摘要
Overabundance of phosphorus (P) in soils and water is of great concern and has received much attention in Florida, USA. Therefore, it is essential to analyze and predict the distribution of P in soils across large areas. This study was undertaken to model the variation of soil total phosphorus (TP) in Florida. A total of 448 soil samples were collected from different soil types. Soil samples were analyzed by chemical reference method and scanned in the visible/near-infrared (VNIR) region of 350-2 500 nm. Partial least squares regression (PLSR) calibration model was developed between chemical reference values and VNIR values. The coefficient of determination (R2) and the root mean squares error (RMSE) of calibration and validation sets, and the residual prediction deviation (RPD) were used to evaluate the models. The R2in calibration and validation for log-transformed TP (log TP) were 0.69 and 0.65, respectively, indicating that VNIR calibration obtained in this study accounted for at least 65% of the variance in log TP using only VNIR spectra, and the high RPD of 2.82 obtained suggested that the spectral model derived in this study was suitable and robust to predict TP in a wide range of soil types, being representative of Florida soil conditions.
Overabundance of phosphorus （P） in soils and water is of great concern and has received much attention in Florida, USA. Therefore, it is essential to analyze and predict the distribution of P in soils across large areas. This study was undertaken to model the variation of soil total phosphorus （TP） in Florida. A total of 448 soil samples were collected from different soil types. Soil samples were analyzed by chemical reference method and scanned in the visible/near-infrared （VNIR） region of 350-2 500 nm. Partial least squares regression （PLSR） calibration model was developed between chemical reference values and VNIR values. The coefficient of determination （R2） and the root mean squares error （RMSE） of calibration and validation sets, and the residual prediction deviation （RPD） were used to evaluate the models. The R2 in calibration and validation for log-transformed TP （log TP） were 0.69 and 0.65, respectively, indicating that VNIR calibration obtained in this study accounted for at least 65% of the variance in log TP using only VNIR spectra, and the high RPD of 2.82 obtained suggested that the spectral model derived in this study was suitable and robust to predict TP in a wide range of soil types, being representative of Florida soil conditions.
基金
Supported by the National Natural Science Foundation of China (No. 41071159)
the Cooperative Ecosystem Studies UnitNational Resources Conservation Service (NRCS), USA
