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探索高分辨 LC-MS 与离子淌度分离和替代最小深度相结合在增强杏仁产地鉴定中的潜力。

Exploring the potential of high-resolution LC-MS in combination with ion mobility separation and surrogate minimal depth for enhanced almond origin authentication.

机构信息

Hamburg School of Food Science - Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146, Hamburg, Germany.

Hamburg School of Food Science - Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146, Hamburg, Germany.

出版信息

Talanta. 2024 May 1;271:125598. doi: 10.1016/j.talanta.2023.125598. Epub 2023 Dec 28.

DOI:10.1016/j.talanta.2023.125598
PMID:38224656
Abstract

Almonds (Prunus dulcisMill.) are consumed worldwide and their geographical origin plays a crucial role in determining their market value. In the present study, a total of 250 almond reference samples from six countries (Australia, Spain, Iran, Italy, Morocco, and the USA) were non-polar extracted and analyzed by UPLC-ESI-IM-qToF-MS. Four harvest periods, more than 30 different varieties, including both sweet and bitter almonds, were considered in the method development. Principal component analysis showed that there are three groups of samples with similarities: Australia/USA, Spain/Italy and Iran/Morocco. For origin determination, a random forest achieved an accuracy of 88.8 %. Misclassifications occurred mainly between almonds from the USA and Australia, due to similar varieties and similar external influences such as climate conditions. Metabolites relevant for classification were selected using Surrogate Minimal Depth, with triacylglycerides containing oxidized, odd chained or short chained fatty acids and some phospholipids proven to be the most suitable marker substances. Our results show that focusing on the identified lipids (e. g., using a QqQ-MS instrument) is a promising approach to transfer the origin determination of almonds to routine analysis.

摘要

杏仁(Prunus dulcisMill.)在全球范围内被消费,其地理起源在决定其市场价值方面起着至关重要的作用。在本研究中,从六个国家(澳大利亚、西班牙、伊朗、意大利、摩洛哥和美国)共提取并分析了 250 份杏仁参考样本,采用 UPLC-ESI-IM-qToF-MS 非极性提取方法。该方法开发中考虑了四个收获期、30 多种不同品种,包括甜杏仁和苦杏仁。主成分分析表明,有三组样品具有相似性:澳大利亚/美国、西班牙/意大利和伊朗/摩洛哥。对于产地的确定,随机森林的准确率达到 88.8%。美国和澳大利亚的杏仁之间主要存在误分类,这是由于品种相似以及气候条件等类似的外部影响。使用替代最小深度选择与分类相关的代谢物,证明含有氧化、奇数链或短链脂肪酸的三酰基甘油和一些磷脂是最适合的标记物质。我们的结果表明,关注所鉴定的脂质(例如,使用 QqQ-MS 仪器)是将杏仁产地确定转移到常规分析的一种很有前途的方法。

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