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利用元素标记和多元分析对 sengcu 米进行地理起源追溯。

Geographical origin traceability of Sengcu rice using elemental markers and multivariate analysis.

机构信息

Center for Research and Technology Transfer, Vietnam Academy of Science and Technology, Ha Noi, Vietnam.

Department of Analytical Chemistry, Faculty of Chemistry, Viet Tri University of Industry, Phu Tho, Vietnam.

出版信息

Food Addit Contam Part B Surveill. 2022 Sep;15(3):177-190. doi: 10.1080/19393210.2022.2070932. Epub 2022 Jun 19.

Abstract

Multi-element analysis combined with chemometric method has been used to investigate the distinguish between Sengcu rice and other types of rice origins in Vietnam. In Sengcu rice, As, Ba Sr, Pb, Ca, Se were confirmed as the key elements for geographical traceability among three fields of Lao Cai, whereas Al, Ca, Fe, Mg, Ag, As were major factors to distinguish between Sengcu and other types of rice. Based on linear discriminant analysis and partial least squares-discriminant analysis model, overall correct identification rates distinguishing between Sengcu and other types of rice were approximately 100% in both training and validation test. Moreover, to distinguish geographical origin of Sengcu rice samples, these rates vary from 80% to 99%. These results suggest the presence of food adulteration illustrated in the latter.

摘要

多元分析结合化学计量学方法已被用于研究区分越南三省种植的森谷稻与其他类型大米的产地。在森谷稻中,砷、钡、锶、铅、钙、硒被确认为在老挝、莱州和山罗三省产地间进行地理溯源的关键元素,而铝、钙、铁、镁、银、砷则是区分森谷稻与其他类型大米的主要因素。基于线性判别分析和偏最小二乘判别分析模型,在训练和验证测试中,区分森谷稻与其他类型大米的总体正确识别率均接近 100%。此外,要区分森谷稻样品的产地,这些比率从 80%到 99%不等。这些结果表明存在食品掺假的情况,后文将对此进行说明。

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