Application of composite microbial agents obtained through quadratic regression orthogonal design in green waste composting

Incorporating microbial agents to enhance lignocellulose degradation in green waste composting is crucial for the efficient utilization of green waste resources. However, determining the optimal ratio of different microbial agents in composting and understanding the relationship between microorganism combinations and their ability to degrade lignocellulose remain challenging. This study employed a quadratic regression orthogonal design experiment to identify the optimal ratio of two microbial strains. A mathematical model was developed to determine the optimal ratio of composite microbial agents. The effectiveness of these microbial agents was verified in actual composting and compared with monobacterial strains and EM microbial agents. The statistical significance of the quadratic regression orthogonal design was confirmed (p < 0.05), demonstrating its suitability for modeling microbial interactions in lignocellulose degradation. The observed combined lignin and cellulose decomposition rate in the experimental group was 37.4% after adding the composite microbial agents. These results highlight the applicability of the quadratic regression orthogonal test for optimizing the proportion of composite microbial agents, thereby promoting composting efficiency, and improving the quality of compost products.