Metabolomic fingerprinting of volatile organic compounds for the geographical discrimination of rice samples from China, Vietnam and India

Ratnasekhar Ch, Olivier Chevallier, Philip McCarron, Terence F McGrath, Di Wu, Le Nguyen Doan Duy, Arun P Kapil, Mary McBride, Christopher T Elliott

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Rice is one of the most important cereals for human nutrition and is a basic staple food for half of the global population. The assessment of rice geographical origins in terms of its authenticity is of great interest to protect consumers from misleading information and fraud. In the present study, a head space gas chromatography mass spectrometry (HS-GC-MS) strategy for characterising volatile organic compounds (VOCs) profiles to distinguish rice samples from China, India and Vietnam is described. Partial Least Square Discriminant Analysis (PLS-DA) model exhibited a good discrimination (R2 = 0.98182, Q2 = 0.9722, and Accuracy = 1.0) for rice samples from China, India and Vietnam. Moreover, Data-Driven Soft Independent Modelling of Class Analogy (DD-SIMCA) and K-nearest neighbors shown good specificity 100% and accuracy 100% in identifying the origin of samples. The present study established VOC fingerprinting as a highly efficient approach to identify the geographical origin of rice.

Original languageEnglish
Article number127553
Number of pages9
JournalFood Chemistry
Volume334
Early online date13 Jul 2020
DOIs
Publication statusPublished - 01 Jan 2021

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