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 mâ1), 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 mâ1) 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