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Cited 24 time in webofscience Cited 25 time in scopus
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Quantitative detection of benzoyl peroxide in wheat flour using line-scan short-wave infrared hyperspectral imaging

Authors
Kim, GeonwooLee, HoonsooBaek, InsuckCho, Byoung-KwanKim, Moon S.
Issue Date
1-Feb-2022
Publisher
Elsevier BV
Keywords
Food safety; Wheat flour; Benzol peroxide; Partial least square regression; SWIR spectroscopy; Hyperspectral imaging
Citation
Sensors and Actuators, B: Chemical, v.352
Indexed
SCIE
SCOPUS
Journal Title
Sensors and Actuators, B: Chemical
Volume
352
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/1634
DOI
10.1016/j.snb.2021.130997
ISSN
0925-4005
0925-4005
Abstract
The addition of benzol peroxide (BPO) to wheat flour as a bleaching agent has been widely recognized as an important food safety issue due to its negative effects on human health. To address this issue, various nondestructive optical-based techniques have been developed to screen for BPO, such as Raman spectroscopy and hyperspectral imaging (HSI). In this study, a shortwave infrared (SWIR) HSI system was developed for the rapid detection of BPO particles in wheat flour. The SWIR HSI system, detailed hyperspectral image processing procedures, and optimal model to detect BPO particles were evaluated. The model was developed using the partial least square regression (PLSR) method. To improve performance of the model, effective wavelength regions were selected, and various pre-processing methods were applied to the PLSR analysis. The developed model was able to detect BPO in wheat flour at 50-6400 ppm with a high determinant coefficient (> 0.985) between predicted and actual values. The developed SWIR HIS system and optimized model demonstrated a high potential for discriminating BPO particles in wheat flour and allowed for its quantitative evaluation.
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농업생명과학대학 (생물산업기계공학과)
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