10–14 Nov 2025
Office of Grants and Research
Africa/Accra timezone

Chemometric and model-driven assessment of compost quality for environmental sustainability in Ghana

Not scheduled
45m
Office of Grants and Research

Office of Grants and Research

Poster Presentation Climate Resilience, Environmental Sustainability, and Food Systems

Speaker

Prof. Kwasi Obiri-Danso (Department of Theoretical and Applied Biology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana)

Description

Composting provides a sustainable pathway for organic waste management, converting biodegradable residues into nutrient-rich soil amendments that enhance soil fertility and support climate-smart agriculture. This study applied a chemometric and model-driven framework to evaluate compost quality across 20 randomly selected facilities in Ghana, integrating physicochemical, microbial, and energetic parameters. Compost pH ranged from 8.65–9.30, bulk density from 710.10–792.00 kg/m³, and organic matter content averaged 24.94%. Electrical conductivity (1.10–1.96 dS/m) remained within acceptable agronomic limits. Nutrient composition was favourable, with nitrogen (0.78–1.98%), phosphorus (0.47–0.99%), and potassium (0.65–0.93%) supporting its role as a fertilizer substitute. Carbon-to-nitrogen ratios (mean: 10.32) were inversely related to nitrogen availability, which reached up to 2.48% in more stabilized composts. Microbial analysis confirmed significant pathogen inactivation: faecal coliforms declined by 94.5% (117 to 6.5 cfu/g), while Escherichia coli and Salmonella spp. were completely eliminated, reducing the pathogenic index from 0.427 to 0.013 (p < 0.0001). Heavy metals, including arsenic (0.01–0.21 mg/kg) and cadmium (0.04–0.18 mg/kg), remained within permissible thresholds, although sporadic variations highlight the need for stricter quality monitoring. Advanced statistical analysis revealed significant effects of composting methods (F = 5373.30, p < 0.0001) and facility conditions (F = 10746.51, p < 0.0001) on compost quality, with strong interaction effects (F = 10190.31, p < 0.0001). Principal Component Regression extracted five components explaining 81.97% of total variance, with predictive strength (R² = 0.82; CV R² = 0.75 ± 0.08), demonstrating the robustness of chemometric models. The findings highlight the potential of standardized, model-based assessments to ensure compost safety, optimize agronomic use, and strengthen Ghana’s composting industry and general environmental sustainability.

Primary author

Ebenezer Ebo Yahans Amuah (Department of Environmental Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana; Department of Civil Engineering, Takoradi Technical University, P. O. Box 256, Takoradi, Ghana)

Co-authors

Prof. Bernard Fei-Baffoe (Department of Environmental Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana) Dr Kodwo Miezah (Department of Environmental Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana) Dr Yaw Amo Sarpong (Bureau of Integrated Rural Development (BIRD), Kwame Nkrumah University of Science and Technology, Kumasi, Ghana) Dr Lyndon Nii Adjiri Sackey (Department of Environmental Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana) Dr Raymond Webrah Kazapoe (Department of Geological Engineering, University for Development Studies, Nyankpala, Ghana) Prof. Kwasi Obiri-Danso (Department of Theoretical and Applied Biology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana)

Presentation materials

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