Prediction of humic acid content and respiration activity of biogenic waste by means of Fourier transform infrared (FTIR) spectra and partial least squares regression (PLS-R) models

Fourier transform infrared (FTIR) spectroscopy has been proven to be an appropriate analytical method for the qualitative assessment of compost stability. This study focuses on quantitative determination of two time-consuming parameters: humic acid (HA) contents and respiration activity. Reactivity/stability and humification were quantified by respiration activities (oxygen uptake) and humic acid contents. These features are also reflected by a specific infrared spectroscopic pattern. Based on this relationship partial least squares regression (PLS-R) models for the prediction of respiration activities and humic acid contents were calculated. Characteristic wavenumber regions that are assigned to the biological/chemical parameter were selected for multivariate data analysis. The coefficient of determination (R²) obtained for the humic acid prediction model from infrared spectra was 87% with a root mean square error of cross-validation (RMSECV) of 2.6% organic dry matter (ODM). The prediction model for respiration activity resulted in a R² of 94% and a RMSECV for oxygen uptake of 2.9 mg g⁻¹ dry matter (DM).