Developing environmentally friendly cropping pattern with a multi-objective planning approach in Sari County
Subject Areas :
Agricultural Economics Research
ghasem layani
1
,
Abdollah Darzi
2
,
Ali Motevali
3
,
Mostafa Bagherian- Jelodar
4
,
Mahdi Kaikha
5
,
Mehdi Nadi
6
,
Ali Asghar Firouzjaeian
7
,
HAMID AMIRNEJAD
8
,
Hemmatollah Pirdashti
9
1 - Postdoctoral Researcher, Sari Agricultural Sciences and Natural Resources University and Assistant Professor of Management and Rural Development Department, Shahrekord University
2 - Water Engineering Department, Sari Agricultural Sciences and Natural Resources University
3 - Department of Mechanics of Biosystem Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
4 - Department of Social Sciences, Payame Noor University, Tehran, Iran.
5 - Water Engineering Department, University of Zabol, Zabol, Iran.
6 - Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
7 - Department of Social Sciences, University of Mazandaran, Babolsar, Iran.
8 - Department of Agricultural Economics, Sari Agricultural Sciences and Natural Resources University
9 - Department of Agronomy, Sari Agricultural Sciences and Natural Resources University
Received: 2021-08-03
Accepted : 2023-02-27
Published : 2023-04-21
Keywords:
Sustainability,
Life Cycle Assessment,
Cultivation Pattern,
Multi-Objective Planning,
Abstract :
Introduction: Due to the negative effects of agricultural production activities on the environment, especially water and soil pollution, one of the most important decisions in the agricultural sector is the optimal allocation of resources. This decision should be in such a way that while maximizing the profit of farmers, it will result in less environmental effects. This action is often done by determining the optimal cropping pattern (CP). In this research, by quantifying the economic, social and environmental effects, a compatible CP with agricultural resources was presented by using a multi-objective planning model.
Materials and Methods: The social effects of different agricultural crops were calculated using various indicators such as social solidarity, social security, participation and quality of life through interviews with farmers. The environmental effects and economic efficiency of the CP were also considered through the concept of life cycle assessment (LCA) and gross margin per ha, respectively. Further, by calculating socio-economic and environmental indicators, the optimal CP was formulated by developing a multi-objective function based on maximizing profit, reducing water and fertilizer consumption, reducing negative environmental effects of production and improving social indicators. In order to solve the multiple programming model, the method of weighted LP-metric model was used. The information required in this study included information on the production pattern, consumption of inputs, price and yeild of major agricultural crops of Sari County.
Findings: The results showed that considering the social indicators, the least attention of the farmers was related to corn and onion, and the five priority crops were identified as wheat, cotton, lentils, rice and canola, respectively. The results of LCA showed that the cultivation of tobacco, canola and corn in this city have the most negative environmental effects. In the optimal CP by combining economic, social and environmental goals, alfalfa, cotton and corn were removed from the stydy area, and the cultivated area of cucumber and clover showed positive changes compared to the current pattern. Also, the cultivated area of the cereal decreaseed in the areaChanges in the cultivated area of barley were predicted more than wheat and rice. The total cultivated area reduced by 15%, resulting in 12.91% and 14.46% reduction in water and fertilizer consumption, respectively. In addition, the efficiency of the program in the studied area decreased by 12.97%.
Conclusion: The development of environmental goals in the implementation of CP programs requires that policymakers consider appropriate economic incentives for farmers. Therefore, policy makers should find suitable solutions to make the farmers to follow the proposed CP.
References:
Acosta-Alba, I., Chia, E., & Andrieu, N. (2019). The LCA4CSA framework: Using life cycle assessment to strengthen environmental sustainability analysis of climate smart agriculture options at farm and crop levels. Agricultural Systems, 171, 155-170.
https://www.sciencedirect.com/science/article/pii/S0308521X1830564X
Bailey, A. P., Rehman, T., Park, J., Keatinge, J. D. H., & Tranter, R. B. (1999). Towards a method for the economic evaluation of environmental indicators for UK integrated arable farming systems. Agriculture, ecosystems & environment, 72(2), 145-158.
