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Feasibility Study of Soil Heavy Metal Pb2+ Content Detection Using Terahertz Spectroscopy

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Paper number  131620908,  2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: http://dx.doi.org/10.13031/aim.20131620908) @2013
Authors:   BIN LI, WENZHONG GUO
Keywords:   Terahertz time-domain spectroscopy, soil heavy metals, Pb2+, partial least squares method, interval method

Abstract. Soil is an important natural resource for human beings. Soil heavy metal pollution has been making prominent influences on farmland environment. Pb2+ is kind of typical heavy metals. Development of an advanced, efficient and feasible detection method for heavy metal Pb2+ content in soil is in an urgent need.

This study presents a feasible study of heavy metal Pb2+ content detection method based on Terahertz Time-domain Spectroscopy (THz-TDS). A series of experiment were carried out. Soil samples with predefined concentration levels of heavy metal ions Pb2+ were carefully prepared in China Agricultural University, Beijing, China. Soil with a sample holder was used for the spectra measurement. The absorption spectra were collected with a THz spectroscopic system in Capital Normal University, Beijing, China. Multivariate statistical methods were studied and used to analyze the collected data and establish predication model for Pb2+ concentrations. Calibration and prediction models were established based on partial linear regression (PLR) methods using the full THz spectrum and the selected THz wavebands respectively. GA method was used for

characteristic wavelengths’ selection. The prediction models were validated with a set of randomly collected spectra. The results showed that the established models were able to predict soil heavy metal Pb2+ content with a correlation coefficient of 0.81.The method of using THz technology for soil heavy metal Pb2+ detection is feasible; however, more investigation on measurement principles and a large amount of sample tests are still needed in the future.

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