The Study on Fertilization Strategy of Malt and Distiller's Grains Based on Multi-Objective Optimization

This study addresses the growing need for sustainable agricultural practices by optimizing the fertilization strategy of malt and distiller’s grains-a nutrient-rich by-product of brewing and distillation. A multi-objective optimization framework was developed to simultaneously enhance soil fertility, increase crop yield, minimize fertilizer costs, and reduce environmental pollution. The study employs a dynamic feedback model to simulate interactions between soil nutrients, microbial activity, and crop growth, integrating genetic algorithms and differential evolution to identify optimal fertilization schemes. The results indicate that the optimal combination-nitrogen (1.0 g/kg), phosphorus (0.5 g/kg), and potassium (0.5 g/kg)-significantly improves soil fertility and crop performance while lowering carbon emissions and nutrient leaching. A key innovation lies in the integration of Life Cycle Assessment (LCA) to quantify environmental impact, offering a holistic and data-driven solution. This research demonstrates that precise, algorithm-assisted fertilization planning not only supports sustainable agriculture but also provides actionable guidance for farmers and policymakers.