科研动态

为了解国内外奶牛疫病预警技术及其应用现状，归纳了奶牛疾病的预警要求，分析了国内外8种疫病预警技术的发展现状及其在奶牛养殖中存在的局限性。一是兽医巡检预警技术：该技术较为成熟，但不能满足大规模养殖牛场迅速、高效预警的需求。二是奶样体细胞数测定技术：可初步诊断隐性乳腺炎，但需要额外细菌培养和检测确诊。三是奶牛群体改良测定技术：以监测生产性能为主，仅可预警奶牛乳腺炎及酮病。四是计步器及发情、反刍项圈预警技术：同时具备发情与反刍监测功能，但仅适用于牛群的发情与反刍监测。五是大数据挖掘技术：在数据库基础上，利用各种模型或算法预测传染病的发生和发展，但预警效率受限。六是智能化体温连续远程监测及预警技术：可预警口蹄疫等重大传染病，但无法完全替代临床诊断，不能监测病原微生物。七是基于AI和群体热成像的奶牛行为分析技术：可以监视记录奶牛行为与温度特征，锁定病畜，但对发病初期无异常行为的牛只无效。八是生物气溶胶激光光谱测量技术：通过检测病原微生物种类和浓度，达到预警疫病的目的，目前主要用于军方监测人类重大疫病。未来的奶牛疫病预警技术需要进一步相互结合、取长补短，充分利用大数据、物联网等新兴技术进行奶牛重大疫病预警诊断。本文为预警监测技术的本地化发展提供了参考。

Development Status of Early Warning and Surveillance Technologies for Cow Diseases

 In order to identify the development and application of early warning and surveillance technologies for cow diseases in the world，relevant requirements for the technologies were summarized，and the development status of 8 different technologies and their limitations in cow breeding industry were analyzed. Specifically，for the technology of routing inspection and early warning by veterinarian，it was relatively mature，but failed to meet the need for rapid and efficient early warning in large-scale farms；for the technology of somatic cell count（SCC）of milk samples，by which，recessive mastitis could be initially diagnosed，but additional bacterial culture and testing would still be needed；for the dairy herd improvement（DHI）technology，it mainly focused on the monitoring of production performance，and only could be applied to early warning of cow mastitis and ketosis；for the pedometer and collar early warning technology for estrous and ruminant，it was only appropriate for monitoring of estrous and ruminant of the cows；for big data mining technology，the occurrence and development of infectious diseases could be predicted by various models or algorithms based on the database，but its efficiency was limited；for intelligent continuous remote temperature monitoring and early warning technology，major infectious diseases such as foot-and-mouth disease could be warned，but it could not fully replace clinical diagnosis and failed to monitor pathogenic microorganisms；for the cow behavior analysis technology based on AI and population thermal imaging，the behavior and temperature characteristics of cows could be monitored and recorded，sick cows could be targeted，but the technology was invalid for the cows without any abnormal behaviors at the early stage of the disease；and for bio-aerosol laser spectrometric measurement technology，the purpose of early warning could be achieved through the testing of species and concentration of pathogenic microorganism，which was mainly used to monitor major diseases in human by military at present. In conclusion，the early warning technologies for cow diseases should be further combined with each other in the future，learn from each other and make full use of big data，internet of things and other emerging technologies，which would contribute to early warning and diagnosis of major cow diseases. Some references were provided for the localization development of early warning and surveillance technologies.

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