In the past two decades, the interest of using visible-near infrared (Vis-NIR) spectroscopy for determining soil properties has increased. Soil spectral reflectance is an alternative approach for soil properties determination and has the advantage to be rapid and non-destructive. To obtain reliable prediction of soil properties multivariate calibration techniques as Partial Least Squares Regression (PLSR) are commonly used to correlate the spectra with the studied soil properties.The aim of the paper was to evaluate the potential of Vis-NIR spectroscopy and PLSR for prediction of chemical and physical soils properties as organic matter (OM), sand, silt and clay, and calcium carbonate (CaCO3) in a sample area of southern Italy. Results of multivariate calibration were satisfactory with high values of coefficient of determination ( ) and values of residual predictive deviation (RPD) greater than of 2.
Using Vis-NIR spectroscopy to assess some soil properties in a sample area of southern Italy
Conforti Massimo;Buttafuoco Gabriele
2013
Abstract
In the past two decades, the interest of using visible-near infrared (Vis-NIR) spectroscopy for determining soil properties has increased. Soil spectral reflectance is an alternative approach for soil properties determination and has the advantage to be rapid and non-destructive. To obtain reliable prediction of soil properties multivariate calibration techniques as Partial Least Squares Regression (PLSR) are commonly used to correlate the spectra with the studied soil properties.The aim of the paper was to evaluate the potential of Vis-NIR spectroscopy and PLSR for prediction of chemical and physical soils properties as organic matter (OM), sand, silt and clay, and calcium carbonate (CaCO3) in a sample area of southern Italy. Results of multivariate calibration were satisfactory with high values of coefficient of determination ( ) and values of residual predictive deviation (RPD) greater than of 2.| File | Dimensione | Formato | |
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Descrizione: Conforti and Buttafuoco - sib2013
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