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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Pasquale Garofalo & Alessandro Vittorio Vonella, 2025. "A Multi-Objective Evaluation Tool (MUVT) for Optimizing Inputs in Cropping Systems: A Case Study on Three Herbaceous Crops," Sustainability, MDPI, vol. 17(7), pages 1-24, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3030-:d:1623176
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    as
    1. Raes, Dirk & Fereres, Elias & García Vila, Margarita & Curnel, Yannick & Knoden, David & Çelik, Sema Kale & Ucar, Yusuf & Türk, Mevlüt & Wellens, Joost, 2023. "Simulation of alfalfa yield with AquaCrop," Agricultural Water Management, Elsevier, vol. 284(C).
    2. Rosa Francaviglia & Claudia Di Bene, 2019. "Deficit Drip Irrigation in Processing Tomato Production in the Mediterranean Basin. A Data Analysis for Italy," Agriculture, MDPI, vol. 9(4), pages 1-14, April.
    3. Man Li & Wenchao Xu & Tingju Zhu, 2019. "Agricultural Water Allocation under Uncertainty: Redistribution of Water Shortage Risk," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(1), pages 134-153.
    4. Farhana Bibi & Azizur Rahman, 2023. "An Overview of Climate Change Impacts on Agriculture and Their Mitigation Strategies," Agriculture, MDPI, vol. 13(8), pages 1-15, July.
    5. Wellens, Joost & Raes, Dirk & Fereres, Elias & Diels, Jan & Coppye, Cecilia & Adiele, Joy Geraldine & Ezui, Kodjovi Senam Guillaume & Becerra, Luis-Augusto & Selvaraj, Michael Gomez & Dercon, Gerd & H, 2022. "Calibration and validation of the FAO AquaCrop water productivity model for cassava (Manihot esculenta Crantz)," Agricultural Water Management, Elsevier, vol. 263(C).
    6. Xiao, Chao & Zou, Haiyang & Fan, Junliang & Zhang, Fucang & Li, Yi & Sun, Shikun & Pulatov, Alim, 2021. "Optimizing irrigation amount and fertilization rate of drip-fertigated spring maize in northwest China based on multi-level fuzzy comprehensive evaluation model," Agricultural Water Management, Elsevier, vol. 257(C).
    7. Wang, Haidong & Cheng, Minghui & Zhang, Shaohui & Fan, Junliang & Feng, Hao & Zhang, Fucang & Wang, Xiukang & Sun, Lijun & Xiang, Youzhen, 2021. "Optimization of irrigation amount and fertilization rate of drip-fertigated potato based on Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation methods," Agricultural Water Management, Elsevier, vol. 256(C).
    8. Garofalo, Pasquale & Campi, Pasquale & Vonella, Alessandro Vittorio & Mastrorilli, Marcello, 2018. "Application of multi-metric analysis for the evaluation of energy performance and energy use efficiency of sweet sorghum in the bioethanol supply-chain: A fuzzy-based expert system approach," Applied Energy, Elsevier, vol. 220(C), pages 313-324.
    9. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(C).
    10. Pasquale Garofalo & Liliana Gaeta & Carolina Vitti & Luisa Giglio & Rita Leogrande, 2025. "Optimizing Water Footprint, Productivity, and Sustainability in Southern Italian Olive Groves: The Role of Organic Fertilizers and Irrigation Management," Land, MDPI, vol. 14(2), pages 1-28, February.
    11. Uygan, Demet & Cetin, Oner & Alveroglu, Volkan & Sofuoglu, Aytug, 2021. "Improvement of water saving and economic productivity based on quotation with sugar content of sugar beet using linear move sprinkler irrigation," Agricultural Water Management, Elsevier, vol. 255(C).
    12. Bao-Li Miao & Ying Liu & Yu-Bing Fan & Xue-Jiao Niu & Xiu-Yun Jiang & Zeng Tang, 2023. "Optimization of Agricultural Resource Allocation among Crops: A Portfolio Model Analysis," Land, MDPI, vol. 12(10), pages 1-18, October.
    13. Vedula, S. & Mujumdar, P.P. & Chandra Sekhar, G., 2005. "Conjunctive use modeling for multicrop irrigation," Agricultural Water Management, Elsevier, vol. 73(3), pages 193-221, May.
    14. Dhouib, M. & Zitouna-Chebbi, R. & Prévot, L. & Molénat, J. & Mekki, I. & Jacob, F., 2022. "Multicriteria evaluation of the AquaCrop crop model in a hilly rainfed Mediterranean agrosystem," Agricultural Water Management, Elsevier, vol. 273(C).
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