Authentication of premium Asian rice varieties: Stable isotope ratios and multi-elemental content for the identification of geographic fingerprints

文献类型： 外文期刊

第一作者： Giannioti, Zoe

作者： Giannioti, Zoe;Brigante, Federico Ivan;Tonon, Agostino;Ziller, Luca;Bontempo, Luana;Giannioti, Zoe;Brigante, Federico Ivan;Bontempo, Luana;Kelly, Simon;Ogrinc, Nives;Hudobivnik, Marta Jagodic;Mazej, Darja;Kukusamude, Chunyapuk;Kongsri, Supalak;Thantar, Saw;Widyastuti, Henni;Yuan, Yuwei

作者机构：

关键词： Food fraud; IRMS; ICP-MS; Data fusion; Multivariate analysis

期刊名称：LWT-FOOD SCIENCE AND TECHNOLOGY （ 影响因子：6.6； 五年影响因子：6.9 ）

ISSN： 0023-6438

年卷期： 2024 年 209 卷

页码：

收录情况： SCI

摘要： Over 90 percent of the world's rice is produced and consumed in the Asia-Pacific region. Varieties such as Thai Jasmine rice and Paw San (or "Myanmar pearl rice") are globally recognised as premium, while more local high-grade varieties include the Indonesian Ciherang and Inpari. Being able to trace the origin of these products has become necessary, since they are marketed at relatively higher prices compared to other cultivars, and they often become the target of fraudulent activities. In this work, we aimed to identify variables that could distinguish the premium-producing regions within each country, by Isotope Ratio Mass Spectrometry (IRMS) and Inductively Coupled Plasma- Mass Spectrometry (ICP-MS). Low-Level Data Fusion (LLDF) followed the analysis of more than 300 authentic samples, and (O)PLS-DA models yielded very high accuracy values. The most important geo-differentiating variables (VIP>1.4) were identified as: delta C-13, delta O-18, delta H-2, delta S-34, Co, Rb, Cu, Ba and Zn.

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