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

Abstract

Raman imaging has been proven to be a powerful analytical technique for the characterization and visualization of chemical components in a range of products, particularly in the food and pharmaceutical industries. The conventional backscattering Raman imaging technique for the spatial analysis of a deep layer suffers from the presence of intense fluorescent and Raman signals originating from the surface layer which mask the weaker subsurface signals. Here, we demonstrated the application of a new reflection amplifying method using a background mirror as a sample holder to increase the Raman signals from a deep layer. The approach is conceptually demonstrated on enhancing the Raman signals from the subsurface layer. Results show that when bilayer samples are scanned on a reflection mirror, the average signals increase 1.62 times for the intense band at 476 cm^-1 of starch powder, and average increases of 2.04 times (for the band at 672 cm^-1) for a subsurface layer of high Raman sensitive melamine powder under a 1 mm thick teflon sheet. The method was then applied successfully to detect noninvasively the presence of small polystyrene pieces buried under a 2 mm thick layer of food powder (a case of powdered food adulteration) which otherwise are inaccessible to conventional backscattering Raman imaging. In addition, the increase in the Raman signal to noise ratio when measuring samples on a mirror is an important feature in many applications where high-throughput imaging is of interest. This concept is also applicable in an analogous manner to other disciplines, such as pharmaceutical where the Raman signals from deeper zones are typically, substantially diluted due to the interference from the surface layer.

Keywords: Raman imaging; food authenticity; layered samples; reflection mirror; subsurface analysis.

Figure 1

Schematic diagram of line-scan Raman imaging system (a), sample holder with reflection mirror to facilitate layered samples (b), and schematic representation of Raman signals collated without (c) and with a back-reflection mirror (d).

Figure 2

Raman spectra of starch, melamine, and Teflon used in this study to form subsurface and surface layers.

Figure 3

Preprocessed Raman band images of S1 (a), and S2 (b) for replication 1. Raman signals increase for the subsurface layer with the mirror (difference between the images on upper row), however, there was no notable difference in the Raman intensity of the surface layer when using the reflection mirror (bottom row). Raman maps with and without mirror are presented in the same intensity scale for the purpose of direct comparison and the intensity scales are in arbitrary units.

Figure 4

Box plots showing the distribution of magnitudes of Raman signal increases for the subsurface layer on a mirror: subsurface (a) and surface layer (b) of S1, and subsurface (c) and surface layer (d) of S2. (This figure is the box plot representation of Figure 3 with additional wavebands).

Figure 5

Preprocessed mean Raman spectra of central hundred pixels from S1 (a) and from S2 (b) collected with and without reflection mirror.

Figure 6

Raman band (1000 cm⁻¹) images of polystyrene crystals exposed to the laser without any cover (a), covered with a 2 mm thick layer of wheat flour (b), and the spectral angle mapper (SAM) rule image of polystyrene crystals covered with a 2 mm thick layer of wheat flour (c). The intensity scales are in arbitrary units.

Figure 7

Mapping of hidden small polystyrene pieces using a reflection mirror: Raman spectra of polystyrene (a), and principle component analysis (PCA) loading plots calculated for S4 (with mirror) replications 1 (b) and 2 (c), and the corresponding PCA images on the right side. Note that the PCA results did not show any evidence of polystyrene pieces under wheat flour for the S4 data collected without the mirror.

Figure 8

SAM generated Raman images of small polystyrene pieces mapped without (upper row) and with (lower row) the reflection mirror for two replicates. (Representation of Sample S4 with supervised analysis method SAM).