Prediction of Adsorbed Phosphate, Clay and Iron Oxide Contents, Using Diffuse Reflectance Spectroscopy.

Traditional technologies for measuring adsorbed phosphate (Pads), clay and iron oxide contents and other soil attributes of agronomic importance are relatively unfeasible when large areas are mapped, with the aim of the characterization of spatial variability. This pushes the scientific society to develop methodologies able to assess these attributes within the landscape quickly, nondestructively, and not expensive. The diffuse reflectance spectroscopy (DRS) has been used to the characterization of soil attributes in large areas. The objective of this study was to evaluate the ability of DRS to estimate  Pads, clay,  Fe extracted by dithionite-citrate-bicarbonate (Fed), contents of goethite (Gt) and hematite (Hm) in Oxisols (Typic Hapludox and Typic Eutrudox) in the São Paulo State, Brazil. Soil samples were collected in the transect each 25 m (100 samples) (dataset 1). Beside the transect, an area of 500 hectares was sampled totaling 206 samples ( dataset 2 ). The soil samples (dataset 1) were taken to the laboratory for chemical, physical and mineralogical analysis and DRS spectra were obtained over 380-2300 nm. Chemometric calibration and validation (using a one-out cross validation procedure) were performed on absorbance data [Log10 (1/Reflectance)] by partial least-squares regression (PLSR) analysis using the dataset 1. Values of dataset 2 were so estimated by calibrated models. The calibration efficiency was evaluated via determination coefficient (R²), RMSE and the ratio performance deviation (RPD). The DRS was effective in predicting the attributes studied whereas the obtained models for the prediction of clay, Fed and Hm with greater accuracy (RPD> 1.4) were calibrated in the visible (380-800 nm) and to predict Pads, were calibrated in the visible + near infrared (801-2300 nm). Predicted values allowed the assessment of the soil attributes and their spatial variability in a production area.