Metabolomic-guided comprehensive food analysis and smart food traceability

据保守估计，食品欺诈每年给全球食品行业造成650亿美元的损失。食品欺诈不仅会造成经济损失，还会损害消费者对政府和食品行业的信任，潜在地在产品中隐藏有害成分，并阻止消费者根据他们的营养需求以及宗教和其他信仰(如素食主义者)做出明智的决定。近年来，由于全球粮食供应链日益复杂，这一问题变得更加严重。为了解决这个问题，我们的小组将开发新的有效的分析方法，并将它们与全球信息共享系统相结合，以发现欺诈产品并及时将结果分享给所有利益相关者(即消费者、食品行业和政府)。我这个项目的长期研究目标是推动检测假冒食品的分析技术的进步，并将先进的分析方法与包括物联网和人工智能在内的信息技术相结合。这将允许食品价值链上的即时成果共享，并最好地保护所有利益攸关方免受食品欺诈的影响。在这个5年的研究计划中，我将使用代谢组学来识别能够实现可靠的食品认证的新的食品标记。针对这些新型食品标记物，我将开发两种适用于不同应用场景的食品认证快速分析方法。第一种方法是一种廉价的一次性纸基微流控传感器，可以应用于现场筛选食品真实性，而不需要实验室规模的仪器。第二种方法是基于实验室规模的仪器(即环境电离源-质谱仪)的一步半定量分析。为了实现即时结果共享，将开发一个基于网络的用户界面，以处理这两种分析方法收集的数据，解释结果，并以自动化和即时方式与利益攸关方分享结果。植物性牛奶替代品将被用作这些概念验证研究活动的示范食品。这些拟议研究活动的成果包括一个全面的食品化学概况数据库，有助于开发食品真实性以及食品安全和质量的新分析方法。将开发的两种快速分析方法将为检验机构、食品行业和消费者提供更强大的工具来调查食品欺诈问题。此外，基于网络的用户界面将为成功的基于物联网的食品可追溯平台奠定基础，该平台将在我的研究计划中长期开发，将提供一个全面的平台来解决食品欺诈问题。这些结果将保护加拿大消费者、食品行业以及政府免受食品欺诈的影响。

Food fraud is conservatively estimated to cause $65B USD in damage to the global food industry every year. Food fraud not only causes economic damage, but also impairs consumers' trust in government and the food industry, potentially hides harmful ingredients in the products, and prevents consumers from making wise decisions based on their nutritional needs as well as religious and other beliefs (e.g., vegetarian). This issue has become more serious in recent years due to the increasingly complex global food supply chain. To address this issue, our group will develop new and effective analytical methods and integrate them with a global information sharing system to detect fraudulent products and share the results to all stakeholders (i.e., consumers, food industry and government) in a timely manner. The long-term research objective of my program is to push the advancement of analytical techniques for the detection of fraudulent foods and integrate the advanced analytical methods with information technologies including the Internet of Things and artificial intelligence. This will allow instant results sharing along the food value chain and best protects all stakeholders from food fraud. For this 5-year research plan, I will use metabolomics to identify novel food markers that can achieve reliable food authentication. Targeting these novel food markers, I will develop two rapid analytical methods for food authentication suitable for different application scenarios. The first method is a cheap and disposable paper-based microfluidic sensor that can be applied in the field to screen food authenticity, independent of laboratory-scale instrumentation. The second method is a one-step, semi-quantitative analysis based on a laboratory scale instrument (i.e., ambient ionization source-mass spectrometry). To achieve instant results sharing, a web-based user interface will be developed to process the data collected by the two analytical methods, interpret the results, and share the results with stakeholders in an automated and instant manner. Plant-based milk alternatives will be used as a model food commodity for these proof-of-concept research activities. The outcomes of these proposed research activities include a comprehensive database for chemical profiles of foods that are useful for the development of novel analytical methods for food authenticity, as well as food safety and quality. The two rapid analytical methods that will be developed will provide inspection agencies, the food industry and consumers with more powerful tools to investigate food fraud issues. Moreover, the web-based user interface will lay a foundation for a successful Internet of Things-based food traceability platform that will be developed over the long term in my research program which will provide a comprehensive platform to address food fraud. These outcomes will protect Canadian consumers, the food industry as well as governments from the impact of food fraud.