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

Abstract

SUMMARYThis study aimed to evaluate the ability to use Vis-NIR spectroscopy to predict CaCO 3 in the soil and to determine the contribution of the spectral ranges and wavelengths to the prediction. A total of 180 topsoil samples (0-25 cm) of anthropogenic soils derived from Flysch deposits in Dalmatia (Croatia) were analyzed for CaCO 3 and scanned in the laboratory with an ASD FieldSpec spectroradiometer (350-2500 nm). The partial last square regression (PLSR) with leave-one-out cross-validation method was used for calibrating the Vis-NIR spectra and CaCO 3 measured in the laboratory. The CaCO 3 content in investigated soils varies within a very wide range from 186.0 to 894.7 g kg -1 and has a high an average value of 547.2 g kg -1 and normal -near symmetrical frequency distribution. Prediction parameters, the coefficient of determination (R 2 ), the ratio of performance to deviation (RPD) and the range error ratio (RER) were 0.86, 2.42 and 11.4, respectively indicating that created PLSR model was able to predict CaCO 3 content in soil with moderately successful accuracy. The prediction error of the CaCO 3 measured as the root mean square error of prediction (RMSEP) was 57.9 g kg -1. These results suggest that Vis-NIR spectroscopy in combination with PLSR is acceptable as a rapid method for quality control (screening) of the CaCO 3 content in investigated soils.

Lifting Wavelet Transform De-noising for Model Optimization of Vis-NIR Spectroscopy to Predict Wood Tracheid Length in Trees

“…Visible and near-infrared (Vis-NIR) spectroscopy has been widely applied to agriculture, life science, polymer materials, and other fields [1,2,3] because of its many advantages, including simplicity of operation, no need for sample pretreatment, real-time online monitoring, and great adaptability of the model. It has been shown that Vis-NIR spectroscopy can be used in wood science for the prediction of wood’s physical, chemical, anatomical, and mechanical properties such as moisture content, microfibril angle, bending strength, etc.…”