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Original Article

Non-invasive indicators in the poultry manure composting process



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

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
  • λ21151993 index for moisture monitoring in compost
  • λ812941 index for electrical conductivity and pH monitoring in compost


Graphical Abstract