Paper Title
Determination Of Several Soil Properties Based On Ultra-Violet, Visible, And Near-Infrared Reflectance Spectroscopy

Abstract
Soil is a fundamental natural resource which people rely on for theproduction of food, fiber, and energy. Given the importance of soils, there is a need forregular monitoring to detect changes in its status so as to implementappropriate management in the event of degradation. Application of ultra-violet (UV),visible (VIS) and near-infrared (NIR) spectroscopy for prediction of soil properties offer a cost and time effective approach for evaluation of soil structural quality. The main objective ofthis study was to evaluate the ability of reflectance spectroscopy in the UV, VIS and NIR ranges to predictseveral soil properties simultaneously. Soil samples (n=210in 15cm depth from surface) were used forsimultaneous estimation of pH, electrical conductivity (EC), air-dry gravimetric water content, organiccarbon (OC), total nitrogen (TN), free iron, clay, sand, and silt contents, cation exchange capacity (CEC), and exchangeablecalcium (Ca), magnesium (Mg), potassium (K), and sodium (Na). After removal of outliersidentified by principal components analysis (PCA), 75% of the sample set was randomly selectedfor calibration (n=157) and theremaining used for validation.Modified partial least squares (PLS) regressionwith cross-validation was used to develop prediction models. The reliability of the models was assessedusing the coefficient of determination in validation (R2V) and the ratio of standard deviation of the referencedata in the validation set to the standard error of prediction (RPDV). Excellent modelswere achieved for TN,OC and pH (RPD≥3.5, R2c ≥ 0.91). Good modelswere obtained for EC and CEC(RPD from 2 to 3, R2c≥ 0.75), and moderate capability for prediction of particle size and exchangeable cations (RPD from 1.5 to 1.99, R2c ≥ 0.68).Soil spectra produced acceptable models for predicting relevant soil structural indicators, and the mean soil spectra were different between soil structural classes. Therefore VNIRS has the potential as a non-destructive and cost-efficient tool for rapid determination ofsoil quality indicators. Key-words- NIR spectroscopy, PLS regression, soil properties, UV-VIS spectroscopy.