Untargeted Screening in a Case Control Study Using Apples as a Matrix

被引：3

作者：

Bakota, Erica L. ^{[1
]}

Levine, Robert A. ^{[1
]}

机构：

[1] US FDA, Kansas City Lab, Lenexa, KS 66214 USA

来源：

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY | 2020年 / 68卷 / 37期

关键词：

untargeted screening; high resolution mass spectrometry; total diet study; apples; bioinformatics; metabolomics; Compound Discoverer; PESTICIDE-RESIDUES; MASS-SPECTROMETRY; DIETARY EXPOSURE; FOOD; METABOLOMICS; CONTAMINANTS; METABOLITES; ADULTERANTS; JUICE;

D O I：

10.1021/acs.jafc.0c02704

中图分类号：

S [农业科学];

学科分类号：

09 ;

摘要：

Untargeted screening using high resolution mass spectrometry (HRMS) is a promising approach for screening the food supply for contaminants, but the sheer amount of information inherent to the HRMS data set presents analytical challenges. Red apples, collected during the U.S. FDA's Total Diet Study, were studied to determine whether bioinformatic software can be used to distinguish spiked model compounds from those native to apples. A workflow was created, in which initial data sets of over 44,000 features in each of the two spiked samples were reduced by several orders of magnitude to a scale suitable for visual inspection. After visual inspection to address degeneracy and data quality, the final data sets contained 30 and 2 suspect compounds, respectively. To the best of our knowledge, this is the largest scale case-control study on food matrices to date and the first use of market basket samples as references in an untargeted screening study.

引用

页码：10232 / 10246

页数：15

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