Calibration and testing of a Raman hyperspectral imaging system to reveal powdered food adulteration

Abstract

The potential adulteration of foodstuffs has led to increasing concern regarding food safety and security, in particular for powdered food products where cheap ground materials or hazardous chemicals can be added to increase the quantity of powder or to obtain the desired aesthetic quality. Due to the resulting potential health threat to consumers, the development of a fast, label-free, and non-invasive technique for the detection of adulteration over a wide range of food products is necessary. We therefore report the development of a rapid Raman hyperspectral imaging technique for the detection of food adulteration and for authenticity analysis. The Raman hyperspectral imaging system comprises of a custom designed laser illumination system, sensing module, and a software interface. Laser illumination system generates a 785 nm laser line of high power, and the Gaussian like intensity distribution of laser beam is shaped by incorporating an engineered diffuser. The sensing module utilize Rayleigh filters, imaging spectrometer, and detector for collection of the Raman scattering signals along the laser line. A custom-built software to acquire Raman hyperspectral images which also facilitate the real time visualization of Raman chemical images of scanned samples. The developed system was employed for the simultaneous detection of Sudan dye and Congo red dye adulteration in paprika powder, and benzoyl peroxide and alloxan monohydrate adulteration in wheat flour at six different concentrations (w/w) from 0.05 to 1%. The collected Raman imaging data of the adulterated samples were analyzed to visualize and detect the adulterant concentrations by generating a binary image for each individual adulterant material. The results obtained based on the Raman chemical images of adulterants showed a strong correlation (R>0.98) between added and pixel based calculated concentration of adulterant materials. This developed Raman imaging system thus, can be considered as a powerful analytical technique for the quality and authenticity analysis of food products.

Fig 1

Optical design of line-scan RHSI system (The laser light to sample in red and scattered light from the sample in green color) (a), and photograph of a system used to acquire images from layered and mixed food powder samples (b).

Fig 2. Software interface for image acquisition and system control.

Fig 3. Spectral calibration for the Raman imaging system using a quadratic regression model.

Fig 4

Schematic of sample holder for effective penetration depth determination of laser line through food powders (a), and mean Raman spectra of wheat flour of four different thickness over the adulterant material benzoyl peroxide (b).

Fig 5

Fluorescence corrected Raman spectra of pure food powder (wheat flour (a), and paprika powder (b)) samples and adulterant materials.

Fig 6

Raman images of 0.5% adulterated wheat flour: Images of selected wavebands for benzoyl peroxide (a) and alloxan monohydrate(b); (c) and (d) are preprocessed images of (a) and (b), respectively; (e) and (f) are binary images of (c) and (d), respectively.

Fig 7. Preprocessed Raman images of a 1% adulterated paprika powder at selected bands of the adulterants and band summation images.

Fig 8. Combined color coded chemical images of benzoyl peroxide (red) and alloxan monohydrate (yellow) in wheat flour (blue background) with six different concentrations and two replications.

Fig 9. Combined color coded chemical images of Sudan dye (red) and Congo red dye (yellow) in paprika powder (blue background) with six different concentrations and two replications.

Fig 10

Linear relationship between the pixel based calculated concentrations corrected with the ratio of densities and added mass concentration of each adulterant in wheat flour (a) and paprika powder (b).