Qualitative and quantitative identification of nitrofen in terahertz region

Abstract

Terahertz time domain spectroscopy (THz-TDS) has been utilized as an available tool for the identification and analysis of compounds owing to its unique characters. The THz spectrum of nitrofen was detected and the comparison with other two solid pesticides (thiacloprid and acetamipyrid) was provided to demonstrate pesticide's unique characteristics in THz region. For the quantitative analysis of pesticide, we applied THz-TDS to detect nitrofen mixtures with different weight ratios, and employed partial least squares (PLS), interval PLS (iPLS), moving window PLS (mwPLS) and backward interval PLS (biPLS) algorithms to achieve the best analysis accuracy through a variable selection. The regression models were optimized by root mean square error of cross validation (RMSECV) in the calibration set, and the performance of models was evaluated according to the root mean square error of prediction (RMSEP) and correlation coefficient (R). Compared with the results of the other three methods, the biPLS model acquired the best performance with RMSEP=0.4064, R=0.9995.