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Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study

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  • Mardani Najafabadi, Mostafa
  • Ziaee, Saman
  • Nikouei, Alireza
  • Ahmadpour Borazjani, Mahmoud

Abstract

The economic, technical and strategic factors are the three most important factors in examining the cropping patterns in Iran. Iran is geographically located in a part of the planet with specific climate constraints. Drought is one of the constraints that has been a major challenge to agricultural development for many years and has always been the subject of discussions and investigations. On the other hand, constraints such as agricultural soils, economic factors, climate change, agricultural workforce, etc., multiply the production challenges in the country. Despite such constraints, planning a coherent and targeted program for the cultivation of crops and overcome the existing problems is inevitable. The present study introduced a model for optimization of regional cropping pattern decisions, which is one of the subsets of the Multi-Objective Structural Planning (MOSP) approach, and addressed different objectives, such as economic, social and environmental objectives, separately and jointly. However, it is important to address the exchange of crops in different areas in order to achieve the fundamental objectives of determining the optimal cropping pattern. Therefore, in the proposed model of optimal regional cropping pattern, issues such as the transportation of crops and, consequently, virtual water and energy exchanges were also considered. In order to evaluate the proposed model, agricultural arable lands located in the political-geographic divisions of 23 counties of Isfahan province (Iran) were selected for examination. The results showed that in the main groups of grains and forage, a significant reduction was observed in the optimal crop area of the multi-objective model by 26% and 5%, respectively. Increasing the crop area of horticultural products by 10% in the optimal pattern of multi-objective model was another important factor in the analysis of the results. In general, in order to achieve the economic, social and environmental objectives mentioned in this study within the framework of a multi-objective planning, a 16% reduction in the level of the crop area in Isfahan province is inevitable. The results of this measure are reduction in the irrigation water consumption by 17%, increase in the profit by 58% and increase in the production by 11%. Regarding the fact that in the structural planning of cropping pattern, different and sometimes conflicting objectives are considered and the compromise between the objectives is possible in the multi-objective structural planning model, the decision makers are recommended to use this model.

