通过非靶向 LC-MS 分析发现蓝莓蜂蜜真实性标记的快速卷积算法。

IF 6.7 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Analytical Chemistry Pub Date : 2024-11-12 Epub Date: 2024-10-31 DOI:10.1021/acs.analchem.4c01778
Shawninder Chahal, Lei Tian, Shaghig Bilamjian, Ferenc Balogh, Lorna De Leoz, Tarun Anumol, Daniel Cuthbertson, Stéphane Bayen
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引用次数: 0

摘要

蜜蜂通过采集和转化花蜜来生产蜂蜜,而花蜜的植物来源会影响蜂蜜的味道和营养价值,从而影响蜂蜜的市场价格。这种现象导致一些人给蜂蜜贴上错误的标签,以便以更高的价格出售。代谢组学在食品鉴定中越来越受欢迎,但需要快速的数据挖掘算法来帮助发现新的真实性标记。本研究对 262 份单花蜂蜜样品(其中 50 份为蓝莓蜂蜜)进行了非靶向高分辨液相色谱-质谱(HR/LC-MS)分析。数据挖掘方法用于发现二元单一标记物(仅在蓝莓蜂蜜中检测到化合物)、阈值单一标记物(蓝莓蜂蜜中化合物浓度最高)和区间比率标记物(蓝莓蜂蜜中两种化合物的比率在一个独特的区间内)。为发现区间比率标记开发了一种新的卷积算法,该算法的训练速度比现有开源算法快 14 倍,分类得分比现有开源算法高 0.2 个马修斯相关系数(MCC)单位。卷积算法的分类性能也与暴力搜索类似,但训练速度快 1521 倍。此外,还展示了一种从 LC-MS 图谱中筛选出可能适合化学结构鉴定的候选真实性标记的方法,并将烟酸鉴定为蓝莓蜂蜜阈值单一标记。这项工作展示了一种从蜂蜜代谢组中挖掘新型真实性标记的端到端方法,并可随时应用于其他类型的食品和分析化学仪器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Rapid Convolutional Algorithm for the Discovery of Blueberry Honey Authenticity Markers via Nontargeted LC-MS Analysis.

Rapid Convolutional Algorithm for the Discovery of Blueberry Honey Authenticity Markers via Nontargeted LC-MS Analysis.

Bees produce honey through the collection and transformation of nectar, whose botanical origin impacts the taste, nutritional value, and, therefore, the market price of the resulting honey. This phenomenon has led some to mislabel their honey so that it can be sold at a higher price. Metabolomics has been gaining popularity in food authentication, but rapid data mining algorithms are needed to facilitate the discovery of new authenticity markers. A nontargeted high-resolution liquid chromatography-mass spectrometry (HR/LC-MS) analysis of 262 monofloral honey samples, of which 50 were blueberry honey, was performed. Data mining methods were demonstrated for the discovery of binary single-markers (compound was only detected in blueberry honey), threshold single-markers (compound had the highest concentration in blueberry honey), and interval ratio-markers (the ratio of two compounds was within a unique interval in blueberry honey). A novel convolutional algorithm was developed for the discovery of interval ratio-markers, which trained 14× faster and achieved a 0.2 Matthews correlation coefficient (MCC) units higher classification score than existing open-source implementations. The convolutional algorithm also had classification performance similar to that of a brute-force search but trained 1521× faster. A pipeline for shortlisting candidate authenticity markers from the LC-MS spectra that may be suitable for chemical structure identification was also demonstrated and led to the identification of niacin as a blueberry honey threshold single-marker. This work demonstrates an end-to-end approach to mine the honey metabolome for novel authenticity markers and can readily be applied to other types of food and analytical chemistry instruments.

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来源期刊
Analytical Chemistry
Analytical Chemistry 化学-分析化学
CiteScore
12.10
自引率
12.20%
发文量
1949
审稿时长
1.4 months
期刊介绍: Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.
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