## 2 Material and Methods
### Statistical Analyses and Risk Assessment  
The IBM SPSS 25 statistical software package was used for statistical analysis. The data were expressed as mean and standard deviation. Data were analyzed using ANOVA tests. Significant differences were considered when \(p\) < 0.05.  
A probabilistic model was developed to estimate the intake level for Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn derived from feeding with Brassica vegetables. It should be pointed out that in developing the model, only the concentrations of trace elements for the _Brassica rapa_ species were considered as it is the one most consumed in Spain, Portugal and Southern Italy, being part of very traditional recipes. Nowadays, turnip greens and turnip tops have good commercial prospects, and their consumption, both fresh and processed, has considerably increased in the last years. _Eruca resicaria_ and _Sinapis alba_ have only eaten in small amounts in some salads, and they have a slightly spicy flavor like mustard greens.  
This model followed a probabilistic approach in which variables were described by probability distributions, and they were fitted to concentration data obtained in this study for each element. Additionally, to estimate the intake level, serving size was considered assuming 15-20 g per day (around 150-200 g of fresh matter) of _Brassica rapa_ (turnip greens or turnip tops). Daily intake was defined by a uniform distribution in the probabilistic model, meaning that all values in that range had the same probability to occur.  
The probability distributions describing the trace element concentration data were fitted using @Risk v7.5 (Palisade, Newfield, NY, USA). The simulation ran with 10,000 iterations per element. The goodness of fit assessed how well the fitted distribution described the data; in this section, the Akaike Information Criterion (AIC) and Chi-square statistical tests were used. Additionally, the visual analysis was considered to assess the fit of the probability distributions to intake data. Data obtained through this probabilistic model was  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Certified References Material (mg kg\({}^{-1}\))**} \\ \cline{2-10}
**Element** & \multicolumn{6}{c}{**White Cabbage BCR-679**} & \multicolumn{6}{c}{**Peach Leaves NIST-1547**} \\ \cline{2-10}  & \begin{tabular}{c} **LOD** \\ **(\#g/g)** \\ \end{tabular} & \begin{tabular}{c} **LOQ** \\ **(\#g/g)** \\ \end{tabular} & **Certified** & **Found** & \
\begin{tabular}{c} **Recovery** \\ **(\%)** \\ \end{tabular} & **Certified** & **Found** &
\begin{tabular}{c} **Recovery** \\ **(\%)** \\ \end{tabular} \\ \hline Cd & 0.005 & 0.016 & 1.66 \(\pm\) 0.07 & 1.57 \(\pm\) 0.01 & 95 & & & & \\ Co & 0.023 & 0.077 & & & & 0.07 \({}^{*}\) & 0.063 \(\pm\) 0.020 & 90 \\ Cr & 0.016 & 0.052 & 0.6 \(\pm\) 0.1 \({}^{*}\) & 0.61 \(\pm\) 0.03 & 102 & & & \\ Cu & 0.078 & 0.260 & 2.89 \(\pm\) 0.12 & 3.13 \(\pm\) 0.25 & 108 & & & \\ Fe & 1.09 & 3.62 & 55.0 \(\pm\) 2.5 & 56.2 \(\pm\) 3.0 & 102 & & & \\ Mn & 0.138 & 0.459 & 13.3 \(\pm\) 0.5 & 13.2 \(\pm\) 0.4 & 99 & & & \\ Ni & 0.056 & 0.187 & 27.0 \(\pm\) 0.8 & 25.6 \(\pm\) 0.9 & 95 & & & \\ Pb & 0.048 & 0.150 & - & - & - & 0.869 \(\pm\) 0.018 & 0.883 \(\pm\) 0.073 & 102 \\ Zn & 1.20 & 4.84 & 79.7 \(\pm\) 2.7 & 78.2 \(\pm\) 3.0 & 98 & & & \\ \hline \hline \end{tabular}  
\({}^{*}\) Indicative value.  
\end{table}
Table 2: Analysis of certified references materials (mean \(\pm\) standard deviation), limit of detection and limit of quantification.  
compared to the Spanish DRI for adult population [12]. In the case of Cd, Ni and Pb [13; 14; 15] considering that they are heavy metals, tolerable intakes (\(\upmu\)g/day) were considered.