Abstract
This study used Raman spectral imaging coupled with self-modeling mixture analysis (SMA) for identification of three components mixed into a complex food powder mixture. Vanillin, melamine, and sugar were mixed together at 10 different concentration level (1% to 10%, w/w) into powdered non-dairy creamer. SMA was used to decompose the complex multi-component spectra and extract the pure component spectra and corresponding contribution images. Spectral information divergence (SID) values of the extracted pure component spectra and reference component spectra were computed to identify the components corresponding to the extracted spectra. The contribution images obtained via SMA were used to create Raman chemical images of the mixtures samples, to which threshold values were applied to obtain binary detection images of the components at all concentration levels. The detected numbers of pixels of each component in the binary images was found to be strongly correlated with the actual sample concentrations (correlation coefficient of 0.99 for all components). The results show that this method can be used for simultaneous identification of different components and estimation of their concentrations for authentication or quantitative inspection purposes.
Highlights
Food authentication is important in food supply chain operations, as illustrated by various incidents of food fraud that have caused public outcry around the world, raised public concerns, and highlighted the need for effective ingredient authentication methods
This study presents the use of Raman spectral imaging to obtain Raman chemical images of a food powder mixed with multiple components
To investigate methodology for identifying multiple components mixed to form a complex food matrix, vanillin and sugar were chosen as components due to their common use as
Summary
Food authentication is important in food supply chain operations, as illustrated by various incidents of food fraud that have caused public outcry around the world, raised public concerns, and highlighted the need for effective ingredient authentication methods. A variety of highly accurate analytical methods, such as DNA-based methods [1], polymerase chain reaction [2], mass spectrometry [3], and gas and liquid chromatography [4], can be used for food authentication but are limited in practical application due to high operational costs, long sampling times, and limited sampling volumes. Interest in the development and use of non-destructive optical analysis methods for food safety and quality applications has been increasing due to their greater simplicity, lower operational costs, and suitability for rapidly.
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