、适当算法的开发以及模型的部署，帮助畜牧生产者根据实时监测做出决策，并作为早期预警系统，根据预测模型预测疾病动态。由于人工智能模型的性能、精度和准确性令人信服，智能畜牧生产采用人工智能技术进行规模化应用，成功降低了反刍家畜的热应激，从而确保了可持续的畜牧生产和保护全球经济。
