## 2 The Tools--Chemometrics and Vibrational Spectroscopy
### Vibrational Spectroscopy  
Qualitative and quantitative applications of vibrational spectroscopic techniques are well established in the food industry [48; 49; 50; 51]. This is also true for seafood, were specific applications include the evaluation of product freshness, authenticity of fish and seafood ingredients and products, such as geographical origin and production method (e.g., wild vs. farmed, fresh vs. frozen-thawed); and detection or monitoring of spoilage [48; 49; 50; 51]. It is in this context that vibrational spectroscopy (infrared, Raman) has been one of the most attractive and commonly used methods of analysis, as it allows for simultaneous, rapid, and non-destructive determination of major components in many  
Figure 1: An illustration of the application of principal component analysis combined to vibrational spectroscopy to identify the origin of seafood. agriculture-related products and plant materials [42; 48; 52]. Mid (MIR), near infrared (NIR) and Raman spectroscopy are classified as molecular/vibrational spectroscopy techniques and they are used to evaluate and study the interactions of electromagnetic waves with a sample. The electromagnetic spectrum comprises of different types of radiation, ranging from radio waves (lower end of the spectrum) through to gamma rays (upper end) [41; 42; 51; 52; 53]. Molecules absorb IR owing to the vibrational movements of their chemical bonds (e.g., bending, stretching, rocking, wagging or scisoring) [41; 42; 51; 52; 53]. As these actions occur solely at specific energy levels, chemical bonds absorb IR radiation of defined energies at distinct wavenumbers or wavelengths. Infrared spectroscopy is the measure of this absorption, resulting in a spectrum with peaks representing the chemical bonds present in the given sample [41; 42; 51; 52; 53]. The NIR region of the spectrum is located between 700-2500 nm [41; 42; 51; 52; 53]. NIR spectroscopy has been established as an efficient analytical technique in the food industry when combined with chemometric tools (e.g., data mining and data processing), as the weaker bands in the NIR region are less intense than those in the MIR (between 10-100 times) [41; 42; 51; 52; 53]. This characteristic of the NIR energy facilitates that samples can be analysed directly without the need of pre-processing (e.g., drying, homogenisation, grinding) [41; 51; 52; 53]. Overall, the NIR spectra is the result of overtone and combination bands of fundamental vibrations of C--H, O--H, and N--H bonds [41; 51; 52; 53; 42]. The interpretation of NIR spectra can be hindered further as consequence of not only the many overlapping bands but also because an individual analyte might absorb at several wavelengths [41; 51; 52; 53; 42]. The MIR region (4000-400 cm\({}^{-1}\)) has been very important in the development of several applications in different fields (e.g., biology, environment and food) [41; 51; 52; 53; 42]. The MIR is of particular importance analytically as it contains the so called biochemical and chemical fingerprint region (1800-900 cm\({}^{-1}\)) [41; 42; 51; 52; 53]. The MIR region is known to contain the distinguishing a number of common biochemical and chemical compounds present in complex food matrices such as Amide I, II and III around 1650 cm\({}^{-1}\), 1550 cm\({}^{-1}\), and 1260 cm\({}^{-1}\), carbohydrates around 1155 cm\({}^{-1}\), glycogen around 1030 cm\({}^{-1}\), lipids and ester groups around 1750 cm\({}^{-1}\), asymmetric phosphate stretching vibrations (PO\({}_{2}^{-}\)) around 1225 cm\({}^{-1}\), symmetric phosphate stretching vibrations (PO\({}_{2}^{-}\); \(\sim\)1080 cm\({}^{-1}\)) and protein phosphorylation around 970 cm\({}^{-1}\)[41; 51; 52; 53; 42]. The MIR range between 1500 and 400 cm\({}^{-1}\) is also known as the fingerprint region [41; 51; 52; 53; 42]. Absorption values or peaks in the fingerprint region are predominantly produced by bending and skeletal vibrations, which are sensitive to large wavenumber shifts, minimising against unambiguous identification of specific functional groups.