Quantitative assessment of zearalenone in maize using multivariate algorithms coupled to Raman spectroscopy

文献类型： 外文期刊

第一作者： Guo, Zhiming

作者： Guo, Zhiming;Wang, Mingming;Chen, Quansheng;Ouyang, Qin;Shi, Jiyong;Zou, Xiaobo;Wu, Jingzhu;Tao, Feifei;Wang, Qingyan;Shi, Jiyong;Zou, Xiaobo

作者机构：

关键词： Food safety; Raman spectroscopy; Zearalenone; Chemometrics; Quantitative determination; Ant colony optimization

期刊名称：FOOD CHEMISTRY （ 影响因子：7.514； 五年影响因子：7.516 ）

ISSN： 0308-8146

年卷期： 2019 年 286 卷

页码：

收录情况： SCI

摘要： Zearalenone is a contaminant in food and feed products which are hazardous to humans and animals. This study explored the feasibility of the Raman rapid screening technique for zearalenone in contaminated maize. For representative Raman spectra acquisition, the ground maize samples were collected by extended sample area to avoid the adverse effect of heterogeneous component. Regression models were built with partial least squares (PLS) and compared with those built with other variable selection algorithms such as synergy interval PLS (siPLS), ant colony optimization PLS (ACO-PLS) and siPLS-ACO. SiPLS-ACO algorithm was superior to others in terms of predictive power performance for zearalenone analysis. The best model based on siPLS-ACO achieved coefficients of correlation (R-p) of 0.9260 and RMSEP of 87.9132 mu g/kg in the prediction set, respectively. Raman spectroscopy combined multivariate calibration showed promising results for the rapid screening large numbers of zearalenone maize contaminations in bulk quantities without sample-extraction steps.

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