Development of near-infrared spectroscopy based quantitative model for nicotine with projection pursuit method
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Abstract
In order to accurately and rapidly determine the nicotine content (mass fraction) in tobacco leaves, a quantitative model based on near-infrared (NIR) spectroscopy for nicotine content in tobacco leaves was established with projection pursuit method. The NIR spectra and nicotine contents of tobacco samples in calibration set were obtained by a handheld NIR spectrometer and a laboratory NIR spectrometer respectively. After the first-order derivation of spectral data, the wavelength variables were selected by projection pursuit method and competitive self-adaptive reweighted algorithm, and the corresponding quantitative prediction models for nicotine content were developed via partial least square method. The two developed models were used to predict the nicotine content in the samples of validation sets of three batches. The results showed that the nicotine contents in tobacco leaves predicted by the model developed with projection pursuit method had smaller mean absolute error and higher correlation coefficient. This method provides a support for the accurate prediction of nicotine content in tobacco leaves.
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