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.

Improving Sensitivity in Raman Imaging for Thin Layered and Powdered Food Analysis Utilizing a Reflection Mirror

“…Most recently, Raman imaging on both the micro- and macroscale levels have been successfully tested for powdered food authenticity analysis [13,14,15,16,17,18,19]. Since a laser beam can penetrate a certain depth into a sample, the penetration depth was first determined to ensure that the adulterant particles at the very bottom of the sample could be detected [18,20].…”

Nontargeted Analytical Methods as a Powerful Tool for the Authentication of Spices and Herbs: A Review

“…Therefore, Lohumi et al. () showed that there is a linear correlation between the peaks obtained by Raman spectroscopy (785 nm) and the amount of the adulterants Sudan I ( R = 0.989) and Congo red ( R = 985) in paprika at concentrations between 0.05% and 1%. Bivariate analysis (two‐band image) compared to a single band image showed better results for the visualization and quantification of the adulterants Sudan I (1227 and 1493 cm −1 ) and Congo red (1351 and 1451 cm −1 ).…”

“…Polynomial fitting algorithm is used for removing fluorescence background signal and baseline in Raman spectra (Lieber & Mahadevan‐Jansen, ), and this algorithm was used for treated Raman spectra of paprika/Sudan I (Monago‐Maraña et al., ), chili pepper/Sudan I (Haughey et al., ), and turmeric/metanil yellow (Dhakal et al., ). In Raman HSI, fluorescence background signals could be corrected using the adaptive iteratively reweighted penalized least squares (airPLS) method (Lohumi et al., ; Zhang, Chen, & Liang, ). In addition, 2D‐median filter could be applied to remove high‐intensity spikes (Bocklitz, Guo, Ryabchykov, Vogler, & Popp, ).…”

Desarrollo y evaluación de un prototipo de medición de color en vegetales frescos

“…El prototipo de medición de color para uso en vegetales frescos fue construido y evaluado en el Laboratorio de Frutas y Hortalizas de la Universidad Nacional de Colombia, Sede Palmira. El prototipo consistió en una caja con dimensiones 20 cm x 20 cm x 20 cm y paredes de color negro, lo cual fue definido siguiendo las investigaciones efectuadas por Tarlak et al (2016) y Lohumi et al (2018). Se adaptaron el sensor de temperatura DHT11 en la base y el sensor de color TCS230-3200 que incluía LEDs, por encima del material a evaluar.…”