Metabolomics for tea authentication and fraud detection: Recent applications and future directions

IF 15.1 1区 农林科学 Q1 FOOD SCIENCE & TECHNOLOGY Trends in Food Science & Technology Pub Date : 2024-05-23 DOI:10.1016/j.tifs.2024.104558
Hui Ru Tan , Weibiao Zhou
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Abstract

Background

With 86.2% of tea production in Asia, teas consumed in other parts of the world are usually imported. The intricacies of the supply chain make tea vulnerable to fraudulent activities, highlighting the importance of ensuring authenticity and detecting fraud committed in teas. Conventionally, tea authentication is done by sensory evaluation. Moreover, the standardised chemical analysis techniques used for the evaluation of tea quality and authenticity are laborious. Thus, metabolomics, particularly the non-targeted metabolic fingerprinting approach, has been increasingly applied for high throughput authentication of tea.

Scope and approach

A brief overview of the metabolomics approach is provided. Then, this review delves into recent applications (i.e., from 2017 to 2023) of metabolomics to detect fraud committed in the form of mislabelling, substitution adulteration, and artificial enhancement. It concludes with future directions that could be undertaken.

Key findings and conclusion

Targeted and non-targeted metabolomics were found to be largely successful in authenticating tea and detecting fraud. There is a growing interest in the use of non-targeted fingerprinting approach using rapid, non-destructive, and easy-to-use analytical platforms (e.g., vibrational spectroscopy, hyperspectral imaging). These techniques provide the possibility for high-throughput, large-scale, and point-of-site screening of teas. Nonetheless, more work on building a reliable database of chemical fingerprints/profiles for future authentication efforts and developing a tier-based approach for a confident confirmation of fraudulent activity perpetrated in tea is needed.

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用于茶叶认证和欺诈检测的代谢组学:最新应用和未来方向
背景86.2%的茶叶产自亚洲,世界其他地区消费的茶叶通常来自进口。错综复杂的供应链使茶叶很容易受到欺诈活动的影响,这凸显了确保茶叶真实性和检测欺诈行为的重要性。传统的茶叶鉴别方法是感官评估。此外,用于评估茶叶质量和真伪的标准化化学分析技术非常费力。因此,代谢组学,特别是非靶向代谢指纹图谱方法,已越来越多地应用于茶叶的高通量鉴定。然后,本综述深入探讨了代谢组学最近(即从 2017 年到 2023 年)在检测标签错误、替代掺假和人工强化等欺诈行为方面的应用。主要发现和结论研究发现,靶向和非靶向代谢组学在鉴定茶叶真伪和检测欺诈方面取得了很大成功。人们对使用快速、非破坏性和易于使用的分析平台(如振动光谱、高光谱成像)进行非目标指纹识别的兴趣与日俱增。这些技术为高通量、大规模和现场点筛选茶叶提供了可能。尽管如此,仍需开展更多工作,为未来的鉴定工作建立可靠的化学指纹/档案数据库,并开发基于分级的方法,以可靠地确认茶叶中的欺诈活动。
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来源期刊
Trends in Food Science & Technology
Trends in Food Science & Technology 工程技术-食品科技
CiteScore
32.50
自引率
2.60%
发文量
322
审稿时长
37 days
期刊介绍: Trends in Food Science & Technology is a prestigious international journal that specializes in peer-reviewed articles covering the latest advancements in technology, food science, and human nutrition. It serves as a bridge between specialized primary journals and general trade magazines, providing readable and scientifically rigorous reviews and commentaries on current research developments and their potential applications in the food industry. Unlike traditional journals, Trends in Food Science & Technology does not publish original research papers. Instead, it focuses on critical and comprehensive reviews to offer valuable insights for professionals in the field. By bringing together cutting-edge research and industry applications, this journal plays a vital role in disseminating knowledge and facilitating advancements in the food science and technology sector.
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