An integrated approach to optimizing environmental impact and crop yields in the regenerative agriculture system of Central Europe.

Achieving sustainable agriculture requires balancing high productivity with minimal environmental impact, a challenge that is ongoing for both farmers and policymakers. This study proposes an innovative approach by integrating life cycle assessment (LCA), data envelopment analysis (DEA), causal loop diagrams (CLD), and the DPSIR (Driving forces, Pressures, State, Impacts, Responses) framework to evaluating regenerative agriculture systems (RAS) in Central Europe. Focusing on wheat and maize production in Slovakia, we assessed scenarios involving different herbicides containing glyphosate and pyridine compounds, as well as the use of cow manure. LCA was first applied to quantify the environmental impacts of each scenario. These results were then used along with the crop yield data in DEA to assess environmental efficiency in the various scenarios, taking into account both environmental and economic goals. CLD and DPSIR frameworks were employed to support a systems-level interpretation of the findings. The LCA results indicated that the complete removal of two key herbicides (Scenario 4) for durum wheat and maize production led to the lowest environmental impact but also the lowest yield. In contrast, applying two key herbicides slightly increased environmental impacts but resulted in higher yields. DEA results indicate that Scenario 1, which incorporates two key herbicides, was the most environmentally efficient for durum wheat, while both Scenarios 1 and 3, which include one key herbicide, were effective for maize. Overall, while the environmental burden differences between scenarios were relatively small, the differences in crop yields were substantial. Therefore, scenarios involving at least one key herbicide proved the most environmentally and economically optimal.