可追溯性
线性判别分析
化学计量学
偏最小二乘回归
多元统计
同位素分析
数学
统计
稳定同位素比值
计算机科学
生物
机器学习
生态学
量子力学
物理
作者
Zhi Liu,Wei Yuan,Hao Yudi,Wei Liu,Бин Ли,Guiyuan Meng
出处
期刊:Food Chemistry
[Elsevier BV]
日期:2023-01-06
卷期号:412: 135417-135417
被引量:17
标识
DOI:10.1016/j.foodchem.2023.135417
摘要
Stable isotope and multi-element analytical techniques with chemometrics were developed to trace the origin authenticity of rice in China market. In the long-term study from 2017 to 2020, a total of 115 batches of rice samples from 8 main producing areas of 7 Asian countries were determined 5 stable isotope ratios and 18 elemental contents. One-way analysis of variance (ANOVA) and various multivariate modeling methods were performed for the origin discrimination. Supervised multivariate modeling including partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) can realize more satisfactory identification of 8 rice origins than ANOVA comparison and unsupervised methods, their leave-one-out cross-validation accuracies approach 85.0 % and 90.9 %, respectively. δ2H, δ13C, Ba, Al, Mg, δ34S, Pb and δ18O were screened as the most important variables for rice origin traceability (VIP > 1 or AUC > 0.5). This analytical strategy combining maybe promising to ensure the origin authenticity and combat illegal mislabeling in rice trade.
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