A Multi-Objective Evaluation Tool (MUVT) for Optimizing Inputs in Cropping Systems: A Case Study on Three Herbaceous Crops

Pasquale Garofalo () and Alessandro Vittorio Vonella
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Pasquale Garofalo: Council for Agricultural Research and Economics, Research Centre for Agriculture and Environment (CREA-AA), Via C. Ulpiani 5, 70125 Bari, Italy
Alessandro Vittorio Vonella: Council for Agricultural Research and Economics, Research Centre for Agriculture and Environment (CREA-AA), Via C. Ulpiani 5, 70125 Bari, Italy

Sustainability, 2025, vol. 17, issue 7, 1-24

Abstract: This study introduces the Multi-Objective Evaluation Tool (MUVT), developed to optimize resource management in cropping systems by balancing productivity, economic returns, and environmental sustainability. Using MUVT, the research examines three key aspects of irrigation management: the impact of irrigation strategies on agro-environmental parameters (e.g., yield, water use efficiency, and economic performance), the integration of these parameters into a multi-objective framework to identify optimal irrigation volumes, and the ability to adjust irrigation strategies by prioritizing sustainability over productivity. MUVT was tested on three crops—processing tomato, maize, and sugar beet—under varying irrigation scenarios, with the dynamics of certain crop system variables in relation to irrigation management assessed through AquaCrop simulations. Results indicate that optimal irrigation levels range between 400 and 500 mm for maize and tomato and 300 and 400 mm for sugar beet when balancing productivity and sustainability. When environmental sustainability is prioritized, recommended irrigation volumes decrease to 300 mm for maize, 300–400 mm for tomato, and 200 mm for sugar beet. Among the crops analyzed, maize showed the best overall performance, followed by tomato and sugar beet. By systematically evaluating trade-offs between agronomic and environmental factors, MUVT provides a flexible decision-support system, enabling farmers and policymakers to make data-driven decisions for improving resource efficiency while ensuring economic and environmental sustainability.

Keywords: AquaCrop; irrigation management; maize; sugar beet; processing tomato; agricultural sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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