## 3 Conventional and Emerging Methods of Analysis of Quality Changes in Muscle Food
### Brief Overview of Spectroscopic Techniques
Spectra originated in the MIR region are characterized by intense and more selective bands or peaks associated with molecules present in the food matrix (fundamental frequencies) [128; 129; 130; 131; 132; 133; 134; 135; 136; 137; 138; 139; 140]. Raman spectroscopy, based on the inelastic scattering of monochromatic light when interacting with molecules, is gaining an increasingly wider area of applications in different industries (e.g., pharmaceutical, food) [141; 142; 143]. Raman spectroscopy provides rich information of the molecule's vibrational modes, as well as its characteristic structure [141; 142; 143]. Although only a small fraction of the incident light is inelastically scattered, resulting in the Raman scattering being a naturally weak effect, the weak counterpart of the incident light energy is modified by the molecular vibrations of the scattering sample [141; 142; 143]. Therefore, the observed vibrational responses provide the analyst with enough information about the chemical composition of the sample [141; 142; 143]. In recent years, measuring the Raman spectra of complex samples (e.g., muscles, cereals, wine) in situ has been more accessible due to the release of high resolution and portable instruments that provide good detection capabilities [141; 142; 143]. Indeed, several kinds of handheld and portable Raman and NIR spectrometers have been developed in the recent years for on-site food quality applications in real time. Although some loss of information can occur, this can be compensated by the reduction of measurement time and instrumentation costs, as well as low power consumption, user-friendliness, and tailored design [144; 145; 132]. For example, spatially offset Raman (SORS) can be used to obtain layered subsurface information by collecting Raman scattering signals from a series of surface positions. Increasing the distance (offset) between the laser and detector results in less signal contributions from the surface and more Raman signatures from the subsurface layers [143; 146]. Most of the applications based in vibrational spectroscopy reported in the literature have been primarily target on spot measurements using either the NIR or visible (Vis) regions of the electromagnetic spectrum. More recently, a diverse range of hyperspectral devices, including cameras and spectral imaging devices, are now readily available providing exciting new possibilities in food analysis and processing. This technology can acquire either single or multiple images at discrete wavelengths, presenting the potential for the detection of specific attributes relating to quality in an extensive range of raw materials and products [147; 148; 41]. Overall, the availability of hyperspectral imaging (HSI) and multispectral imaging (MSI) systems allowed for obtaining spatial, spectral, and multiconstituent information about the sample being analyzed has increased notably [147; 148; 41]. Multispectral imaging involves the acquisition of spectral images at few discrete and narrow wavebands (bandwidths of between 5 and 50 nm) and it might be considered an improvement of HSI as this technology is cost effective [147; 148; 41]. The result is the ability of MSI to simultaneously predict multiple components, providing a key advantage and rendering a promising future outlook with a single, automated image acquisition [147; 148; 41]. HSI relies on one of two sensing modes as in-line scanning (push broom) mode (Figure 2) or as filter-based imaging mode [147; 148; 41]. In-line scanning mode involves the imaging system scans moving product items. This results in three-dimensional (3D) hyperspectral images, also called hypercubes [147; 148; 41]. In filter-based imaging mode, spectral images are obtained from stationary targets for a waveband sequence using either a liquid crystal tuneable filter or an acousto-optical tunable filter [147; 148; 41]. In-line scanning is the most common as it is relatively easy to implement, particularly for real-time and online applications.