Optimizing cropping patterns under emission reduction constraints: Balancing food production, carbon sequestration, and profit

In view of increasing climate pressure and population growth, ensuring food security while progressing towards carbon neutrality has become a key challenge for agricultural development. Although cropping pattern optimization has been widely explored, most existing studies focus on single objectives or static configurations and rarely incorporate long-term cropping dynamics and stakeholder preferences into a unified decision framework, limiting their applicability in agricultural management. This study proposes a hybrid framework that integrates remote sensing data, agricultural systems modeling, life cycle assessment, and multi-objective optimization to identify optimal cropping patterns based on stakeholder preferences. The approach aims to maximize the yield, profitability, and carbon sequestration potential of corn and soybeans while minimizing associated carbon emissions in the typical black soil region of Northeast China. The results show that between 2008 and 2022, both continuous corn cultivation and corn–soybean rotation systems expanded, with continuous corn cultivation accounting for 60–75% of the total cultivated area, whereas continuous soybean cultivation declined steadily. Spatially, most cultivation patterns exhibited a clear northward shift. Overall, the results suggest that continuous corn cultivation can offer the most effective compromise between food production, carbon sequestration, and economic returns, provided that strict measures to reduce emissions are implemented. Among all rotation strategies, the two-year corn and one-year soybean rotation is the most effective in mitigating the adverse effects of continuous cropping while maintaining a balanced food–carbon–profit performance. In contrast, soybean cultivation offers notable environmental benefits but is constrained by relatively low yields and limited economic returns, underscoring the need for targeted optimization measures. This study provides actionable insights for designing sustainable crop patterns that balance agricultural productivity with climate mitigation goals.