## 4 Discussion  
Previous reports have used a chemometric approach to identify bacteria, especially those employing SERS technology coupled with microscopy interrogating single cells and specific cell wall areas [21; 22]. Although assigning a signal to a particular compound is not always possible, this study compared the spectra acquired to previous reports using similar Raman technologies shown in Table 2. Each strain spectrum differed from the non-inoculated control, although some peaks are matched in all the samples at the Raman shift (cm\({}^{-1}\)) axis. This is the case for signals at 424-427, 764-766, 804-806, 940-943, and 1333-1335 cm\({}^{-1}\) Raman shift, indicating molecules existing in the media, such as carbohydrates (C-C and C-O-H) and proteins. Furthermore, some peaks were distinctive for each species, such as 618 (Phe) and 670 (Val) cm\({}^{-1}\) shifts for _S. enterica_, 657 (Tyr), and 901 (teicuronic acid present in Gram-positive cell wall) cm\({}^{-1}\) shifts for _S. aureus_. Interestingly, this last peak was not observed in _L. monocytogenes_, another Gram-positive strain, but in _S. enterica_, where the adenine signal can overlap. Instead, peaks in _L. monocytogenes_ spectra appeared at 1000 (Phe), 1173 (C-H, wagging of Tyr, guanine, cytosine, fatty acids, CH\({}_{3}\) deformation), 1285 (amide III, CH\({}_{2}\) twisting), 1582 (guanine, adenine, ring stretching, Phe, Trp), and 1635 (thymine, guanine) cm\({}^{-1}\) shifts. Interestingly, a prominent peak found at 1333 corresponds to amide III vibrations, Trp, and C\(\alpha\)-H vibrations, and CH-deformation is significantly enhanced after 18 h and 24 h for all the strains but not in control, indicating an increase of transmembrane proteins that characterise mature cells in the stationary growth phase [23]. Other signals could not be associated with other compounds in the literature but are distinctive of each sample, creating a particular fingerprint and allowing the discrimination between them. This is the case for two remarkable shifts noticed at 779 and 895 for _E. coli._ No compound was associated in previous reports with these specific shifts. However, these are distinctive peaks in the fingerprint of _E. coli_ at 18 and 24 h of growth. The Raman handheld device used in this study is loaded with a 785 nm laser with Orbital Raster Scan (ORS) technology that enables the system to scan a larger area than conventional Raman, allowing the analysis of more complex structures [24]. Moreover, it has been suggested that the 785 nm wavelength falls within an optimum balance between a reasonable signal-to-noise ratio and low damage to the cell structure [25]. It was observed that shorter wavelength lasers provide spectra with less noise but increase cell degradation, whereas longer wavelengths lower Raman scattering efficiency [25]. However, the spectra acquired in this study are likely a composite of the molecules suspended in the media and those present on the bacterial cell surface. Hence, PCA and SVM classifier systems were used to identify the studied strains based on a unique fingerprint. The data analysis in this study was made directly without normalising data, subtracting the background as described in the methodology section. Future work will investigate the effects of adding a normalising pre-processing step, such as normalising the 1000 nm response to unit magnitude. Previous studies have reported Raman techniques for rapidly detecting foodborne pathogenic bacteria. [PERSON] et al. (2011) described a method to distinguish between _S. enterica_, _E. coli_, and _S. aureus_ simultaneously using a combination of nanomembranes with metallic nanoparticles loaded with pathogen-specific antibodies for SERS [26]. This technique accomplished rapid detection under 45 min with a detection limit of 10\({}^{2}\)-10\({}^{3}\) CFU mL\({}^{-1}\).