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Mar. 31, 2009 to Apr. 2, 2009
ISBN: 978-0-7695-3507-4
pp: 10-13
Near infrared spectroscopy combined with chemometrics was investigated to determine the total amino acids (TAA) in oilseed rape leaves. The samples in calibration, validation and prediction set were 80, 40 and 30, respectively. Different spectral preprocessing were compared, and three calibration methods were employed including partial least squares (PLS), multiple linear regression (MLR) and least squares-support vector machine (LS-SVM). The performance evaluation standards were determination coefficients (R2) and root mean square error (RMSE). Successive projections algorithm (SPA) was applied as variable selection method. The optimal model was achieved by SPA-LS-SVM using 13 relevant wavelengths with R2 = 0.9830 and RMSEP = 0.3964. The LS-SVM outperformed PLS and SPA-MLR models. The results indicated that near infrared spectroscopy was successfully applied for the determination of TAA in oilseed rape leaves. This detection method could be used for the on field monitoring of growing status and other physiological parameters of oilseed rape.
near infrared spectroscopy, oilseed rape, total amino acids, successive projections algorithm, least squares-support vector machine
Fei Liu, Fan Zhang, Hui Fang, Weijun Zhou, Yong He, "Determination of Total Amino Acids in Oilseed Rape Leaves Using Near Infrared Spectroscopy and Chemometrics", CSIE, 2009, Computer Science and Information Engineering, World Congress on, Computer Science and Information Engineering, World Congress on 2009, pp. 10-13, doi:10.1109/CSIE.2009.899
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