Food Fraud Detection: How to differentiate food fraud from cross-contamination?
食品欺诈检测:如何区分食品欺诈和交叉污染?
基本信息
- 批准号:538382-2018
- 负责人:
- 金额:$ 1.74万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Research and Development Grants
- 财政年份:2019
- 资助国家:加拿大
- 起止时间:2019-01-01 至 2020-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Fraud has become one major concern of consumers and can be defined by four aspects: (1) an intentional act (2) for an economic gain (3) that should not be detected and (4) that results in a food product misrepresentation. The types of frauds can vary from a falsified composition, a false product origin, its substitution, or counterfeiting. Beyond potentially causing safety issues, food fraud can lead to massive economic losses and the lack of consumer confidence. To mitigate the risks, agribusiness companies can assess those that are related to fraud. However, analytical methods applied to identify food frauds are not validated or standardized across labs and countries. Similarly, quantitative differences between a fraud and a quality failure are not clear leading to uncertainty in the interpretation of a test result. In other words, if a substance is detected, should one immediately conclude to a willingness to commit a fraud or is it the result of accidental contamination? This project aims at studying adulterant occurrences and concentrations in food matrices that were prepared to mimic fraud or cross-contamination. Protocols to manufacture adulterated or contaminated products at different levels will be designed and food matrices will be made in industrial manufacturing in the event of inadequate cleaning or poor practices in this matter. The methods to detect and to quantify contaminants will be those used or sold by the project partners. By quantifying one or more within food matrices, thresholds between fraud and unintentional presence will be determined. The outcomes of this project will support regulators in their interpretation of results within their fraud surveillance program, and industries while screening supplied materials. The involvement of partners, including federal and provincial government agencies, will ensure the acceptance and implementation of the identified thresholds. Finally, built on the knowledge acquired during the project and the expertise of the research team, reference materials (products which contain controlled quantities of contaminants) will be developed for the standardization of fraud detection methods, thus enabling laboratories to validate their detection methods.
欺诈已成为消费者的一个主要关注点,可以从四个方面来定义:(1)故意行为(2)为了经济利益(3)不应该被发现和(4)导致食品虚假陈述。欺诈的类型可以从伪造的成分、虚假的产品来源、替代品或伪造品中变化。除了可能导致安全问题外,食品欺诈还可能导致巨大的经济损失和消费者信心的缺乏。为了降低风险,农业综合企业公司可以评估与欺诈有关的风险。然而,用于识别食品欺诈的分析方法并没有在实验室和国家之间得到验证或标准化。同样,欺诈和质量不合格之间的定量差异也不明确,导致对测试结果的解释存在不确定性。换句话说,如果检测到一种物质,人们是否应该立即得出愿意实施欺诈的结论,或者这是意外污染的结果?该项目旨在研究食品基质中掺假物的发生和浓度,这些基质是为了模拟欺诈或交叉污染而准备的。将设计制造不同水平掺假或受污染产品的方案,并在工业制造中制造食品基质,以防清洁不充分或这方面的做法不当。检测和量化污染物的方法将是项目合作伙伴使用或出售的方法。通过量化食品基质中的一种或多种,将确定欺诈和无意存在之间的阈值。该项目的成果将支持监管机构在其欺诈监督计划中解释结果,并支持行业在筛选提供的材料时。包括联邦和省政府机构在内的伙伴的参与将确保所确定的门槛得到接受和执行。最后,在项目期间获得的知识和研究小组的专门知识的基础上,将为欺诈检测方法的标准化开发参考材料(含有受控数量污染物的产品),从而使实验室能够验证其检测方法。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Godefroy, Samuel其他文献
Standard Method Performance Requirements (SMPRs) 2017.020: Quantitation of Chicken Egg by ELISA-Based Methods.
- DOI:
10.5740/jaoacint.smpr2017.020 - 发表时间:
2018-07-01 - 期刊:
- 影响因子:1.6
- 作者:
Godefroy, Samuel;Yeung, Jupiter;Yang, Jinchuan - 通讯作者:
Yang, Jinchuan
Stability of milk and gliadin on swabs during 7 days under different storage conditions
- DOI:
10.1016/j.foodcont.2019.107054 - 发表时间:
2020-04-01 - 期刊:
- 影响因子:6
- 作者:
Barrere, Virginie;Theolier, Jeremie;Godefroy, Samuel - 通讯作者:
Godefroy, Samuel
Godefroy, Samuel的其他文献
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{{ truncateString('Godefroy, Samuel', 18)}}的其他基金
Food Fraud Detection: How to differentiate food fraud from cross-contamination?
食品欺诈检测:如何区分食品欺诈和交叉污染?
- 批准号:
538382-2018 - 财政年份:2020
- 资助金额:
$ 1.74万 - 项目类别:
Collaborative Research and Development Grants
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538382-2018 - 财政年份:2020
- 资助金额:
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