New artificial network model to estimate biological activity of peat humic acids.

Purpose: This article focuses on new method to estimate biological activity of peat humic acids (HAs) using artificial neural network (ANN) to process spectroscopic measurements in infrared and visible ranges. Conventional approaches generally rely on biological models and direct detection of chemical substances related to bioactivity. These methods proved to be accurate and reliable, but at the expense of speed and simplicity.

Physicochemical Characterization and Antioxidant Activity of Humic Acids Isolated from Peat of Various Origins.

Although humic acids (HAs) from peat exhibit various therapeutic properties, there is little information available concerning their physicochemical and antioxidant properties. To address this issue, nine different types of peat, including oligotrophic, mesotrophic, and minerotrophic peat samples, were used for isolation of HA fractions by basic (HAb) and pyrophosphate (HAp) extractions. Physical parameters of the HAs were analyzed by UV-Vis, fluorescent, infrared (IR), and electron paramagnetic resonance (EPR) spectroscopy.