Methods to detect a vian influenza virus for food safety surveillance  

作　　者：SHI Ping Shu Geng LI Ting-ting LI Yu-shui FENG Ting WU Hua-nan 

机构地区：[1]School of Environment and Energy,Peking University Shenzhen Graduate School [2]Sino-US Joint Food Safety Research Center,Northwest A&F University [3]Department of Plant Science,University of California

出　　处：《Journal of Integrative Agriculture》2015年第11期2296-2308,共13页农业科学学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (21405008);the Shenzhen Municipal Government Subsidies for Postdoctoral Research;the Special Fund for Sino-US Joint Research Center for Food Safety in Northwest A&F University, China (A200021501);the Start-up Funds for Talents in Northwest A&F University, China (Z111021403)

摘　　要：Avian influenza （AI）, caused by the influenza A virus, has been a global concern for public health. AI outbreaks not only impact the poultry production, but also give rise to a risk in food safety caused by viral contamination of poultry products in the food supply chain. Distinctions in AI outbreak between strains H5N1 and H7N9 indicate that early detection of the AI virus in poultry is crucial for the effective warning and control of AI to ensure food safety. Therefore, the establishment of a poultry surveillance system for food safety by early detection is urgent and critical. In this article, methods to detect AI virus, including current methods recommended by the World Health Organization （WHO） and the World Organisation for Animal Health （Office International des Epizooties, OIE） and novel techniques not commonly used or commercialized are reviewed and evaluated for feasibility of use in the poultry surveillance system. Conventional methods usually applied for the purpose of AI diagnosis face some practical challenges to establishing a comprehensive poultry surveillance program in the poultry supply chain. Diverse development of new technologies can meet the specific requirements of AI virus detection in various stages or scenarios throughout the poultry supply chain where onsite, rapid and ultrasensitive methods are emphasized. Systematic approaches or integrated methods ought to be employed according to the application scenarios at every stage of the poultry supply chain to prevent AI outbreaks.Avian influenza （AI）, caused by the influenza A virus, has been a global concern for public health. AI outbreaks not only impact the poultry production, but also give rise to a risk in food safety caused by viral contamination of poultry products in the food supply chain. Distinctions in AI outbreak between strains H5N1 and H7N9 indicate that early detection of the AI virus in poultry is crucial for the effective warning and control of AI to ensure food safety. Therefore, the establishment of a poultry surveillance system for food safety by early detection is urgent and critical. In this article, methods to detect AI virus, including current methods recommended by the World Health Organization （WHO） and the World Organisation for Animal Health （Office International des Epizooties, OIE） and novel techniques not commonly used or commercialized are reviewed and evaluated for feasibility of use in the poultry surveillance system. Conventional methods usually applied for the purpose of AI diagnosis face some practical challenges to establishing a comprehensive poultry surveillance program in the poultry supply chain. Diverse development of new technologies can meet the specific requirements of AI virus detection in various stages or scenarios throughout the poultry supply chain where onsite, rapid and ultrasensitive methods are emphasized. Systematic approaches or integrated methods ought to be employed according to the application scenarios at every stage of the poultry supply chain to prevent AI outbreaks.

关 键 词：avian influenza food safety detection methods poultry supply chain surveillance system 

分 类 号：S852.65[农业科学—基础兽医学]