A rapid and reliable method for discriminating rice products from different regions using MCX-based solid-phase extraction and DI-MS/MS-based metabolomics approach

Dong Kyu Lim, Changyeun Mo, Nguyen Phuoc Long, Jongguk Lim, Sung Won Kwon

Research output: Contribution to journalArticle

1 Scopus citations


The expansion of the global rice marketplace ultimately raises concerns about authenticity control. Several analytical methods for differentiating the geographical origin of rice have been developed, yet a high-throughput method is still in demand. In this study, we developed a rapid approach using direct infusion-mass spectrometry (DI-MS) to distinguish rice products from different countries. Specifically, the elimination of the matrix effect by a polytetrafluoroethylene (PTFE) filter, a mixed-mode cation exchange (MCX) solid-phase extraction (SPE) with 20% methanol, and an MCX SPE with 100% methanol were measured. Afterward, partial least squares discriminant analysis and random forests were applied to seek the optimal discrimination method. The results revealed that the combination of MCX SPE with 100% methanol and DI-MS in positive ion mode (accuracy = 1.000, R2 = 0.916, Q2 = 0.720, B/W-based p-value = 0.015) or the combination of MCX SPE with 20% methanol and targeted DI-MS/MS in positive ion mode (accuracy = 1.000, R2 = 0.931, Q2 = 0.849, B/W-based p-value = 0.002) showed the excellent discriminatory ability. Furthermore, differentially expressed metabolites including sodiated lysophosphatidylcholine, lysophosphatidylcholine, lysophosphatidylethanolamines and lysophosphatidylglycerol classes were found. In conclusion, our study provides a rapid and reliable platform for geographical discrimination of white rice and will contribute to the authenticity control of rice products.

Original languageEnglish (US)
Pages (from-to)185-192
Number of pages8
JournalJournal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences
StatePublished - Sep 1 2017



  • Biomarker
  • Direct infusion mass spectrometry
  • Oryza sativa L
  • Partial least squares discriminant analysis
  • Phospholipid
  • Random forests

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Clinical Biochemistry
  • Cell Biology

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