## 3 Discussion
The latter can be visualized in a general way with a box-plot representation (Figure 5), where through the comparison between matrices (RM and SC) based on volatile chemical components, for example, a decrease of FSFAs and an increase of ESTs (produced by the condensation/substitution reaction between an organic acid and an aliphatic alcohol) were observed. Nevertheless, it should be highlighted that locations 4 and 6 using process 4 (cooked whey residue from cheese + salting whey or commercial milk cream) along with location 5 using process 5 (rennet curdling) produced SC with the highest variability in the main volatile constituents identified for most SC samples, i.e., (i) the lowest and lower contents of FSFAs and esters for both L4 and L6, (ii) the highest and lowest contents of FSFAs (including SCFAs) and esters, respectively for L5, and (iii) the lowest (L4) and mid-range (L6) contents of SCFAs. Of course, since the raw material for process 4 was whey (containing up to 14% protein and up to 4% fat [69]) from artisanal cheese making, its fat content must have been low and, consequently, lipolytic activity (or \(\beta\)-oxidation of fatty acids) by LAB during the fermentation process did not produce amounts of FSFAs and esters (derived from free fatty acids) comparable to the other SC samples, which would be in agreement with that reported by [PERSON] et al. [70], who determined that during the buttermilk fermentation (by LAB) to produce cheddar cheese, the formation of free fatty acids by lipolysis depended on the fat content of the matrix, i.e., the higher the fat content, the higher the amount of free fatty acids. In addition, if there was less fat content (as well as low glyceride content), the esterification by LAB (alcoholysis) should also be low [58; 67]. On the other hand, as it is well known, rennet is a complex mixture of protease-type enzymes (mainly chymosin and pectin) used industrially or domestically to curdle milk (casein coagulation) and produce fermented dairy foods (e.g., ripened and fresh cheeses), which might present desirable or undesirable sensory characteristics (taste and flavor) depending on storage time, as well as whether or not the rennet contains some lipases [71]. However, when [PERSON] et al. [72] studied the effect of the use of rennet (sanitized paste) on the volatile fraction of a hand-made cheese (from goat's milk), they found the highest content of SCFAs (C\({}_{4\oplus 3>}\) C\({}_{6\oplus 6}\)), an increased content of mono-/di-glyceride, and a low content of ethyl esters (C\({}_{8:0}\) and C\({}_{6:0}\) esters being the majority) compared to other industrially processed cheeses; they also suggested that the high SCFA content was due to native lipases in raw milk. These findings showed similarities with the SC from L5: the highest content of SCFAs (differing in C\({}_{6:0}\)\(>>>\) C\({}_{4:0}\)), an increase of monoglycerides (related to FSFA content), and a low content of ethyl esters (C\({}_{8.0}\) > C\({}_{6.0}\)); consequently, the volatile chemical profile was different from that of the other SC samples. Finally, [PERSON] et al. [73] described that (i) SPME and GC-MS are widely used techniques for food volatilome analysis, (ii) multivariate analysis (PCA and LDA) is an important tool for an accurate description of the obtained data, (iii) each food would have a particular volatile chemical fingerprint, and (iv) food volatilome profiles could be a useful and effective tool for the assessment of both quality and authenticity. According to these premises, the volatilome profile of SC could be established in this research and, therefore, this food would have its own volatile chemical fingerprint, which is described above.