首页> 外文期刊>Analytical methods >Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis - moving out of the laboratory and into the food supply chain
【24h】

Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis - moving out of the laboratory and into the food supply chain

机译:傻瓜相机:用于现场食品欺诈分析的快速定量检测方法-移出实验室,进入食品供应链

获取原文
获取原文并翻译 | 示例
           

摘要

Major food adulteration and contamination events occur with alarming regularity and are known to be episodic, with the question being not if but when another large-scale food safety/integrity incident will occur. Indeed, the challenges of maintaining food security are now internationally recognised. The ever increasing scale and complexity of food supply networks can lead to them becoming significantly more vulnerable to fraud and contamination, and potentially dysfunctional. This can make the task of deciding which analytical methods are more suitable to collect and analyse (bio)chemical data within complex food supply chains, at targeted points of vulnerability, that much more challenging. It is evident that those working within and associated with the food industry are seeking rapid, user-friendly methods to detect food fraud and contamination, and rapid/high-throughput screening methods for the analysis of food in general. In addition to being robust and reproducible, these methods should be portable and ideally handheld and/or remote sensor devices, that can be taken to or be positioned on/at-line at points of vulnerability along complex food supply networks and require a minimum amount of background training to acquire information rich data rapidly (ergo point-and-shoot). Here we briefly discuss a range of spectrometry and spectroscopy based approaches, many of which are commercially available, as well as other methods currently under development. We discuss a future perspective of how this range of detection methods in the growing sensor portfolio, along with developments in computational and information sciences such as predictive computing and the Internet of Things, will together form systems- and technology-based approaches that significantly reduce the areas of vulnerability to food crime within food supply chains. As food fraud is a problem of systems and therefore requires systems level solutions and thinking.
机译:严重的食品掺假和污染事件以惊人的规律性发生,并且是偶发性的,问题不在于是否会在何时发生另一次大规模食品安全/完整性事件。确实,维护粮食安全的挑战现已得到国际公认。食品供应网络的规模和复杂性不断增加,可能导致它们变得更加容易受到欺诈和污染的影响,并可能出现功能失调的情况。这可以决定在目标脆弱点更复杂的食品供应链中,哪种分析方法更适合于收集和分析(生物)化学数据,这一任务更具挑战性。显然,与食品工业相关并与之相关联的人们正在寻求快速,用户友好的方法来检测食品欺诈和污染,以及寻求快速/高通量筛选方法来分析食品。这些方法除了要健壮和可重现外,还应该是便携式的,理想情况下应该是手持式和/或远程传感器设备,可以沿着复杂的食品供应网络携带或在线放置或在线放置在易受伤害的位置,并且需要的数量最少进行背景培训以快速获取信息丰富的数据(遍历傻瓜)。在这里,我们简要讨论了一系列基于光谱学和光谱学的方法,其中许多是可商购的,以及当前正在开发的其他方法。我们讨论了在日益增长的传感器产品组合中这种检测方法范围的未来观点,以及诸如预测计算和物联网之类的计算和信息科学的发展将如何共同形成基于系统和技术的方法,从而大大减少食品供应链中易受食品犯罪影响的领域。由于食品欺诈是系统问题,因此需要系统级解决方案和思考。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号