https://www.sciencedirect.com/science/article/abs/pii/S0167880998001716
Bylin, C., Misra, R., Murch, M., & Rigterink, W. (2004). Sustainable Agriculture: Development of an On-farm Assessment Tool: a Project Submitted in Partial Fulfillment... for the Degree of Master of Science/Master of Forestry/Master of Landscape Architecture... University of Michigan.
https://onlinelibrary.wiley.com/doi/abs/10.1111/jiec.12077
Chen, , Zhou, Y., Fang, S., Li, M., Wang, Y., & Cao, K. (2022). Crop pattern optimization for the coordination between economy and environment considering hydrological uncertainty. Science of the Total Environment, 809, 151152.
https://www.sciencedirect.com/science/article/abs/pii/S0048969721062306
San Cristóbal, J. R. (2012). A goal programming model for environmental policy analysis: Application to Spain. Energy Policy, 43, 303-307.
https://www.sciencedirect.com/science/article/abs/pii/S0301421512000109
Duckstein, L. (1981). Multiobjective optimization in structural design: The model choice problem. Arizona Univ Tucson Dept of Systems and Industrial Engineering.
https://apps.dtic.mil/sti/citations/ADP000073
Emamzadeh, S. M., Forghani, M. A., Karnema, A., & Darbandi, S. (2016). Determining an optimum pattern of mixed planting from organic and non-organic crops with regard to economic and environmental indicators: A case study of cucumber in Kerman, Iran. Information processing in agriculture, 3(4), 207-214.
https://www.sciencedirect.com/science/article/pii/S2214317315300366
Fantin, V., Righi, S., Rondini, I., & Masoni, P. (2017). Environmental assessment of wheat and maize production in an Italian farmers' cooperative. Journal of cleaner production, 140, 631-643.
https://www.sciencedirect.com/science/article/abs/pii/S095965261630823X
Fathi, F., & Zibaei, M. (2012). Water resources sustainability using goal programming approach in optimizing crop pattern, strategy and irrigation method. Iran-Water Resources Research, 8(1), 10-19.
http://www.iwrr.ir/article_17413.html?lang=en
Galán-Martín, Á, Pozo, C., Guillén-Gosálbez, G., Vallejo, A. A., & Esteller, L. J. (2015). Multi-stage linear programming model for optimizing cropping plan decisions under the new Common Agricultural Policy. Land use policy, 48, 515-524.
https://www.sciencedirect.com/science/article/abs/pii/S0264837715002008
Halkidis, I., & Papadimos, D. (2007). Technical report of LIFE Environment project: Ecosystem based water resources management to minimise environmental impacts from agriculture using state-of-the-art modeling tools in Strymonas basin. Greek Biotope/Wetland Center (EKBY).
https://www.mdpi.com/2073-4433/11/7/677
Hwang, C. L., & Masud, A. S. M. (2012). Multiple objective decision making—methods and applications: a state-of-the-art survey(Vol. 164). Springer Science & Business Media.
https://books.google.com/books?hl=en&lr=&id=M0noCAAAQBAJ&oi
Jain, S., Ramesh, D., & Bhattacharya, D. (2021). A multi-objective algorithm for crop pattern optimization in agriculture. Applied Soft Computing, 112, 107772.
https://www.sciencedirect.com/science/article/abs/pii/S1568494621006931
Khodarezaie, E., Veisi, H., Noori, O., Taheri, M., & Khoshbakht, K. (2017). Environmental impact assessment of olive production using Life Cycle Assessment: A case study, Tarom County, Zanjan province. Journal of Agroecology, 9(2), 458-474. doi: 10.22067/jag.v9i2.46350
https://agry.um.ac.ir/article_35864.html?lang=en
Li, R., Lv, F., Yang, L., Liu, F., Liu, R., & Dong, G. (2020). Spatial–temporal variation of cropping patterns in relation to climate change in Neolithic China. Atmosphere, 11(7), 677.
https://www.mdpi.com/2073-4433/11/7/677
Lundberg, L., Jonson, E., Lindgren, K., Bryngelsson, D., & Verendel, V. (2015). A cobweb model of land-use competition between food and bioenergy crops. Journal of Economic Dynamics and Control, 53, 1-14.
