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基于 HRMS 代谢组学的哥伦比亚咖啡原产地保护评估。

Assessment of protected designation of origin for Colombian coffees based on HRMS-based metabolomics.

机构信息

GDCON Research Group, Faculty of Engineering, University Research Headquarters (SIU), University of Antioquia, Street 70 # 52 - 21, Medellin, Colombia.

Research Institute for Pesticides and Water (IUPA), Avda. Sos Baynat, s/n. University Jaume I, 12071 Castellón, Spain.

出版信息

Food Chem. 2018 Jun 1;250:89-97. doi: 10.1016/j.foodchem.2018.01.038. Epub 2018 Jan 4.

Abstract

An untargeted metabolomics approach based on HRMS has been applied to Colombian green coffee to develop a discrimination model to highlight the most differential compounds. For this purpose, 41 green coffee samples of different genotypes collected from 5 regions were analysed. Samples were extracted with aqueous and organic solvents to cover a wide range of compounds. Sample extracts were randomly injected and data were pre-processed with XCMS software. PCA was used to verify quality control samples behaviour, and PLS-DA and DD-SIMCA were employed to create models for discrimination using VIP variable selection method. Thirteen different compounds correctly separate green coffee samples according to their origin, several related to the quality and health benefits of coffee. Model validation was achieved using both cross-validation and an additional set with coffee samples from different harvest year. The results reveal that UHPLC-(Q)ToF MS-based metabolomics is a suitable tool to develop food origin discrimination strategies.

摘要

基于高分辨质谱的非靶向代谢组学方法已被应用于哥伦比亚绿咖啡豆,以开发一种区分模型来突出最具差异的化合物。为此,对来自 5 个地区的 41 个不同基因型的绿咖啡豆样本进行了分析。样本用不同的水相和有机相溶剂提取,以覆盖广泛的化合物范围。随机注入样本提取物,并使用 XCMS 软件进行数据预处理。PCA 用于验证质控样品的行为,PLS-DA 和 DD-SIMCA 用于使用 VIP 变量选择方法创建用于区分的模型。根据其来源,13 种不同的化合物可以正确区分绿咖啡豆样本,其中一些与咖啡的质量和健康益处有关。使用交叉验证和来自不同收获年份的咖啡样本的额外数据集对模型进行验证。结果表明,基于 UHPLC-(Q)ToF MS 的代谢组学是开发食品起源区分策略的合适工具。

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