Determination of Optimal Cropping Pattern Emphasizing Sustainability of Natural Resources and Environment in Orzoyeh District

Document Type : Research Paper

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Abstract

Water, soil, Vegetation and other natural resources, will be sustainable and useable permanently when they use scientifically and consciously. If the resources are used irregularly, this action will cause to stop renewing resources and they will be mortal. In current study, we used fuzzy goal programming for determining of optimal cropping pattern which emphasizes sustainability of natural resources and environment. For this purpose, four fuzzy goals include profit maximization; irrigation water minimization, fertilizers minimization and pesticides minimization were considered in four scenarios. Requirement data were collected by questionnaire and from Kerman province Jihad Keshavarzi documents. Four optimal cropping patterns were represented by considering different weights for goals. Results illustrated in those scenarios that natural resource conservation and production sustainability have priority, the activities that need require less water, fertilizers and pesticides are more into the cropping pattern. On the contrary, in that scenario that profit maximization has the most weight, the cropping pattern limited to watermelon and potato activities. Because have the highest profit in hectare, although use the most water. Therefore, considering natural resources and environmental sustainability approaches are effective on optimal cropping pattern determination.
 

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References

Anonymous, 2013. Agricultural Statistics. Agricultural Jihad Organization of Kerman province (In Persian).
Asadpour H, Khalilian S and Paykani GH, 2005. Theory and application of fuzzy goal linear programming in optimization of cropping pattern. Journal of Agricultural Economics and Development, 13(54): 307-328. (In Persian).
 Askari A, Sabuhi M, Salarpour M and Rekan A. 2012. Determine of optimal cropping pattern with emphasis on limitation of water resources using fuzzy goal programming approaches. 1st National Desert Conference. Thursday, Jun. 17, Tehran, Iran. (In Persian).
Azadegan E, Rastegaripour F and Sabouhi M, 2013. Determination of cropping pattern of Sabzevar county, using fuzzy programming. , Journal of Agricultural Economics and Development, 27(1): 8-15. (In Persian).
Biswas A, Dhamar S and Rao JR, 1978. Fuzzy goal programming, an additive model. Fuzzy Sets and System, 24: 27-34.
Fasakhodi A  and Nouri SH, 2011. Sustainability Assessment and Cropping Pattern Determination in Farming Systems Based on the Optimization of Soil and Water Resources Utilization Using Non-linear Mathematical Programming Models. Journal of Water and Soil Science, 15(55): 99-111. (In Persian).
Kaykha A, Ghafari Moghadam Z and Rafiee S, 2009. Determination of optimal cropping pattern in Sistan district during Drought period (using fuzzy goal programming). 7th Agricultural Economics Conference, Iran, Mashhad. (In Persian).
Kim JS and Whang K, 1998. A tolerance approach to the fuzzy goal programming problems with unbalanced triangular membership function. European Journal of Operational Research, 107(4): 614–624.
Kohansal M and Zaree A, 2008. Determining optimal cultivation model corresponding with sustainable agriculture Application of Multiple-objective Linear Fuzzy Fractional Programming (Case study: North Khorasan Province), 16(62): 1-32.  (In Persian).
Li YP, Huang GH and Zhou HD, 2009.A multistage fuzzy-stochastic programming model for supporting water-resources allocation and management. Environmental Modeling and Software, 24:786-797.
Oliveira C and Carlos HA, 2007. Multiple objective linear programming models with interval coefficients – an illustrated overview. European Journal of Operational Research, 181(3): 1434-1463.
Pal BB and Basu I, 1996. Selection of appropriate priority structure for optimal land allocation in agricultural planning through goal programming, Indian Journal of Agricultural Economics, 51(3):342- 354.
Pal BB, Moitra BN, 2003. Fuzzy goal programming approach to long term and allocation planning problem in agriculture system: Acase study In: Proceeding of fifth International Conference on Advances in Pattern Recognition Allied Publishers. Pvt. Ltd, 441-7.
Pourgholam M, Nemati N and Oveysi M. 2013. Effect of zinc and iron under the influence of drought on prolin, protein and nitrogen leaf of rapeseed (Brassica napus L.). Annals of Biological Research, 4(7): 200-203. (In Persian).
Schweizer LE, Nyquist WE, Santini JB and Kimes TM, 1986. Soybean cultivar mixtures in a narrow-row, noncultivatable production system. Crop Science, 26: 1043-1046.
Zamani O, Sabouhi Saboni M and Nader H, 2010. Determining Cropping Pattern Corresponding Sustainable Agriculture by Using Multi-objective Fuzzy Fractional programming: a Case of Piranshahar City.  Journal of Sustainable Agriculture and Production Science, 20(4): 101-112. (In Persian).
Zimmermann HJ, 1985. Application of fuzzy set theory to mathematical programming. Information Science, 34: 29-58.
JOURNAL OF AGRICULTURAL SCIENCE AND SUSTAINABLE PRODUCTION
Volume 26, Issue 4
January 2017
Pages 185-195

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