https://www.sciencedirect.com/science/article/abs/pii/S0165188915000044
Manos, B., Papathanasiou, J., Bournaris, T., & Voudouris, K. (2010). A multicriteria model for planning agricultural regions within a context of groundwater rational management. Journal of environmental management, 91(7), 1593-1600.
https://www.sciencedirect.com/science/article/pii/S030147971000068X
Mansuri, H. and Kohansal, M.R. (2007). Determine the optimum cropping pattern based on economic and environmental approach, the Sixth Conference of Agricultural Economics, Ferdowsi University of Mashhad. (In Persian)
https://gdij.usb.ac.ir/article_5061_a5b8b8674ad93aa39ad804ac70047122.pdf
Najafabadi, M. M., Ziaee, S., Nikouei, A., & Borazjani, M. A. (2019). Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study. Agricultural Systems, 173, 218-232.
https://www.sciencedirect.com/science/article/abs/pii/S0308521X18306644
Marzban, Z., Asgharipour, M., Ganbari, A., Nikouei, A., Ramroudi, M., Seyedabadi, E. (2020). Reducing Environmental Impacts through Redesigning Cropping Pattern Using LCA and MOP (Case study: East Lorestan Province). Journal of Agricultural Science and Sustainable Production, 30(3), 311-330.
https://agris.fao.org/agris-search/search.do?recordID=DJ20210229021
Miettinen, K. (2001, July). Some methods for nonlinear multi-objective optimization. In Evolutionary Multi-Criterion Optimization: First International Conference, EMO 2001 Zurich, Switzerland, March 7–9, 2001 Proceedings(pp. 1-20). Berlin, Heidelberg: Springer Berlin Heidelberg.
https://link.springer.com/chapter/10.1007/3-540-44719-9_1
Mirzaei, A., Layani, G., Azarm, H., Jamshidi, S. (2019). Determination Optimal Crop Pattern of Sirjan County Central Part Based on Stability of Water Resources and Environmental. Agricultural Economics Research, 9(36), 283-304.
https://www.cabdirect.org/cabdirect/abstract/20183102413
Mosleh, Z., Salehi, M. H., Fasakhodi, A. A., Jafari, A., Mehnatkesh, A., & Borujeni, I. E. (2017). Sustainable allocation of agricultural lands and water resources using suitability analysis and mathematical multi-objective programming. Geoderma, 303, 52-59.
https://www.sciencedirect.com/science/article/abs/pii/S0016706117300174
Mousavi, S. N., Saleh, I., and Akbari, S. M. (2015). The Optimal cropping pattern and its impact on water resources management (Case study: Mrvdsht- Karbala region). Water Engineering, 7: pp. 101-110.
https://www.sciencedirect.com/science/article/abs/pii/S0016706117300174
Pedro-Monzonís, M., Jiménez-Fernández, P., Solera, A., & Jiménez-Gavilán, P. (2016). The use of AQUATOOL DSS applied to the of Environmental-Economic Accounting for Water (SEEAW). Journal of hydrology, 533, 1-14.
https://www.sciencedirect.com/science/article/abs/pii/S002216941500921X
Rao, AR, Scanlan JP & Keane AJ. (2007). Applying Multiobjective Cost andWeight Optimization to the Initial Design of Turbine Disks. J. Mech. Des., 129: 1303.
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/129/12/1303/461929/Applying-Multiobjective-Cost-and-Weight
Tovar-Facio, J., Guerras, L. S., Ponce-Ortega, J. M., & Martin, M. (2021). Sustainable Energy Transition Considering the Water–Energy Nexus: A Multiobjective Optimization Framework. ACS Sustainable Chemistry & Engineering, 9(10), 3768-3780.
https://pubs.acs.org/doi/full/10.1021/acssuschemeng.0c08694
Xu, Z. (2000). On consistency of the weighted geometric mean complex judgement matrix in AHP. European journal of operational research, 126(3), 683-687.
https://www.sciencedirect.com/science/article/abs/pii/S037722179900082X
Zeleny, M. (1973). Compromise programming. In Cochrane, J.; Zeleny, M., eds., Multiple Criteria Decision Making, 262–301. University of South Carolina Press, Columbia, 1973.
https://cir.nii.ac.jp/crid/1573387450346632704
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