Food Phenotyping: Recording and Processing of Non-Targeted Liquid Chromatography Mass Spectrometry Data for Verifying Food Authenticity

被引:11
|
作者
Creydt, Marina [1 ,2 ]
Fischer, Markus [1 ,2 ]
机构
[1] Univ Hamburg, Hamburg Sch Food Sci, Inst Food Chem, Grindelallee 117, D-20146 Hamburg, Germany
[2] Univ Hamburg, Ctr Hybrid Nanostruct CHyN, Dept Phys, Luruper Chaussee 149, D-22761 Hamburg, Germany
来源
MOLECULES | 2020年 / 25卷 / 17期
关键词
metabolomics; non-targeted; mass spectrometry; food fraud; food authenticity; data preprocessing; multivariate methods; chemometrics; metabolite identification; pathway analysis; MINIMUM REPORTING STANDARDS; HAZELNUTS CORYLUS-AVELLANA; LC-MS; METABOLOMICS DATA; PEAK DETECTION; GEOGRAPHICAL ORIGIN; MULTIVARIATE-ANALYSIS; PLANT METABOLOMICS; CROSS-VALIDATION; QUALITY-CONTROL;
D O I
10.3390/molecules25173972
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Experiments based on metabolomics represent powerful approaches to the experimental verification of the integrity of food. In particular, high-resolution non-targeted analyses, which are carried out by means of liquid chromatography-mass spectrometry systems (LC-MS), offer a variety of options. However, an enormous amount of data is recorded, which must be processed in a correspondingly complex manner. The evaluation of LC-MS based non-targeted data is not entirely trivial and a wide variety of strategies have been developed that can be used in this regard. In this paper, an overview of the mandatory steps regarding data acquisition is given first, followed by a presentation of the required preprocessing steps for data evaluation. Then some multivariate analysis methods are discussed, which have proven to be particularly suitable in this context in recent years. The publication closes with information on the identification of marker compounds.
引用
收藏
页数:36
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