科研動(dòng)態(tài)

為了解國(guó)內(nèi)外奶牛疫病預(yù)警技術(shù)及其應(yīng)用現(xiàn)狀，歸納了奶牛疾病的預(yù)警要求，分析了國(guó)內(nèi)外8種疫病預(yù)警技術(shù)的發(fā)展現(xiàn)狀及其在奶牛養(yǎng)殖中存在的局限性。一是獸醫(yī)巡檢預(yù)警技術(shù)：該技術(shù)較為成熟，但不能滿足大規(guī)模養(yǎng)殖牛場(chǎng)迅速、高效預(yù)警的需求。二是奶樣體細(xì)胞數(shù)測(cè)定技術(shù)：可初步診斷隱性乳腺炎，但需要額外細(xì)菌培養(yǎng)和檢測(cè)確診。三是奶牛群體改良測(cè)定技術(shù)：以監(jiān)測(cè)生產(chǎn)性能為主，僅可預(yù)警奶牛乳腺炎及酮病。四是計(jì)步器及發(fā)情、反芻項(xiàng)圈預(yù)警技術(shù)：同時(shí)具備發(fā)情與反芻監(jiān)測(cè)功能，但僅適用于牛群的發(fā)情與反芻監(jiān)測(cè)。五是大數(shù)據(jù)挖掘技術(shù)：在數(shù)據(jù)庫(kù)基礎(chǔ)上，利用各種模型或算法預(yù)測(cè)傳染病的發(fā)生和發(fā)展，但預(yù)警效率受限。六是智能化體溫連續(xù)遠(yuǎn)程監(jiān)測(cè)及預(yù)警技術(shù)：可預(yù)警口蹄疫等重大傳染病，但無(wú)法完全替代臨床診斷，不能監(jiān)測(cè)病原微生物。七是基于AI和群體熱成像的奶牛行為分析技術(shù)：可以監(jiān)視記錄奶牛行為與溫度特征，鎖定病畜，但對(duì)發(fā)病初期無(wú)異常行為的牛只無(wú)效。八是生物氣溶膠激光光譜測(cè)量技術(shù)：通過(guò)檢測(cè)病原微生物種類和濃度，達(dá)到預(yù)警疫病的目的，目前主要用于軍方監(jiān)測(cè)人類重大疫病。未來(lái)的奶牛疫病預(yù)警技術(shù)需要進(jìn)一步相互結(jié)合、取長(zhǎng)補(bǔ)短，充分利用大數(shù)據(jù)、物聯(lián)網(wǎng)等新興技術(shù)進(jìn)行奶牛重大疫病預(yù)警診斷。本文為預(yù)警監(jiān)測(cè)技術(shù)的本地化發(fā)展提供了參考。

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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