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Integrating untargeted metabolomics and targeted analysis for not from concentrate and from concentrate orange juices discrimination and authentication

Journal 2020 · IF 6.306 · 发表于 2020 年 5 月 23 日
作者: Lei Xu,Zhenzhen Xu,Simon Kelly,Xiaojun Liao
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摘要

Untargeted metabolomics was used to investigate the differences between orange juices from concentrate or not. Although no distinctive separation could be observed from principal component analysis for all samples, student’s t -test, fold change, orthogonal projection to latent structures discriminant and detection rate analyses were conducted to find the latent potential markers. Subsequently, 91 and 42 potential markers were defined in positive/negative mode. Thirteen of them, l -glutamine, carvone, erucamide, lysoPE (16:0/0:0), oleic acid, α-linolenic acid and 7 tripeptides (reported for the first time in orange juice) were identified with standards. A partial least squares discriminant analysis model, based on the potential markers in positive mode by direct analysis in real time mass spectrometry-quadrupole time of flight (DART-QTOF) with 9 s acquisition time, was constructed and validated with 97% and 95% accuracy for training and test. The model was applied to commercial samples successfully, and an NFC brand was found highly suspicious.

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