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Updated: Dec 18, 2025
Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
Published on: May 20, 2013
Integrating untargeted metabolomics and targeted analysis for not from concentrate and from concentrate orange juices
Lei Xu1, Zhenzhen Xu2, Simon Kelly3
1Institute of Quality Standard & Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-food Safety and Quality, Ministry of Agriculture and Rural Affairs, Beijing 100081, China; College of Food Science and Nutritional Engineering, China Agricultural University, Beijing Key Laboratory for Food Nonthermal Processing, Key Lab of Fruit and Vegetable Processing, Ministry of Agriculture and Rural Affairs, Beijing 100083, China.
Abstract:
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.
