Chemometric Methods to Predict of Pb in Urban Soil using Spectrally Active of Soil Carbon.

What is it about?

This study has shown that NIRS may potentially estimate the total Pb of soil around the Port Pirie smelter. Although Pb is a spectrally inactive metal, a good predictive model for Pb in VNIR was achieved by combining soil RS with soil measurements using a PLSR model. The regression model showed that Pb concentration when converted to a log scale correlated optimally with the modified reflectance spectra. In addition to cross-validation, the accuracy and precision of the PLSR model were determined using an extra set of data that was not used in the original prediction

Featured Image

Why is it important?

This data set was evaluated through many prediction accuracy parameters such as R2, RMSE, RPD, and RER. The chemometric methods also used correlation loading function to highlight the regions of high spectral importance between 500 and 612 nm for Pb content determination. Total C was more spectrally active and more correlated with Pb than other elements in soil such as iron oxides and clays. In addition to an acceptable correlation between total C and soil Pb, the region associated with Pb detection was also coincident with the region where soil C could be detected. Thus, these results indicated that the absorption features for C content can be utilized to predict soil Pb. While the regression model for Pb concentration developed here was indeed quantitative and accurate, this model was developed for a specific soil and may not be applicable to another soil that has different feature space.

Perspectives