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

被引:78
作者
Ch, Ratnasekhar [1 ,2 ]
Chevallier, Olivier [1 ,2 ]
McCarron, Philip [1 ,2 ]
McGrath, Terence F. [1 ,2 ]
Wu, Di [3 ]
Le Nguyen Doan Duy [4 ]
Kapil, Arun P. [5 ]
McBride, Mary [6 ]
Elliott, Christopher T. [1 ,2 ]
机构
[1] Queens Univ Belfast, Sch Biol Sci, Inst Global Food Secur, Belfast BT9 5DL, Antrim, North Ireland
[2] Queens Univ Belfast, ASSET Lab, Belfast BT9 5DL, Antrim, North Ireland
[3] Tsinghua Univ, Yangtze Delta Reg Inst, Jiaxing, Zhejiang, Peoples R China
[4] Ho Chi Minh City Univ Technol, VNU HCM HCMUT, Ho Chi Minh City, Vietnam
[5] Green Saffron Spices Ltd, Cork, Ireland
[6] Agilent Technol, Santa Clara, CA USA
基金
中国国家自然科学基金;
关键词
Rice; Rice fraud; VOC metabolome; HS-GC-MS; Geographical origin; Metabolomics; QUALITY;
D O I
10.1016/j.foodchem.2020.127553
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
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 (R-2 = 0.98182, Q(2) = 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.
引用
收藏
页数:9
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