Multivariate Analysis of Heavy Metal Pollution and Salinity Interactions in Saline Soils for Agricultural Management

This study examined heavy metal (HMs) pollution in saline soils of Sukkur Sindh, Pakistan, and determined the relationship between salinity and metal content. Multivariate statistical methods such as regression analysis, principal component analysis (PCA), and cluster analysis (CA) were applied to characterize anthropogenic and natural factors affecting HMs in soils. Close relationships were found for electrical conductivity (EC) and cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), lead (Pb), and zinc (Zn) concentrations, but correlation strength differed among soil samples. Bulk Saline Soil (BSS) samples had Cd (1.01–3.62 µg/g), Co (18.6–29.1 µg/g), Cr (5.07–13.6 µg/g), Cu (122–191 µg/g), Pb (4.01–9.99 µg/g), and Zn (170–193 µg/g). Regression analysis was also used to demonstrate the need for EC as well as the measurement of HMs concentration in agricultural management. PCA indicated that variables under PC2 were generally orthogonal to PC1, with a third factor (PC3) accounting for 19.7% data variance, demonstrating the presence of other independent factors influencing HMs accumulation aside from the main components described. The results emphasize the significance of integrated EC and HMs monitoring in successful salt-affected farmland management.