Rapid discrimination of soil variety based on spectroscopic techniques - WANG Zun-yi; JIN Chun-hua; LIU Fei; WANG Yan-yan; BAO Yi-dan (浙江大学学报. 农业与生命科学版)
Three spectral regions were investigated for the discrimination of four main soil varieties in Zhejiang Province. The three spectral regions included the visible-near infrared (Vis-NIR), near infrared (NIR), middle-infrared (MIR) spectroscopy. After spectral collection, different calibration methods were applied to improve the detection precision and to reduce the computational complexity. Principal component analysis (PCA) combined with back propagation neural networks (ANN/BP), partial least squares (PLS) and PLS combined with ANN (PLS-ANN) were applied for calibration models. The results indicated that the performance of MIR was not quite acceptable. However, Vis-NIR and NIR made an excellent discrimination precision for soil varieties. In Vis-NIR region, PLS-ANN model outperformed PCA-ANN/BP and PLS models. This supplies a convenient and feasible approach for the rapid discrimination of soil variety.