Mapping compositional trends in biocrude from mixed food waste: methodological insights from regression and neural networks

Key Points

• Biocrude composition varies significantly based on initial food waste characteristics, indicating diverse recycling potential.
• Analysis identified trends using regression and neural networks, showing a clear correlation in compositional outputs.
• Data-driven insights were drawn from mixed food waste samples to enhance biocrude production efficiency and sustainability.
• The findings may enable more effective recycling strategies, making food waste utilization more practical and beneficial.