文献类型： 外文期刊

第一作者： Wu Wei

作者： Wu Wei;Zu Guang-peng;Chen Gui-yun;Chen Kun-jie;Xu Jian-hong

作者机构：

关键词： Deoxynivalenol; Trend parameters; Quadratic discriminant analysis; Wheat flour

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2020 年 40 卷 5 期

页码：

收录情况： SCI

摘要： Deoxynivalenol (DON) is a mycotoxin that often occurs in cereals and their derivatives. It is harmful to the life and health of human and livestock. It is urgent to develop a detection method, which can rapidly, accurately and economically detect DON without environmental hazard. This study defined a Trend Parameter (TP) of the visible-near-infrared (VIS-NIR) spectra. The TP was used to determine the characteristic bands which were most relevant to the DON concentration. In this paper, the rows of spectral matrix of the samples in calibration set were arranged in the order of gradual increase in DON concentration. Each column (each band) of the matrix corresponded to a TP value. Under a certain band, the stronger the increasing trend of the absorbances of all samples in the column direction is (ie, the larger the TP value), the stronger the correlation between the absorbance and the DON concentration in this band is, and this band can be used as a characteristic band for evaluating the DON concentration. The study found that the local maximum of TP appeared at 666, 1 238, and 1 660 nm. The quadratic discriminant analysis (QDA) was performed by the spectra of the three characteristic bands. The wheat flour can be divided into three grades : mild (0 DON<1 000 mu g . kg(-1)), moderate (1 000 DON<2 000 mu g . kg(-1)), and severe (DON >= 2 000 mu g . kg(-1)) pollution by the constructed TP-QDA model. The overall classification accuracy of the model was respectively 88. 24% and 86. 27% in the calibration set and verification set. The Principal Component Analysis (PCA) of characteristic bands selection was used to make a comparison. The PCA-QDA model divided the same wheat sample into three pollution levels. The overall classification accuracy rate was 68. 62% in the calibration set and 72. 55% in the verification one. These findings confirmed that the selection of characteristic bands by TP parameter is superior to the one by the PCA in judging DON pollution level, and the TP-QDA model can be effectively used to quickly classify the pollution level of wheat flour, thereby reducing the time and economic cost of analyzing and screening wheat during the process of acquisition, storage and transport. The results of this study have yet to be tested for universality in a wider range of wheat varieties.

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