Journal of Integrative Agriculture ›› 2015, Vol. 14 ›› Issue (11): 2296-2308.DOI: 10.1016/S2095-3119(15)61122-4

• 论文 • 上一篇    下一篇

Methods to detect avian influenza virus for food safety surveillance

 SHI Ping, Shu Geng, LI Ting-ting, LI Yu-shui, FENG Ting, WU Hua-nan   

  1. 1 School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, P.R.China
    2 Sino-US Joint Food Safety Research Center, Northwest A&F University, Yangling 712100, P.R.China
    3 Department of Plant Science, University of California, Davis, CA 95616, USA
  • 收稿日期:2014-12-26 出版日期:2015-11-08 发布日期:2015-11-12
  • 通讯作者: WU Hua-nan,Tel: +86-755-26032670, Fax: +86-755-26035332,E-mail: wuhn@pkusz.edu.cn
  • 作者简介:SHI Ping, E-mail: shiping@pkusz.edu.cn; Shu Geng,E-mail: gengxu@pkusz.edu.cn;* These authors contributed equally to this study.
  • 基金资助:

    This research is 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) and the Start-up Funds for Talents in Northwest A&F University, China (Z111021403).

Methods to detect avian influenza virus for food safety surveillance

 SHI Ping, Shu Geng, LI Ting-ting, LI Yu-shui, FENG Ting, WU Hua-nan   

  1. 1 School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, P.R.China
    2 Sino-US Joint Food Safety Research Center, Northwest A&F University, Yangling 712100, P.R.China
    3 Department of Plant Science, University of California, Davis, CA 95616, USA
  • Received:2014-12-26 Online:2015-11-08 Published:2015-11-12
  • Contact: WU Hua-nan,Tel: +86-755-26032670, Fax: +86-755-26035332,E-mail: wuhn@pkusz.edu.cn
  • About author:SHI Ping, E-mail: shiping@pkusz.edu.cn; Shu Geng,E-mail: gengxu@pkusz.edu.cn;* These authors contributed equally to this study.
  • Supported by:

    This research is 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) and 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.

关键词: avian influenza , food safety , detection methods , poultry supply chain , surveillance system

Abstract: 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.

Key words: avian influenza , food safety , detection methods , poultry supply chain , surveillance system