Prediction of soil available phosphorous content using spectra-radiometer and GIS in southern of Iraq

In this study, soil samples were collected from two locations: Samawa and Rumetha in southern Iraq. The samples from each location were split into two datasets: calibration set and validation set. A representative soil sample for each location was chosen for application of 5 levels of potassium phosphate fertilizer in 3 replications. Vis-NIR reflectance (350-2500 nm) and GIS-Kriging were used in combination with Partial Least Square (PLS) to predict soil available P. According to the results of this study, three wavelength regions were reported as a main sensitive bands for soil available P. The best prediction ability was achieved for Rumetha location at 1400-1600 nm with an R2 of 0.85, lowest RMSE of 1.405, and lowest standard deviation of 1.577 and for Samawa location at 900-1000 nm with an R2 of 0.81, RMSE of 2.666 and lowest standard deviation of 2.879. The capability of the Vis-NIRSbased and GIS-Kriging prediction models were evaluated by using cross-validation values Q2 and R2 between measured and predicted soil available P of each model. The selection principle parameters showed best prediction by NIRS-models with an R2 of 0.79 for Rumetha and 0.75 for Samawa location. While the prediction ability of GIS-Kriging models were in worst with an Q2 of 0.17 for Samawa location and reasonable with an Q2 of 0.58 for Rumetha location. These empirically result is an evident of the superiority of NIRS-based models for prediction soil available P over the GIS-Kriging models