Suggested Citation

  • Mardani Najafabadi, Mostafa & Ziaee, Saman & Nikouei, Alireza & Ahmadpour Borazjani, Mahmoud, 2019. "Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study," Agricultural Systems, Elsevier, vol. 173(C), pages 218-232.
    • Handle: RePEc:eee:agisys:v:173:y:2019:i:c:p:218-232
    DOI: 10.1016/j.agsy.2019.02.006
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    1. de Koeijer, T. J. & Wossink, G. A. A. & Smit, A. B. & Janssens, S. R. M. & Renkema, J. A. & Struik, P. C., 2003. "Assessment of the quality of farmers' environmental management and its effects on resource use efficiency: a Dutch case study," Agricultural Systems, Elsevier, vol. 78(1), pages 85-103, October.
    2. Zeng, Xieting & Kang, Shaozhong & Li, Fusheng & Zhang, Lu & Guo, Ping, 2010. "Fuzzy multi-objective linear programming applying to crop area planning," Agricultural Water Management, Elsevier, vol. 98(1), pages 134-142, December.
    3. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    4. Lundberg, Liv & Jonson, Emma & Lindgren, Kristian & Bryngelsson, David & Verendel, Vilhelm, 2015. "A cobweb model of land-use competition between food and bioenergy crops," Journal of Economic Dynamics and Control, Elsevier, vol. 53(C), pages 1-14.
    5. Jones, D. & Barnes, E. M., 2000. "Fuzzy composite programming to combine remote sensing and crop models for decision support in precision crop management," Agricultural Systems, Elsevier, vol. 65(3), pages 137-158, September.
    6. Biswas, Animesh & Pal, Bijay Baran, 2005. "Application of fuzzy goal programming technique to land use planning in agricultural system," Omega, Elsevier, vol. 33(5), pages 391-398, October.
    7. Venables, Anthony J. & Limao, Nuno, 2002. "Geographical disadvantage: a Heckscher-Ohlin-von Thunen model of international specialisation," Journal of International Economics, Elsevier, vol. 58(2), pages 239-263, December.
    8. Karami, Ayatollah & Esmaeili, Abdoulkarim & Najafi, Bahadin, 2012. "Assessing effects of alternative food subsidy reform in Iran," Journal of Policy Modeling, Elsevier, vol. 34(5), pages 788-799.
    9. Francisco, Sergio R. & Ali, Mubarik, 2006. "Resource allocation tradeoffs in Manila's peri-urban vegetable production systems: An application of multiple objective programming," Agricultural Systems, Elsevier, vol. 87(2), pages 147-168, February.
    10. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    11. Pennington, Derric N. & Dalzell, Brent & Nelson, Erik & Mulla, David & Taff, Steve & Hawthorne, Peter & Polasky, Stephen, 2017. "Cost-effective Land Use Planning: Optimizing Land Use and Land Management Patterns to Maximize Social Benefits," Ecological Economics, Elsevier, vol. 139(C), pages 75-90.
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    2. Li, Mo & Fu, Qiang & Singh, Vijay P. & Liu, Dong & Li, Tianxiao & Zhou, Yan, 2020. "Managing agricultural water and land resources with tradeoff between economic, environmental, and social considerations: A multi-objective non-linear optimization model under uncertainty," Agricultural Systems, Elsevier, vol. 178(C).
    3. Yuxiang Ma & Min Zhou & Chaonan Ma & Mengcheng Wang & Jiating Tu, 2021. "Hybrid Economic-Environment-Ecology Land Planning Model under Uncertainty—A Case Study in Mekong Delta," Sustainability, MDPI, vol. 13(19), pages 1-22, October.
    4. Nikouei, Alireza & Asgharipour, Mohammad Reza & Marzban, Zahra, 2022. "Modeling land allocation to produce crops under economic and environmental goals in Iran: a multi-objective programming approach," Ecological Modelling, Elsevier, vol. 471(C).
    5. Karner, Katrin & Schmid, Erwin & Schneider, Uwe A. & Mitter, Hermine, 2021. "Computing stochastic Pareto frontiers between economic and environmental goals for a semi-arid agricultural production region in Austria," Ecological Economics, Elsevier, vol. 185(C).
    6. Mostafa Mardani Najafabadi & Niloofar Ashktorab, 2023. "Mathematical programming approaches for modeling a sustainable cropping pattern under uncertainty: a case study in Southern Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9731-9755, September.
    7. Mardani Najafabadi, Mostafa & Magazzino, Cosimo & Valente, Donatella & Mirzaei, Abbas & Petrosillo, Irene, 2023. "A new interval meta-goal programming for sustainable planning of agricultural water-land use nexus," Ecological Modelling, Elsevier, vol. 484(C).
    8. Dariane, A.B. & Ghasemi, M. & Karami, F. & Azaranfar, A. & Hatami, S., 2021. "Crop pattern optimization in a multi-reservoir system by combining many-objective and social choice methods," Agricultural Water Management, Elsevier, vol. 257(C).
    9. Ana Esteso & M. M. E. Alemany & Angel Ortiz & Shaofeng Liu, 2022. "Optimization model to support sustainable crop planning for reducing unfairness among farmers," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(3), pages 1101-1127, September.
    10. Zhang, Zepeng & Wang, Qingzheng & Guan, Qingyu & Xiao, Xiong & Mi, Jimin & Lv, Songjian, 2023. "Research on the optimal allocation of agricultural water and soil resources in the Heihe River Basin based on SWAT and intelligent optimization," Agricultural Water Management, Elsevier, vol. 279(C).
    11. Huihui Zheng & Zhiting Sang & Kaige Wang & Yan Xu & Zhaoyang Cai, 2022. "Distribution of Irrigated and Rainfed Agricultural Land in a Semi-Arid Sandy Area," Land, MDPI, vol. 11(10), pages 1-13, September.
    12. Mostafa Mardani Najafabadi & Abbas Mirzaei & Hassan Azarm & Siamak Nikmehr, 2022. "Managing Water Supply and Demand to Achieve Economic and Environmental Objectives: Application of Mathematical Programming and ANFIS Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3007-3027, July.
    13. Nouri, Milad & Homaee, Mehdi & Pereira, Luis S. & Bybordi, Mohammad, 2023. "Water management dilemma in the agricultural sector of Iran: A review focusing on water governance," Agricultural Water Management, Elsevier, vol. 288(C).

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