# Evaluation of the Radiological and Chemical Risk for Public Health from Flour Sample Investigation
## 3 Results and Discussion
### Elemental and Chemometric Analysis  
Table 5 reports the elemental composition of the analyzed flour samples.  
In particular, macro- (P, Mg, Ca) and micro-inorganic minerals (Na, Fe, Zn, Mn, Cu, Ni) determined by ICP-OES and ICP-MS were tabulated; their average concentrations were in good agreement with values reported in literature [53].  
As reported [48], the presence of inorganic minerals in flour samples is strictly correlated with the plant or fruit of origin. In order to unambiguously establish this correlation, PCA was conducted, considering nine variables and eleven cases. Preliminarily, the measure of sampling adequacy and Bartlett's test of sphericity were carried out to verify the suitability of the data for factor analysis. Test results suggest that the correlation matrix was factored and appropriate for PCA. By using the Kaiser criterion, two principal components (PC1 and PC2) with eigenvalues exceeding one were extracted, representing the 40.57% and 23.72% of total variance, respectively.  
PCA results reveal the presence of four different groups, reported in the bi-plot of Figure 6.  
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & & & & & & \multicolumn{3}{c}{**Mineral Concentration**} \\  & & & & & & **(mg kg\({}^{-1}\))** & \\ \hline
**Sample ID** & **P** & **Mg** & **Ca** & **Na** & **Fe** & **Zn** & **Mn** & **Cu** & **Ni** \\ \hline S1 & 3652 & 1159 & 357 & 41 & 133 & 36 & 36 & 7 & 0.6 \\ S2 & 1439 & 478 & 227 & 42 & 17 & 14 & 7 & 4 & 0.4 \\ S3 & 1045 & 240 & 54 & 1 & 5 & 12 & 8 & 3 & 0.5 \\ S4 & 2173 & 2976 & 8318 & 118 & 17 & 14 & 6 & 6 & 0.7 \\ S5 & 2204 & 1105 & 1204 & 64 & 20 & 16 & 6 & 7 & 0.9 \\ S6 & 1015 & 505 & 573 & 4607 & 19 & 8 & 28 & 6 & 1.4 \\ S7 & 808 & 172 & 272 & 78 & 18 & 8 & 6 & 2 & 0.5 \\ S8 & 2610 & 1140 & 864 & 40 & 44 & 24 & 38 & 6 & 2.5 \\ S9 & 717 & 1106 & 353 & 97 & 10 & 6 & 1 & 1 & 0.2 \\ S10 & 4497 & 1247 & 1161 & 132 & 29 & 26 & 9 & 11 & 0.9 \\ S11 & 4413 & 722 & 827 & 51 & 29 & 26 & 9 & 11 & 1.0 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Average mineral content, determined by ICP-OES and ICP-MS, for each investigated flour type.  
Figure 6: Results of the PCA (bi-plot) for all analyzed samples.  
The groups appear to be comparable to each other in terms of macro- and micro-element concentration. Specifically, four groups were recognized: group I (containing samples S10 and S11, green points) and IV (containing samples S1 and S8, blue points) refer to flows that turned out to be positively correlated, as far as PC1 is concerned, with Ca, Mg, P, Cu, Zn, Fe, Ni, and Mn, and negatively correlated with Na. Regarding PC2, flours in group I exhibited a positive correlation with values of Cu, P, Mg, and Ca contents, and a negative correlation with other variables. The opposite occurred for flours in group IV. Continuing on, group II (containing samples S4, S5, and S9, purple points) and III (containing samples S2, S3, S6, and S7, black points) refers to flours that turned out to be negatively correlated, as far as PC1 is concerned, with Ca, Mg, P, Cu, Zn, Fe, Ni, and Mn, and positively correlated with Na. Regarding PC2, flours in group II exhibited a positive correlation with the values of the Cu, P, Mg, and Ca contents, and a negative correlation with other variables. The opposite occurs for flours in group III.  
The differences in the average concentrations of P, Mg, Ca, Na, Fe, Zn, Mn, Cu, and Ni revealed among the identified groups strictly depend on the compositional features of the plant or fruit from which the analyzed flours derive. In the light of this, the obtained results could potentially be helpful to the producers to warn against food fraud, ensure flour quality, and inform the customers about sensitive parameters to be used potentially in the traceability process, in order to build up several fingerprints able to ensure the healthy effects of these products.