Advanced Characterization of Organic Matter Decaying during Composting of Industrial Waste Using Spectral Methods

To date, compost maturation monitoring is carried out by physical-chemical and microbiological analysis, which could be considered an overweening consumption of time and products. Nowadays, spectroscopy is chosen as a simple tool for monitoring compost maturity. In the present investigation, spectroscopy analysis was performed in the interest of corroborating the compost maturity. This goal was achieved by using the X-ray diffraction, infrared spectroscopy, and scanning electron microscopy. X-ray diffraction analysis showed the presence of the cellulose fraction in compost samples. At the same time, the intensity of pics decreased depending on composting time, thus proving that there was organic matter degradation. Infrared and scanning electron microscopy analysis allow for confirming these results. The correlation between spectroscopies analysis and physical-chemical properties was employed by partial least squares-regression (PLS-R) model. PLS-R model was applied to build a model to predict the compost quality depending on the composting time, the results obtained show that all the parameters analysis are well predicted. The current study proposed that final compost was more stabilized compared with the initial feedstock mixture. Ultimately, spectroscopy techniques used allowed us to confirm the physical-chemical results obtained, and both of them depict maturity and stability of the final compost, thus proving that spectral techniques are more reliable, fast, and promising than physical-chemical analyses.

Automated summary

Spectroscopy techniques were used to monitor compost maturity, with X-ray diffraction, infrared spectroscopy, and scanning electron microscopy confirming the presence of cellulose and organic matter degradation. A PLS-R model was employed to predict compost quality based on composting time, showing accurate predictions for all parameters analyzed. The study concluded that spectral techniques are more reliable, fast, and promising for assessing compost maturity compared to physical-chemical analyses.