Geographical origin modeling of Chinese rice using stable isotopes and trace elements

文献类型： 外文期刊

第一作者： Li, Chunlin

作者： Li, Chunlin;Nie, Jing;Zhang, Yongzhi;Shao, Shengzhi;Rogers, Karyne M.;Yuan, Yuwei;Zhang, Weixing;Li, Chunlin;Nie, Jing;Zhang, Yongzhi;Shao, Shengzhi;Rogers, Karyne M.;Yuan, Yuwei;Li, Chunlin;Nie, Jing;Zhang, Yongzhi;Shao, Shengzhi;Liu, Zhi;Yuan, Yuwei;Liu, Zhi;Rogers, Karyne M.

作者机构：

关键词： Rice (Oryza sativa L.); Authenticity; Geographical origin; Stable isotopes; Nutritional elements; Neural network modeling

期刊名称：FOOD CONTROL （ 影响因子：6.652； 五年影响因子：6.498 ）

ISSN： 0956-7135

年卷期： 2022 年 138 卷

页码：

收录情况： SCI

摘要： Rice is an important staple food in China, which authenticity is closely associated with nutrition and safety. It is necessary to discriminate their geographical origin with a comprehensive databank. 900 Japonica and Indica rice samples from 17 provinces were collected to analysis stable isotopes and trace elements for their origin discrimination of four regions as Middle-Lower Yangtze Plain (Y-R), northeast (N-E), southwest (S-W) and southeast (S-E). Results revealed Japonica rice was isotopically more positive than Indica rice, becoming -27.3 parts per thousand vs. -28.5 parts per thousand for delta C-13, 5.2 parts per thousand vs. 4.6 parts per thousand for delta N-15, -58.7 parts per thousand vs. -65.1 parts per thousand for delta H-2 and 20.3 parts per thousand vs. 18.1 parts per thousand for delta O-18 in Japonica vs. Indica rice, respectively. N-E rice had the most positive stable isotope values and Y-R rice had higher elemental contents. Using neural network modeling, Japonica rice from N-E and Y-R was discriminated with high accuracy of 97.2%. And Indica rice could also be geographically assigned to Y-R, S-W and S-E with the accuracy of 76.0% for blind samples. This study establishes the first comprehensive stable isotopic and elemental geographical database for Chinese rice and provides a promising discrimination method to key production regions in China.

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