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• W4285992168 abstract "Aflatoxins are among the most carcinogenic mycotoxins and are considered as the most problematic mycotoxins in U.S. agriculture. The innovative technologies that can offer high-throughput detection, advantages of rapidness and non-destructiveness are urgently needed. One such technology using the near-infrared hyperspectral imaging between 900 and 2500 nm was employed to distinguish aflatoxin contamination in corn kernels. Nine hundred kernels were used with 3 treatments, namely, each 300 kernels inoculated with the aflatoxigenic AF13 fungus, non-aflatoxigenic AF36 fungus, and sterile distilled water. One hundred kernels from each treatment group were subjected to incubation for 3, 5 and 8 days, dried and wiped to remove exterior fungus, and imaged. The reference aflatoxin concentration in each kernel was determined by the VICAM AflaTest method. The full spectral partial least-squares discriminant analysis (PLS-DA) results show that the models established upon the standard normal variate-preprocessed germ-side absorbance generally performed better. The models with different training sample size ratios in terms of aflatoxin-negative: -positive class, indicate that the 2:1 ratio achieved more balanced prediction performance. With the 20-ppb and 100-ppb thresholds, the type II- competitive adaptive reweighted sampling (CARS)-PLSDA models established upon the 17 and 21 commonly selected variables, under the conditions of “frequency ≥ 70” and “frequency ≥ 60” respectively in 100 random runs, achieved comparable prediction capability to the full spectral and type I-CARS-PLSDA models. The mean prediction accuracies of the aflatoxin-negative, -positive class and overall accuracy of the type II-CARS-PLSDA models, were 90.4%, 81.1% and 89.8%, and 89.7%, 82.8% and 89.3% using the 20-ppb and 100-ppb thresholds." @default.
• W4285992168 created "2022-07-21" @default.
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• W4285992168 date "2022-09-01" @default.
• W4285992168 modified "2023-09-30" @default.
• W4285992168 title "Near-infrared hyperspectral imaging for evaluation of aflatoxin contamination in corn kernels" @default.
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• W4285992168 doi "https://doi.org/10.1016/j.biosystemseng.2022.07.002" @default.
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