Metabolomic-guided comprehensive food analysis and smart food traceability

代谢组学引导的综合食品分析和智能食品追溯

• 批准号: RGPIN-2022-04892
• 负责人: Hu, Yaxi
• 金额: $ 2.4万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=747913
• 关键词: Metabolomic; guided; comprehensive; food; analysis

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.

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。食品欺诈不仅造成经济损失，而且损害消费者对政府和食品行业的信任，可能隐藏产品中的有害成分，并阻止消费者根据其营养需求以及宗教和其他信仰（例如，素食者）。近年来，由于全球食品供应链日益复杂，这一问题变得更加严重。为了解决这个问题，我们的团队将开发新的有效的分析方法，并将其与全球信息共享系统相结合，以检测欺诈产品，并将结果分享给所有利益相关者（即，消费者、食品工业和政府）。我的项目的长期研究目标是推动欺诈食品检测分析技术的进步，并将先进的分析方法与物联网和人工智能等信息技术相结合。这将允许在食品价值链上沿着共享即时结果，并最好地保护所有利益相关者免受食品欺诈。 在这个为期5年的研究计划中，我将使用代谢组学来识别可以实现可靠食品认证的新型食品标记物。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体传感器，可以应用于现场筛选食品的真实性，独立于实验室规模的仪器。第二种方法是基于实验室规模仪器的一步半定量分析（即，常压电离源-质谱法）。为即时分享结果，将开发一个基于网络的用户界面，以自动化和即时的方式处理通过两种分析方法收集的数据，解释结果，并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。 这些拟议的研究活动的成果包括建立一个全面的食品化学特征数据库，有助于开发新的食品真实性分析方法，以及食品安全和质量。即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，以调查食品欺诈问题。此外，基于网络的用户界面将为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，这将提供一个解决食品欺诈的综合平台。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。