Identification of oil, sugar and crude fiber during tobacco (Nicotiana tabacum L.) seed development based on near infrared spectroscopy

Tobacco seeds are a potential feedstock for biofuels. To insure make full use of tobacco seed biomass, the present study was carried out to estimate seed oil, sugar and crude fiber during seed development through near infrared spectroscopy (NIRS) nondestructive determination. Four pre-processing methods, Savitzky-Goly after standard normal variate (SNV-SG), first Savitzky-Goly derivative after standard normal variate (SNV-SG-1stD), Savitzky-Goly after multiplicative scatter correction (MSC-SG) and first Savitzky-Goly derivative after multiplicative scatter correction (MSC-SG-1stD), were respectively performed to optimize the original spectra before establishment of the calibration models. Then linear partial least squares (PLS) and nonlinear least-squares support vector machine (LS-SVM) methods were utilized to develop the calibration models, in which the LS-SVM models were found to have better performance than PLS models. The best LS-SVM models of oil, sugar and crude fiber were established after pre-processed by MSC-SG-1st D. These results indicated that NIRS was suitable to rapidly and accurately analyze tobacco seed composition.