## 4 Results and Discussion
### Analysis of Heavy Metal Sources  
The results of the correlation analysis can reflect the degree of association between different elements and infer their potential homology. The higher the significance of the correlation, the stronger the likelihood that the sources of various heavy metal elements are consistent [29]. The results depicted in Figure 2 demonstrate a significant positive correlation (\(p\) < 0.01) among Ni, Cu, Pb, and Zn. Notably, the correlation between Pb and Zn is particularly strong with a coefficient of 0.76, indicating a common or similar source for these four heavy metal elements. There is also a significant correlation between Cr and Ni, Cd and Zn, suggesting that their sources are similar and potentially mixed. The negative or weak correlation (absolute value less than 0.3) observed between As and Hg with other elements implies that As and Hg are unlikely to share the same source as other heavy metals, indicating independent sources for these elements. In order to further analyze the sources of heavy metal elements in the soil of the study area, principal component analysis of heavy metal elements in the soil of the study area was carried out, in which the results of KMO and [PERSON]'s spherical test showed that the KMO = 0.619 > 0.5 for the sample data, and the significance of [PERSON]'s spherical test was 0.00 < 0.05, which indicated that the principal component analysis could be carried out. The results of the analysis are shown in Table 6, where three principal component factors were extracted with Eigenvalues of 3.387, 1.062 and 0.972, respectively, with a cumulative contribution of 74.51 percent, so that the analytical study of these three principal components explains most of the heavy metal sources. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Item** & **Maximum** & **Minimum** & **Average** & \begin{tabular}{c} **Coefficient of** \\ **Variation (\%)** \\ \end{tabular} & \
\begin{tabular}{c} **Background Value of the Soil** \\ **Environment in Guangxi** \\ \end{tabular} &
\begin{tabular}{c} **Screening Value for** \\ **Agricultural Land** \\ \end{tabular} \\ \hline Cr & 298.57 & 132.29 & 194.05 & 20.30 & 82.10 & 150.00 \\ Ni & 53.10 & 28.85 & 38.14 & 14.58 & 26.60 & 60.00 \\ Cu & 105.12 & 39.80 & 53.29 & 24.93 & 27.80 & 150.00 \\ Zn & 221.77 & 108.58 & 147.11 & 19.80 & 75.60 & 200.00 \\ As & 350.33 & 39.75 & 122.35 & 63.56 & 20.50 & 40.00 \\ Cd & 4.97 & 1.04 & 2.37 & 49.82 & 0.27 & 0.30 \\ Pb & 134.85 & 47.26 & 69.40 & 25.49 & 24.00 & 70.00 \\ Hg & 1.97 & 0.20 & 1.33 & 32.67 & 0.15 & 1.30 \\ pH & 5.16 & 3.42 & 4.02 & 8.23 & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Statistics of soil’s heavy metal content (mg/kg) and pH characteristic value. The contribution rate of factor 1 (PC1) was 42.34%, and Ni, Pb, Zn, Cd, Cr, and Cu had large loadings, indicating that the sources of these six heavy metals were similar. The average concentration of Ni, Pb, Zn, Cd, Cr, and Cu were higher than the background values of the Guangxi soils [18], suggesting that the sources originated mainly from anthropogenic sources, in addition to natural sources. Studies have indicated that the primary gold-bearing minerals found in the original Jinzhuzhou gold mine include pyrite, arsenopyrite, galena, sphalerite, and chalcopyrite, among others [30]. The accumulation of waste slag, wastewater and dust resulting from mining and smelting processes can exert a certain impact on the surrounding soil environment through long-term stacking, rain leaching and atmospheric deposition [31,32]. The study area is cultivated soil, where the use of organic fertilizers, chemical fertilizers, and pesticides in agricultural activities can lead to an increased accumulation of heavy metals such as Pd, Cd, and Cu on the soil surface. The contribution rate of factor 2 (PC2) was 20.019%, and As had a large loading with a contribution of 79.70%.