Visible-near infrared reflectance spectroscopy for assessment of soil properties in a semi-arid area of Turkey

Potential of Spectroradiometry to Classify Soil Clay Content

“…Comparing the laboratory particle-size analysis with DRS prediction for the clay content, Kuang et al (2015) found a Kappa index of 0.48. To predict the soil texture and other properties in a semi-arid area of northern Turkey, Bilgili et al (2010) used DRS. These authors used the Kappa index as an indicator of similarity between laboratory results and DRS, obtaining a value of 0.68 for the prediction of the textural classes.…”

On-line measurement of soil properties without direct spectral response in near infrared spectral range

“…Spectra were subsequently subjected to Savitzky-Golay first derivation (Martens and Naes, 1989). This transformation procedure generally intensifies the absorption characteristics indicative of soils properties, and diminishes variation among spectra (Volkan et al, 2010). This method enabled the computation of the first or higher-order derivatives, including a smoothing factor, which determines how many adjacent variables should be used to estimate the polynomial approximation used for derivatives.…”

“…The PLSR with leave-oneout cross-validation was carried out using Unscrambler 7.8 software (Camo Inc., Oslo, Norway) to generate the calibration models relating soil independent variables (wavelengths) of the diffuse reflectance spectra to each soil parameter. PLSR performs particularly well, compared with other multivariate statistical methods, when there is a high dimensional correlation between variables, which is the case for soil spectral data (Volkan et al, 2010). Also, PLSR is favoured because it requires fewer components to explain the variance in the response, due to the relation that this method establishes between response and predictor variables, and its results are more interpretable .…”

“…literature, sodium (Na ex ) and potassium (K ex ) are among the most difficult properties to be measured with the NIR spectroscopy (Malley et al, 1999;Chang et al, 2001;Zornoza et al, 2008;Pirie et al, 2005;Dunn et al, 2002;Shepherd & Walsh, 2002;Islam et al, 2003;Volkan et al, 2010;. For the same soil property, laboratory vis-NIR methods achieved higher accuracy as compared to measurement under field soil conditions, particularly with on-line vis-NIR sensors Kuang et al, 2012).…”

Estimation of Calcium Carbonate in Anthropogenic Soils on Flysch Deposits From Dalmatia (Croatia) Using Vis-Nir Spectroscopy

“…Our results show better prediction accuracy of CaCO 3 content compared to study of Volkan Bilgili et al (2010) RPD 8.6 for data set with carbonate range of 0.0-84.9 g/100 g of soil and mean value of 16.1 g/100 g of soil. The possible factors of the relatively large differences in the accuracy of the CaCO 3 content estimation are related mainly to nature of soil as a very complex mix of the mineral and organic compounds, parent material and calibration methods.…”