## 4 Conclusions  
The present study results showed that NIR spectroscopy can be applied as a screening technique when a high but not an absolute level of accuracy is required. NIR spectroscopy can estimate moisture and fat contents of traditional sausages with high accuracy, whereas prediction of the protein content can also be achieved with reasonable accuracy. However, the development of a model for the estimation of the chemical composition of sausages, representing variations in sausage ingredients and/or production conditions, requires analysis of a greater number of samples. Future research should focus on developing calibration models for the next generation of low-cost, simple-operation portable NIR spectroscopy instruments that would help butcher shop owners produce healthier sausages that are in compliance with the specifications of the Greek Food Legislation.  
Conceptualization, E.K. and P.M.; methodology, P.M.; investigation E.K. and V.P.; formal analysis, E.K.; resources, P.M.; data curation, E.K. and V.P.; writing--original draft preparation, E.K.; writing--review and editing, E.K. and P.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability Statement:Data is contained within the article.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Correlation Coefficient** & **Significance** \\ \hline Moisture (\%) & 0.983 & *** \\ Ash (\%) & 0.585 & ** \\ Protein (\%) & 0.756 & *** \\ Fat (\%) & 0.903 & *** \\ \hline \hline \end{tabular}  
* \(=p<0.01\); *** \(=p<0.001\).  
\end{table}
Table 4: Pearson correlation coefficients for measured (Ref) and estimated (NIR) values for moisture, ash, protein, and fat content of traditional sausages were used for the external validation.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Mean Values** & **Standard Deviation** & **Range** \\ \hline \hline \multicolumn{4}{c}{Reference Methods} \\ \hline Moisture (\%) & 50.73 & 6.934 & 36.46–59.62 \\ Ash (\%) & 2.29 & 0.452 & 1.19–3.18 \\ Protein (\%) & 17.32 & 2.321 & 13.64–21.45 \\ Fat (\%) & 28.83 & 8.513 & 19.38–47.18 \\ \hline \multicolumn{4}{c}{NIR Spectroscopy} \\ \hline Moisture (\%) & 47.90 & 7.238 & 34.21–58.06 \\ Ash (\%) & 2.42 & 0.248 & 1.94–2.91 \\ Protein (\%) & 16.73 & 2.377 & 13.14–20.37 \\ Fat (\%) & 30.20 & 8.431 & 17.84–43.72 \\ \hline \multicolumn{4}{c}{Deviations between NIR spectroscopy values and reference methods values} \\ \hline Moisture (\%) & \(-\)2.83 & 1.326 & \(-\)4.73—0.15 \\ Ash (\%) & 0.13 & 0.367 & \(-\)0.38–1.12 \\ Protein (\%) & \(-\)0.59 & 1.643 & \(-\)2.99–3.04 \\ Fat (\%) & 1.36 & 3.730 & \(-\)5.48–9.87 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Chemical composition according to reference measurements and NIR spectroscopy for external validation samples and deviations between NIR spectroscopy values and reference methods values (n = 10).  
**Acknowledgments:** The authors would like to thank the company Unity, Ltd., Cholargos, Athens, Greece, for the development of the calibration model.  
**Conflicts of Interest:** The authors declare no conflict of interest.