Determining relative values of pH, CECe, and OC in agricultural soils using functional enhanced derivative spectroscopy (FEDS0) method in the mid-infrared region

Soils are a vital and non-renewable natural resource that provide the nutrients and adequate conditions for plants growth, as well to support several economic activities. Optical spectroscopy has emerged as a reliable technique for determining multiple physicochemical properties of organic and inorganic species in agricultural industries, that employs mathematical and statistical tools to develop new methodologies of spectral analysis easily implementable in remote and in-field applications. This is the case of the Functionally-enhanced derivative spectroscopy (FEDS and FEDS0), which uses operational transformations to extract hidden information from overlapping optical signals generated by the diverse components of solid and liquid matrices. In this study, an algorithm based on FEDS has been applied for optical analysis of agricultural soils in the spectral range from 1200 to 675 cm(-1), to estimate chemical properties related to nutritional and fertility state of 65 soil samples used for planting of cotton, yuca (Manihot Esculenta), and banana in Bolivar and Cordoba departments in Colombia. The results demonstrate that it is possible to establish a correlation between the Pearson's coefficient obtained from two FEDS0 spectra associated to ATR-FTIR signals (r(F) > - 0.85), and their relative values of effective cation exchange capacity, pH and organic carbon content, with a ratio of performance to deviation higher to 2.0 in all cases (RPD > 2.0). This is possible due to high dependence of optical signal with CECe values, which are in turn conditioned by pH level and OC content in the soil samples considered.

Automated summary

Soils play a crucial role in supporting plant growth and various economic activities. Optical spectroscopy, specifically the Functionally-enhanced derivative spectroscopy (FEDS and FEDS0) analyzed in this study, is a reliable technique that utilizes mathematical and statistical tools to extract hidden information from optical signals and determine the physicochemical properties of organic and inorganic species in agricultural soils. The results demonstrate a correlation between the FEDS0 spectra and the chemical properties related to nutritional and fertility state of the soil samples, indicating the potential of optical analysis for assessing soil quality.