Investigation of chemical composition of meat using spatially off-set Raman spectroscopy

Abstract

Spatially off-set Raman spectroscopy (SORS) offers non-invasive chemical characterisation of the sub-surface of various biological tissues as it permits the assessment of diffusely scattering samples at depths of several orders of magnitude deeper than conventional Raman spectroscopy. Chemicals such as glycogen, glucose, lactate and cortisol are predictors of meat quality, however detection of these chemicals is limited to the surface of meat using conventional Raman spectroscopy as their concentration is higher within the tissue. Here, we have used SORS to detect spectral bands for glycogen, lactate, glucose and cortisol beneath the surface of meat tissue by spiking. To our knowledge, this is the first report on this method for potential application in meat quality analysis. We further validate our SORS spectral results using chemometric analysis to determine chemical-specific spectral characteristics suitable for chemical identification. The chemometric analysis clearly shows distinction of spiked metabolites into four distinct groups, even for such chemically similar compounds as glucose, glycogen and lactate.