Non-invasive indicators in the poultry manure composting process

Abstract

Purpose: The study presents how to develop and optimize a spectral measurement methodology for monitoring the composting process of broiler and hen manure using zeolite. Models were set up to determine the pH, electrical conductivity (EC, dS m−1), 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 (1 w/w%) for 62 days. During the experiment, samples were taken to determine MC, pH, and EC measured from a 10% 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 λ2115/λ1993 index-based estimation model with good performance (RMSE 2.42 m/m%) is suggested to measure the moisture content in composts. The electrical conductivity (RMSE 1.38 dS m−1) and pH (RMSE 0.28 pH) are recommended to monitor with the λ812/λ941 index-based models. Conclusion: Based on the results, identified indices are suitable for determining the physico-chemical parameters of compost, which is of great importance for intensive, semi-intensive, and extensive composting plants, as spectral analyses can replace time-consuming analytical analyses. Research Highlights: Non-destructive monitoring of zeolite-amended broiler and hen manure composting λ2115/λ1993 index for moisture monitoring in compost λ812/λ941 index for electrical conductivity and pH monitoring in compost

Keywords

• ec and ph prediction indices
• mc
• nir-spectroscopy
• poultry manure management
• vis-spectroscopy