期刊
APPLIED SCIENCES-BASEL
卷 8, 期 4, 页码 -出版社
MDPI
DOI: 10.3390/app8040564
关键词
Raman chemical image; 1064 nm; self-modeling mixture analysis; food safety; curry powder; azo dyes
Curry powder is extensively used in Southeast Asian dishes. It has been subject to adulteration by azo dyes. This study used a newly developed 1064 nm dispersive point-scan Raman system for detection of metanil yellow and Sudan-I contamination in curry powder. Curry powder was mixed with metanil yellow and (separately) with Sudan-I, at concentration levels of 1%, 3%, 5%, 7%, and 10% (w/w). Each sample was packed into a nickel-plated sample container (25 mm x 25 mm x 1 mm). One Raman spectral image of each sample was acquired across the 25 mm x 25 mm surface area. Intensity threshold value was applied to the spectral images of Sudan-I mixtures (at 1593 cm(-1)) and metanil yellow mixtures (at 1147 cm(-1)) to obtain binary detection images. The results show that the number of detected adulterant pixels is linearly correlated with the sample concentration (R-2 = 0.99). The Raman system was further used to obtain a Raman spectral image of a curry powder sample mixed together with Sudan-I and metanil yellow, with each contaminant at equal concentration of 5% (w/w). The multi-component spectra of the mixture sample were decomposed using self-modeling mixture analysis (SMA) to extract pure component spectra, which were then identified as matching those of Sudan-I and metanil yellow using spectral information divergence (SID) values. The results show that the 1064 nm dispersive Raman system is a potential tool for rapid and nondestructive detection of multiple chemical contaminants in the complex food matrix.
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