## 3 Results and Discussion
### Validation of the Calibration Model  
Table 3 shows the chemical composition (mean, standard deviation, and range of values) of traditional sausages, according to the reference methods and NIR spectroscopy, for the validation set of samples. The composition was also very variable and similar to the composition of the samples used for the development of the calibration model. With regard to fat content, failure to comply with the legislation was also observed in 20% of the samples where the content was higher than 35%.  
The highest deviation between the standard reference methods values and the NIR spectroscopy values was observed in the moisture content, and this can be attributed to changes occurring during the time elapsing between the two types of analyses. Whereas in the present study, the homogenized sausage samples' storage period did not exceed one week, at laboratory conditions, for routine analysis, changes in the moisture content during storage are dependent on the laboratory capacity to process the analyses and available equipment for sample storage such vacuum packaging. Thus, changes in the moisture content during analyses cannot be excluded.  
Concerning nutrients such as protein and fat, whose content is declared in food labels, deviations in their contents fell within the allowances (tolerance) for variation between nutrient values declared on a label and values established by the monitoring authorities. The limits of permissible deviations are \(\pm\)20% when either the protein or the fat content ranges from 10-40 g/100 g of product [33]. In the present study, NIR spectroscopy values and reference methods values deviated approximately \(\pm\)3% for protein content and approximately \(-\)5% to 10% for fat content. It is also noted that NIR spectroscopy was successful in detecting the samples that failed to comply with the legislation with regard to the fat content. In other words, determination of the chemical composition of traditional sausages with NIR spectroscopy will not significantly differ from the chemical composition determined with standard reference methods, enabling the application of NIR spectroscopy for fast routine determination of the sausage composition.  
Regression values for measured (Ref) and estimated (NIR) values for moisture, ash, protein, and fat content of traditional sausages used for the external validation are presented in Figure 3. The highest R\({}^{2}\) (0.9671) value was observed between the reference values and the NIR values for moisture content, whereas the lowest R\({}^{2}\) value was observed for ash content (0.3424). There was a good agreement between reference values and NIR values for fat content (0.8156), whereas an average agreement was found between reference values and NIR values for protein content (0.5708).  
Table 4 shows the Pearson correlation coefficients between the measured and the estimated (NIR) values for moisture, ash, protein, and fat contents. Significant positive correlations (\(p<0.001\)-0.01) were observed for all examined parameters. The highest coefficient is observed for moisture content, followed by the coefficients for fat and protein contents.  
It is noted that this calibration model is valid when the samples' characteristics are the same as those used in the external validation. Therefore, if there are changes in the degree of drying or in the regulations for either fat or protein content, the application of the calibration model may lead to invalid results. However, it is also worth reporting that the main advantage for the application of NIR spectroscopy in the estimation of the composition of food products is the fact the database can be constantly expanded with the addition of the compositional data from new samples, leading to the development of a new calibration model that incorporates changes in the product composition.  
Figure 3: Regression values for measured (Ref) and estimated (NIR) values for moisture, ash, protein, and fat content of traditional sausages used for the external validation.