Establishment of prediction model for chemical components based on handheld near-infrared spectrometer and collection method of sample spectra
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Abstract
The prediction model for tobacco chemical components of a handheld near-infrared spectrometer was studied, and by selecting 296 samples as the modeling set and using partial least square (PLS) method, a model was established. Seventy samples were used as the external test set of laboratory standard detection to validate the model. The results showed that the correlation coefficient of nicotine of the validation set was 0.89, the root mean square error was 0.28, the correlation coefficient of nicotine of the test set was 0.92, and the mean absolute error was 0.26. The accuracy of the established prediction model is high. Comparing the six-point detection method and the single-point detection method, the mean absolute error of the detection values obtained through six-point detection method decreased by 0.41 compared with the values through single-point detection method. Therefore, the six-point detection method is better.
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