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Los Angeles, CA
March 31, 2009 to April 2, 2009
ISBN: 978-0-7695-3507-4
pp: 10-13
ABSTRACT
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.
INDEX TERMS
near infrared spectroscopy, oilseed rape, total amino acids, successive projections algorithm, least squares-support vector machine
CITATION
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, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 10-13, doi:10.1109/CSIE.2009.899
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