## 3 Results and Discussion
Figure 5 shows that the samples from day 3 are farther apart (more considerable Mahalanobis distances) than the other samples from days 4, 5, and 6, which suggests that the presence of different chemical compounds or different amounts of the same chemical compounds present in the stored poultry fillets should be interpreted. In contrast, the samples from days 5 and 6 overlapped, indicating that the samples from these two storage periods were chemically more similar. During poultry meat storage, chemical changes in its components occur, which are closely related to the metabolism of developing bacteria. Proteolysis in meat provides free peptides and amino acids as a good energy source for microorganisms. In addition, several chemicals are produced, including alcohols, volatile esters, ketones, and sulfur-containing compounds. This complex mixture can contribute to unpleasant aftertastes [32]. Meat spoilage is also characterized by the gradual formation of mucus due to the secretion of polysaccharides by some microorganisms [31]. Before they are detected by the senses (taste, smell), these changes can be \"observed\" by spectral data, which are much more sensitive to the chemical changes that cause sensory changes. Thus, the spoilage process can be identified at an earlier stage. No visible changes in the form of mucus or color changes were observed in the studies conducted in the present work. Still, the high sensitivity of FT-IR spectrophotometry made it possible to distinguish the samples tested for each day. Also, it made it possible to identify the degree of progressive undesirable meat spoilage processes related to microbial metabolism. These changes are invisible to the human eye. The changes in chemical composition observed through I.R. spectral data were reflected and confirmed by the results of determining microbial counts by standard methods. The research carried out in this study indicates that FT-IR spectroscopy can find applications for assessing the microbiological quality of products. It is a fast, non-invasive, and sensitive method. Samples from days 3, 4, and 5 were clearly separated (Figure 6), indicating that the chemical composition of the samples changed significantly. In contrast, between days 5 and 6, the samples had almost similar chemical composition, indicating that the dynamics of changes caused by microbial activity were no longer as significant as  
Figure 5: Spectra recorded for chicken meat samples stored for 3 (blue line), 4 (orange line), 5 (red line), and 6 (green line) days. in the initial storage period. The discriminant model constructed was cross-validated with the leave-one-out method. The capabilities of NIR and FT-IR for use in assessing the freshness of chicken breast meat were investigated by [PERSON] et al. [33]. Their results showed that these methods failed to completely distinguish samples from day 0 and day 4 but correctly classified samples from day 8 and day 14, where signs of spoilage were evident. They also determined that the most crucial process detected by NIR FT-IR spectroscopies is proteolysis, which involves the enzymatic cleavage of a peptide bond with the involvement of proteolytic enzymes. They noted an increase in absorption in the wavelength signals corresponding to the absorption bands of amides and amines. This suggests an increase in free amino acids and low-molecular-weight peptides with increased sample storage time since the aerobic bacterial species responsible for meat spoilage proceed to hydrolyze proteins immediately after glucose depletion. Enzymatic degradation of proteins led to the production of free peptides and amino acids used as energy sources and various metabolites that are spoilage indicators [33]. This study's results suggest that NIR FT-IR spectroscopy can become a helpful, rapid, and non-destructive tool for detecting spoilage. [PERSON] et al. [34] used FT-IR spectroscopy to differentiate between fresh and frozen chicken meat.