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Development of a standard food authenticity testing workflow for honey using non-targeted LC/MS analysis

Development of a standard food authenticity testing workflow for honey using non-targeted LC/MS analysis
使用非靶向 LC/MS 分析开发蜂蜜标准食品真实性测试工作流程
批准号:
570864-2021
负责人:
Bayen, StephaneS
金额:
$14.45万
依托单位:
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
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英文摘要
Food fraud (including substitution, adulteration or mislabeling - e.g. origin) is a threat to our food system, resulting into economic losses for consumers and producers of authentic food, with potential food safety consequences. As one of the oldest sweeteners, honey has always been subject to fraud and adulteration. Updated tools are currently needed to test the authenticity of honey, especially since fraudulent practices evolve quickly. An alternative to conventional methods targeting only limited types of adulteration is a more comprehensive multiparameter screening of food products, using high resolution mass spectrometry based non-targeted analysis (NTA). The novelty of the approach relies on the collection and the analysis of a large chemical fingerprint for each sample. NTA now regarded as the next stage of surveillance tools for food. Non-targeted fingerprinting is promising for food authenticity but results are not always replicable and requires standardization. In this project, researchers from McGill University, Laval University, Agilent Technologies, Health Canada, the Canadian Food Inspection Agency and Vogon Laboratory Services, bring together their expertises to harmonize non-targeted fingerprinting workflows used for food authenticity, and develop robust standard protocols for non-targeted analysis which can be used effectively on actual food products sold in the market, using honey as an initial case study. More specifically, this project intends to (i) understand the impact of thermal processing and filtration on the chemical fingerprint of honey; (ii) Establish the fingerprints for >450 honey samples; (iii) Systematically compare & rank a wide range of data processing, data analysis tools for the chemometric based classification of honey samples, (iv) Develop a rapid, robust semi-routine end-to-end workflow to track quality attributes of honey (primarily floral origin) and validate the performance of the standard protocol through a pilot interlaboratory test.
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“合金标准”下测量误差校正模型及其在体育运动数据中的应用
  • 批准号:
    10801133
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    17.0万元
  • 批准年份:
    2008
  • 负责人:
    张三国
  • 依托单位:
基于动态腭位(EPG)的普通话协同发音研究