Qualitative and quantitative detection of aflatoxins B1 in maize kernels with fluorescence hyperspectral imaging based on the combination method of boosting and stacking
文献类型： 外文期刊
作者： Wang, Zheli 1 ; An, Ting 2 ; Wang, Wenchao 2 ; Fan, Shuxiang 2 ; Chen, Liping 1 ; Tian, Xi 2 ;
作者机构： 1.China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
2.Beijing Acad Agr & Forestry Sci, Res Ctr Intelligent Equipment, Beijing 100097, Peoples R China
关键词： Maize kernels; Fluorescence hyperspectral imaging; Aflatoxins B1; Imbalanced data
期刊名称：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY （ 影响因子：4.4； 五年影响因子：3.9 ）
ISSN： 1386-1425
年卷期： 2023 年 296 卷
页码：
收录情况： SCI
摘要： The most widespread, toxic, and harmful toxin is aflatoxins B1 (AFB1). The fluorescence hyperspectral imaging (HSI) system was employed for AFB1 detection in this study. This study developed the under sampling stacking (USS) algorithm for imbalanced data. The results indicated that the USS method combined with ANOVA for featured wavelength achieved the best performance with the accuracy of 0.98 for 20 or 50 & mu;g /kg threshold using endosperm side spectra. As for the quantitative analysis, a specified function was used to compress AFB1 content, and the combination of boosting and stacking was used for regression. The support vector regression (SVR)Boosting, Adaptive Boosting (AdaBoost), and extremely randomized trees (Extra-Trees)-Boosting were used as the base learner, while the K nearest neighbors (KNN) algorithm was used as the meta learner could obtain the best results, with the correlation coefficient of prediction (Rp) was 0.86. These results provided the basis for developing AFB1 detection and estimation technologies.
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