[Analysis of lead in soil with partial least square regression (PLS) method and field portable X-ray fluorescence(FPXRF) analyzer].

In the present study, soil samples were scanned by NITON XLt920 field portable X-ray fluorescence (FPXRF) analyzer, and the relationship between the X-ray fluorescence spectra and the concentration of Pb in soil was studied. For predicating the Pb concentration in soil, a partial least square regression model (PLS)was established with 6 optimal factors and two closely relevant electron volt ranges: 10.40-10.70 keV and 12.41-12.80 keV. After cross-calibration, the correlation coefficient of value predicted by PLS model against that measured by ICP was 0.9666, and the root mean square error of prediction (RMSEP) was 0.8732. Meanwhile, the univariate linear regression and multivariate linear regression models were also built with the correlation coefficient of 0.6805 and 0.7302, respectively. Obviously, the PLS method was better than the other two methods for predication. Comparing to the conventional approach of atomic absorption spectroscopy (AAS), FPXRF has the advantages of rapidness, non-destruction and relatively low cost with the acceptable accuracy. It would be a powerful tool to decide which sample is needs for further analysis.