# Identification and Evaluation of Composition in Food Powder Using Point-Scan Raman Spectral Imaging
## 3 Results and Discussion  
### Identification of Components from Mixed Samples  
In this study, 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 flavorings in coffee creamers. Melamine was chosen as the third component due to its use for increasing the perceived protein content of dairy and dairy-substitution products in past instances of economically driven chemical adulteration. Figure 2 shows the Raman spectra of vanillin, melamine, sugar, and non-dairy creamer. Each component has several Raman spectral peaks, some of which overlap with peaks of other components, while others are unique without overlap. For each of the four components, the unique peak of the highest intensity is labeled in Figure 2 (vanillin: 1597 cm\({}^{-1}\), melamine: 674 cm\({}^{-1}\), sugar: 543 cm\({}^{-1}\), and non-dairy creamer: 1452 cm\({}^{-1}\)) and was selected as the Raman spectral fingerprint for that component. Raman spectral images of all samples were collected over a sample surface area of 96 mm \(\times\) 46 mm using a spatial resolution of 0.5 mm. This spatial resolution was selected based on our previous work that demonstrated effective detection of melamine particles at 0.5 mm spatial imaging resolution [31; 32]. Figure 2: Raman spectra of vanillin, melamine, sugar, and non-dairy creamer. For each image, the total numbers of pixels in the vertical and horizontal spatial axes were 92 and 192, respectively, with a total of 1024 Raman wavebands measured at each spatial pixel. For identification of individual chemical components in a mixture, the Raman spectral fingerprint of an individual component must be identified from the matrix of mixture spectra. Although time-consuming and tedious for large data sets, such identification can be performed manually by identifying a key Raman spectral peak of the component of interest. Alternatively, the spectral matrix can be decomposed to extract spectra of individual components and then identify the components. One such method is the application of the self modeling mixture analysis (SMA) to extract pure component spectra and score vectors followed by the use of spectral information divergence (SID) to identify the components corresponding to the spectra [40]. The expected number of pure components is pre-defined before SMA computation. For an unknown number of components in a mixture, it is generally desirable to overestimate the number of pure components, and to visually analyze the SMA result to determine the true number of pure components in the mixture. Although this study mixed three known components with non-dairy creamer, using the approach of initially overestimating the number of components (five components) for SMA computation produced favorable results--five component spectra and five corresponding scores, of which three were identified as being the pure component spectral contributions from vanillin, melamine, and sugar. The remaining two spectra/scores were identified as residual noise and disregarded from further analysis. Figure 3a shows the pure component spectra of vanillin, melamine, and sugar obtained by SMA for the 6% concentration sample. After the spectral mixture was diffused and pure component spectra and corresponding contributions were extracted, the SID method was used to identify the component corresponding to each pure component spectrum and contribution. Each of the pure component spectra was compared and computed against the reference spectra in the spectral library to obtain SID value. The extracted pure component spectra that showed the least divergence (smallest SID value) compared to a reference component spectrum was assigned identification corresponding to the reference component. Figure 3a shows that the three extracted pure component spectra and their corresponding reference spectra are well matched and, for vanillin and melamine, can be regarded as exact matches.