Utilization of the mid-infrared spectroscopy in a county-scale soil survey: The case of Pest County, Hungary - Mohammed Ahmed MohammedZein; Brian Rotich; Elsadig Omer; Nada Eldawwy; Adam Csorba (Soil Advances)
Soil surveys are required to satisfy the growing need for soil data. Their methods have evolved to incorporate alternative laboratory technologies that are fast, cost-effective, and environmentally friendly. This study aimed to test the application of a Mid-Infrared (MIR) spectroscopy technique in soil survey at the county level. A total of 405 archived soil samples, corresponding to genetic horizons of 105 profiles from Pest County of Hungary, were prepared and scanned, after which the spectra were processed with the OPUS software. Partial Least Square Regression (PLSR) models were built for Soil Organic Carbon (SOC), Calcium Carbonate (CaCO3), sand, clay, silt, Cation Exchange Capacity (CEC) and soil pH. Two accuracy metrics, namely, Coefficient Determination (R2) and Root Mean Square Error (RMSE), were used to evaluate the accuracy of MIR models. Validation results showed that four soil properties, including SOC, sand, clay and silt, were predicted with a high accuracy level (R2=0.82–0.90), two soil properties including CaCO3 and pH were predicted with a medium level of accuracy (R2=0.71–0.74) and CEC was predicted with a fair level of accuracy (R2=0.65). Consequently, SOC, sand, clay and silt had an acceptable level of accuracy to be applied in soil surveys, while CaCO3 and pH demonstrated a marginal level of accuracy for soil surveys, and CEC was deemed marginal and inadequate for effective soil survey purposes. These findings affirm that MIR spectroscopy is a valuable tool for soil survey activities, especially when numerous soil samples are involved.