Detection of Chemical Additives in Food Using Raman Chemical Imaging System†

doi:10.7503/cjcu20160640

Abstract

Abstract:

Raman chemical imaging applies the advantages of Raman spectroscopy to an imaging approach for screening large samples, allowing the presence and distribution of adulterants within a food material to be visualised. The potential of Raman chemical imaging technology for simultaneously detecting benzoyl peroxide(BPO) and L-ascorbic acid(LAA) in wheat flour powder was investigated. A line-scan Raman imaging system consists of a 785 nm laser, a fiber optic probe, a dispersive imaging spectrometer, a spectroscopic CCD camera, and a two-axis positioning table. This system acquired hyperspectral images in the effective spectral range of 0 to 2885.7 cm^-1. BPO and LAA were mixed into wheat flour powder in the concentration range of 0.1%—30% for each adulterant. The quantitative models were established to predict the content of BPO and LAA in wheat flour. The average spectrum of region of interest was used as Raman signal of the sample. The intensity of the Raman signal depends on the BPO and LAA content of wheat flour. The peak intensity of BPO at 1001, 1777 cm^-1 and LAA at 630, 1656 cm^-1 can be used for monitoring the additive levels. Linear regression models were established with the correlation coefficient(R²) of 0.9828 and 0.9912 for BPO and LAA, respectively. The adaptive iteratively reweighted Penalized Least Squares(airPLS) correction method can remove fluorescence background signals from the wheat flour powder. Single-band corrected images at unique Raman peaks identified for BPO and LAA can be used to create images for each adulterant using a simple thresholding method. The binary images of the two adulterants can be combined to create chemical images including both BPO and LAA, in which identification, spatial distribution, and morphological features of the two adulterant particles can be visualized in the background of the wheat flour powder. The high-throughput Raman chemical imaging method can be extended to authenticate other powdered foods and ingredients adulterated with Raman-active chemicals.

Key words: Raman chemical imaging, Wheat flour, Benzoyl peroxide, L-Ascorbic acid, Distributed visual

CLC Number:

O657.37

TrendMD:

ZHAI Chen, PENG Yankun, LI Yongyu, ZHAO Juan. Detection of Chemical Additives in Food Using Raman Chemical Imaging System^†[J]. Chem. J. Chinese Universities, 2017, 38(3): 369.

Figures/Tables 7

Fig.1 Raman spectra of wheat flour(a), L-ascorbic acid(b) and benzoyl peroxide(c)

Fig.2 Raw(A) and corrected(B) Raman spectra of wheat flour with different contents of BPO

Fig.3 Prediction results for BPO(A) and LAA(B) content between the predicted values and reference values

Fig.4 Raman images(A, D), corrected Raman images(B, E) and binary images(C, F) of wheat flour with 30% content of BPO at 1001 cm-1(A—C) and 30% content of LAA at 630 cm-1(D—F)

Fig.5 Binary images of wheat flour with 10%, 1%, 0.5% and 0.1% content of BPO(A1—A4) and LAA(B1—B4), respectively

Fig.6 Raw Raman spectra of wheat flour with different contents of BPO and LAA

Fig.7 Binary images of wheat flour with 1%(A) and 0.1%(B) content of BPO and LAA

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