Non-invasive indicators in the poultry manure composting process

Purpose: The study presents how to develop and optimize a spectral measurement methodology for monitoring thecomposting process of broiler and hen manure using zeolite. Models were set up to determine the pH, electrical conductivity (EC, dS m-۱), and moisture content (MC, w/w%) from reflectance data using spectral indices to establish a rapid, noninvasive, non-destructive method for the monitoring of the composting process.Method: An open composting experiment was set up, in which a mixture of broiler and hen manure was composted with a zeolite additive (۱ w/w%) for ۶۲ days. During the experiment, samples were taken to determine MC, pH, and EC measured from a ۱۰% distilled water extract. Principal component analysis (PCA) was performed for the indices to determine the wavelength ranges that could be used to test the material quality of the compost.Results: Spectral index-based monitoring methods were developed. The λ۲۱۱۵/λ۱۹۹۳ index-based estimation modelwith good performance (RMSE ۲.۴۲ m/m%) is suggested to measure the moisture content in composts. The electricalconductivity (RMSE ۱.۳۸ dS m-۱) and pH (RMSE ۰.۲۸ pH) are recommended to monitor with the λ۸۱۲/λ۹۴۱ index-basedmodels.Conclusion: Based on the results, identified indices are suitable for determining the physico-chemical parameters ofcompost, which is of great importance for intensive, semi-intensive, and extensive composting plants, as spectral analyses can replace time-consuming analytical analyses.

Keywords:

MC , EC and pH prediction indices , Poultry manure management , VIS-spectroscopy , NIR-spectroscopy