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Rice authentication: An overview of different analytical techniques combined with multivariate analysis

文献类型： 外文期刊

作者： Wadood, Syed Abdul 1 ; Nie, Jing 1 ; Li, Chunlin 1 ; Rogers, Karyne M. 1 ; Khan, Abbas 2 ; Khan, Wahab Ali 2 ; Qamar, Aiza 2 ; Zhang, Yongzhi 3 ; Yuwei, Yuan 1 ;

作者机构： 1.State Key Lab Managing Biot & Chem Threats Qual &, Hangzhou 310021, Peoples R China

2.Univ Home Econ Lahore, Dept Nutr & Hlth Promot, Lahore, Pakistan

3.Minist Agr & Rural Affairs China, Key Lab Informat Traceabil Agr Prod, Hangzhou 310021, Peoples R China

4.Zhejiang Acad Agr Sci, Inst Agroprod Safety & Nutr, Minist Agr & Rural Affairs China, Hangzhou 310021, Peoples R China

5.GNS Sci, Natl Isotope Ctr, 30 Gracefield Rd, Lower Hutt 5040, New Zealand

关键词： Rice authentication; Geographical origin; Organic rice; Multivariate analysis

期刊名称：JOURNAL OF FOOD COMPOSITION AND ANALYSIS （ 影响因子：4.52； 五年影响因子：4.942 ）

ISSN： 0889-1575

年卷期： 2022 年 112 卷

页码：

收录情况： SCI

摘要： The authenticity of rice has become an important issue over the last few years. Many techniques have been employed in rice authentication including geographical origin, cultivar discrimination, organic rice authenticity, and impurities detection in rice. This review paper is attempted to highlight the current literature (past twenty years) on the discrimination and authentication of rice using different analytical techniques coupled with multivariate analysis. In recent literature, IRMS and ICPMS provide effective information for geographical identification, cultivar discrimination as well as authenticity regarding farming methods (organic vs conventional) of rice samples. Similarly, spectroscopic methods showed great potential regarding cultivar discrimination and organic rice authenticity. DNA-based methods provide valuable insights in detecting adulteration and cultivar discrimination while omic analysis was very effective in detecting adulterants from rice samples. Regarding multivariate analysis, PCA and HCA, the most common unsupervised methods used to visualize and reduce large data matrices into fewer variables before data processing. In addition, ANN, KNN, LDA, PLS-DA, SIMCA, and SVM were the most common supervised techniques which were performed to process the data obtained from different analytical techniques for rice authentication.

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