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Application of Uninformative Variable Elimination Algorithm to Determine Organophosphorus Pesticide Concentration with Near-infrared Spectroscopy

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

Citation:  2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010  1008570.(doi:10.13031/2013.29654)
Authors:   Jingjing Chen, Yankun Peng, Yongyu Li, Jianhu Wu, Jiajia shan
Keywords:   NIR spectroscopy, Organphosphorus pesticide, Uninformative variable elimination.

The traditional methods of determination pesticide concentration are time-consuming, complicated, and require a lot of pretreatment processes. The objective of this research was to develop a new method for determination the pesticide concentration by using NIR spectroscopy. Organophosphorus pesticide (chlorpyrifos) solution was prepared by dissolving the commercial pesticide into distilled water at different concentrations, and samples were prepared by pipetting the solutions onto the filter papers and then were evaporated by vacuum drying oven. The spectra of filter paper samples were acquired in the range of 4000-10000 cm-1. Partial least squares regression (PLSR) was used to establish prediction models for predicting pesticide concentration. The uninformative variable elimination (UVE) was used for variable selection of NIR spectra data in order to develop an effective PLSR prediction model. The UVE algorithm reduced more than 70% of the variable number. Prediction results indicated that the UVE-PLSR models which multiplicative scatter correction (MSC) and standard normal variate (SNV) were used as pre-processing of spectral data were able to predict the concentration of chlorpyrifos with the correlation coefficient (R) is 0.94 for validation set, and the root mean square errors of prediction (RMSEP) is 0.36 for validation set.

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