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Near-infrared hyperspectral imaging for detection and quantification of azodicarbonamide in flour

TitleNear-infrared hyperspectral imaging for detection and quantification of azodicarbonamide in flour
Publication TypeJournal Article
Year of Publication2018
AuthorsWang, X, Zhao, C, Huang, W, Wang, Q, Liu, C, Yang, G
JournalJ Sci Food Agric
Date PublishedMay
ISBN Number0022-5142
Accession Number29124771
KeywordsAlgorithms, Azo Compounds/*analysis, azodicarbonamide, Bleaching Agents/*analysis, flour, Flour/*analysis, near-infrared hyperspectral imaging, quantitative analysis, Spectroscopy, Near-Infrared/*methods, visual identification

BACKGROUND: The present study aimed to establish a method for the detection and quantification of azodicarbonamide (ADC) in flour using hyperspectral imaging technology. Hyperspectral images of pure flour, pure ADC and flour-ADC mixtures with different concentrations of ADC were collected. F-values of one-way analysis of variance for all possible wavebands within the spectra of the flour and ADC were calculated, and the maximum value indicated that the two wavebands have more significant differences, i.e. the optimal two wavebands. Threshold segmentation was used for band ratio images of two wavebands to create a binary image. This allowed visual identification of ADC-rich pixels in the mixtures. RESULTS: The two wavebands with the largest difference between flour and ADC were 2039 nm and 1892 nm. Using the binary image construction method, different concentrations of ADC in flour were identified. The minimum detected concentration was 0.2 g kg(-1) . In the mixtures, the number of ADC-rich pixels detected had a good linear relationship with the ADC concentrations, with a correlation coefficient of 0.9845. CONCLUSION: This study indicated that the band ratio algorithm combination with threshold segmentation for hyperspectral images provides a non-destructive method for detecting and quantifying of ADC in flour. (c) 2017 Society of Chemical Industry.