Research on the Characteristic Spectrum Selection Method of CARS on Building NIR Calibration Model to Detect Thickness of Flue-cured Tobacco

The thickness of tobacco is an important factor to measure the quality and grading of flue-cured tobacco. The present study shows that it is feasibility to prediction thickness of tobacco by fourier transform near-infrared(FT-NIR)spectrometry. Two methods of screening spectrum range that calculated by competitive adaptive reweighted sampling method (CARS) and directly use the spectrum range (1 000-2 500 nm) had been combined with partial least squares (PLS) to establish the FT-NIR model. The results show that the number of variables of the thickness of tobacco FT-NIR model also had reduced to 180 from 1 543. The number of principal components also had reduced 6 from 10. The lower of standard error of calibration (SEC) and root mean square error of cross validation (RMSECV) was 0.003 4 and 0.010 3, respectively.Thirty samples had been used as external validation. The standard error of validation (SEV) and standard deviation of validation error (SDV) reduced to 0.001 1 from 0.018 2. According NIR model of paired-t tests of measured and prediction value, the results have no significant variance at level of 0.05.The CARS-NIR model have smaller variance. The stability and forecasting accuracy of FT-NIR model had been developed improved by the CARS method to select the sensitive wavelengths.