Spatio-temporal distribution patterns and quantitative detection of aflatoxin B1 and total aflatoxin in peanut kernels explored by short-wave infrared hyperspectral imaging

Guo, Zhen; Zhang, Jing; Dong, Haowei; Sun, Jiashuai; Huang, Jingcheng; Li, Shiling; Guo, Yemin; Sun, Xia

doi:10.1016/j.foodchem.2023.136441

Cited by 8 publications

(1 citation statement)

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“…One significant challenge is the difficulty in distinguishing adulterated products when the addition of colorants results in color values similar to those of authentic products. From this perspective, HSI, especially SWIR-based HSI, is a useful alternative to overcome the above limitations since it provides detailed information about several compounds in food [ 21 ]. Therefore, this study used SWIR technology to identify adulterated red pepper powder.…”

Section: Resultsmentioning

confidence: 99%

Detection of Red Pepper Powder Adulteration with Allura Red and Red Pepper Seeds Using Hyperspectral Imaging

Park,

Cho,

Lee

et al. 2023

Foods

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This study used shortwave infrared (SWIR) technology to determine whether red pepper powder was artificially adulterated with Allura Red and red pepper seeds. First, the ratio of red pepper pericarp to seed was adjusted to 100:0 (P100), 75:25 (P75), 50:50 (P50), 25:75 (P25), or 0:100 (P0), and Allura Red was added to the red pepper pericarp/seed mixture at 0.05% (A), 0.1% (B), and 0.15% (C). The results of principal component analysis (PCA) using the L, a, and b values; hue angle; and chroma showed that the pure pericarp powder (P100) was not easily distinguished from some adulterated samples (P50A-C, P75A-C, and P100B,C). Adulterated red pepper powder was detected by applying machine learning techniques, including linear discriminant analysis (LDA), linear support vector machine (LSVM), and k-nearest neighbor (KNN), based on spectra obtained from SWIR (1,000–1,700 nm). Linear discriminant analysis determined adulteration with 100% accuracy when the samples were divided into four categories (acceptable, adulterated by Allura Red, adulterated by seeds, and adulterated by seeds and Allura Red). The application of SWIR technology and machine learning detects adulteration with Allura Red and seeds in red pepper powder.

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Section: Resultsmentioning

confidence: 99%