Abstract: Visible and near infrared (Vis/NIR) spectroscopy were employed for the fast and nondestructive estimation of the total amino acid (TAA) content in barley (Hordeum vulgare L.) leaves. The calibration set was composed of 50 samples; and the remaining 25 samples were used for the validation set. Seven different spectral preprocessing methods and six different calibration methods (linear and nonlinear) were applied for a comprehensive prediction performance comparison. Successive projections algorithm (SPA) and regression coefficients (RC) were applied to select effective wavelengths (EWs). The results indicated that the latent variables-least-squares-support vector machine (LV-LS-SVM) model achieved the optimal performance. The prediction results by LV-LS-SVM with raw spectra were achieved with a correlation coefficients (r) = 0.937 and root mean squares error of prediction (RMSEP) = 0.530. The overall results showed that the NIR spectroscopy could be used for determination of TAA content in barley leaves with an excellent prediction precision; and the results were also helpful for on-field monitoring of barley growing status under herbicide stress during different growth stages.
Keywords: visible and near infrared spectroscopy; barley; total amino acid; variable selection; successive projections algorithm; least squares-support vector machine
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Bao, Y.; Kong, W.; He, Y.; Liu, F.; Tian, T.; Zhou, W. Quantitative Analysis of Total Amino Acid in Barley Leaves under Herbicide Stress Using Spectroscopic Technology and Chemometrics. Sensors 2012, 12, 13393-13401.
Bao Y, Kong W, He Y, Liu F, Tian T, Zhou W. Quantitative Analysis of Total Amino Acid in Barley Leaves under Herbicide Stress Using Spectroscopic Technology and Chemometrics. Sensors. 2012; 12(10):13393-13401.
Bao, Yidan; Kong, Wenwen; He, Yong; Liu, Fei; Tian, Tian; Zhou, Weijun. 2012. "Quantitative Analysis of Total Amino Acid in Barley Leaves under Herbicide Stress Using Spectroscopic Technology and Chemometrics." Sensors 12, no. 10: 13393-13401.