تعیین الگوی بهینه همسو با تولید پایدار ارقام برنج در منطقه گهرباران ساری: کاربرد مدل الگوریتم ژنتیک

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار گروه اقتصاد کشاورزی، دانشگاه علوم کشاورزی و منابع طبیعی ساری. ایران

2 دانشجوی دکتری اقتصاد کشاورزی، دانشگاه علوم کشاورزی و منابع طبیعی ساری

چکیده

هدف مطالعه حاضر، بهینه‌یابی الگوی کشت در قالب مدل چندهدفه در شرایط آب وهوایی نرمال و خشک، در منطقه گهرباران شهرستان ساری با استفاده از مدل الگوریتم ژنتیک می‌باشد. در این راستا، ترکیب بهینه محصولات، حداکثر بهره‌وری اقتصادی آب، حداقل مصرف آب، حداقل آلایندگی ناشی از مصرف کودهای شیمیایی حاصل از کشت ارقام مختلف برنج تعیین و با شرایط فعلی منطقه مقایسه شده است.
در این مطالعه از روش الگوریتم ژنتیک با لحاظ شرایط، سه سال‌‌ آبی مختلف برای دستیابی به هدف مذکور استفاده شده است. جهت دستیابی به مدیریت توام اقتصادی و زیست‌محیطی از الگوی برنامه‌ریزی چندهدفه استفاده می‌شود. داده‌های مطالعه از سازمان جهاد کشاورزی و شرکت آب منطقه‌ای مازندران در سال زراعی 1399-1398 جمع‌آوری شد. همچنین جهت بهینه‌سازی از نرم‌افزار matlab استفاده شده است.
نتایج نشان می‌دهد الگوی پیشنهادی الگوریتم ژنتیک در هر دو حالت آب و هوایی نسبت به الگوی فعلی منطقه دارای برتری است و دستیابی مناسب‌تر اهداف مطالعه را نشان می‌دهد. طبق الگوی بهینه در وضعیت نرمال آب و هوایی، هدف اقتصادی 16 درصد، هدف اکولوژیکی 5/3 درصد و هدف زیست‌محیطی 5/17 درصد بهبود خواهد یافت. همچنین در وضعیت آب وهوایی خشک هدف اقتصادی 17 درصد افزایش، هدف اکولوژیکی 22 درصد کاهش و هدف زیست‌محیطی 20 درصد کاهش را نسبت به الگوی کشت فعلی منطقه نشان می‌دهد. در هر دو حالت آب و هوایی پیشنهاد می‌شود رقم طارم هاشمی بیشترین میزان سطح زیرکشت را به خود اختصاص دهد. نتیجه مذکور با توجه به میزان کم مصرف آب و کود شیمیایی این رقم، منطقی به‌نظر می‌رسد.

کلیدواژه‌ها


عنوان مقاله [English]

Determining aligned optimal pattern with sustainable production of rice cultivars in Gaharbaran region of Sari: Application of Genetic Algorithm Model

نویسندگان [English]

  • somayeh shirzadi laskookalayeh 1
  • Khadijeh Abdi Rokni 2
1 Asistant Prof, Faculty of Agricultural Engineering, Agricultural Sciences and Natural Resources University Sari. Iran
2 PhD Student of Agricultural Economics, Agricultural Sciences and Natural Resources University Sari
چکیده [English]

The aim of the present study is the application of the genetic algorithm model for optimizing the cropping pattern in form of a multi-objective model in the normal and dry climates of Goharbaran area in Sari. In this regard, at first, the optimal products composition, maximum economic water productivity, minimum water consumption, minimum consumption of chemical fertilizers from different rice cultivars have been determined. At second, results were compared with the current conditions in the region.
In this study, the method of genetic algorithm with respect to the conditions of different aquatic years has been used to achieve this goal. A multi-objective planning model has been used to achieve integrated economic and environmental management. The data of the present study were collected through the Jihad Agricultural Organization and Mazandaran Regional Water Company in the 2019-2020 crop year. Matlab software has also been used to estimate the results
The results show that the suggested pattern of the genetic algorithm in these climate conditions superior to the current model of the region and shows more appropriate achievement of study objectives. The optimal pattern in normal climate conditions will be improved in economic goal, ecological goal, and environmental goal by 16%, 3.5%, and17.5%, respectively. Also, in dry climate, the economic goal increases by 17%, the ecological goal decreases by 22% and the environmental goal decreases by 20% compared with the current cultivation pattern of the region.

کلیدواژه‌ها [English]

  • Genetic Algorithm
  • Rice
  • Sustainable Agriculture
  • Water Management
  • . Goharbaran
Abbasi A and Ghadami M, 2006. The effect of optimizing the cultivation pattern in reducing water consumption and increasing income. 7 Biennial Conference of Agricultural Economics. (In Persian).
Adib A and Gorgizadeh A, 2016. Evaluation and Monitoring of drought using of drought Indexes: Case study the Dez watershed. Irrigation and water engineering, 26: 173-185. (In Persian).  
Asadi H, Latifi V and Ebrahimi E, 2018. Study of the Phosphorus Losses from Different Watersheds in Guilan province. Amirkabir Journal of Civil Engineering, 50(4): 641-654. (In Persian).
Baghrian A, Saleh A and Peykani Gh, 2007. Optimization of cropping pattern in Kazeroon region using linear programming method. Sixth Biennial Conference of Iranian Agricultural Economics Association, Mashhad. 8 and 9 November. (In Persian).
Barzegari M and Ghazal soflo A, 2015. Optimization of Urban Water Distribution Network Using Genetic Algorithm (Case Study: Salami City). National Conference on Civil Engineering and Needs Research.1-11. (In Persian).
Chizari A and Ghasemi A, 1999. Application of mathematical planning in determining the optimal cultivation pattern of crops. Journal of Agricultural Economics and Development, 28(7): 61-76. (In Persian).
Ganji N, Abdos M and Moghari M, 2018. Using of Metaheuristic Water Cycle Algorithm in order to Determine Optimal Crop Cultivation across of Genetic Algorithm and linear programming (Case Study: Varamin Irrigation Network). Journal of Water and Soil Science (Science and Technology of Agriculture and Natural Resources), 23(3): 211-222. (In Persian).
Geng Nb, Zhengb Y, Hanb F and Huapeng Q, 2019. The nexus of water, ecosystems and agriculture in arid areas: A multiobjective optimization study on system efficiencies. Agricultural Water Management, 223(2): pp 105697, ref 64.
 Ghasemi M, Karamouz M, and  Shui L, 2016. Farm-based cropping pattern optimization and conjunctive use planning using piece-wise genetic algorithm (PWGA): a case study. Modeling Earth Systems and Environment, 2(25): 2-12. (In Persian).
Falsoliman M and Chakoshi B, 2011. The role of optimal management of agricultural water consumption to increase productivity and sustainability of water resources in critical plains in arid and low water areas of the country (Case study: West of Birjand plain). Journal of Geography and Regional Developmenm, 16: 200-218. (In Persian).
Hashmi M, Mazandarani Zade H, Daneshkare Arasteh P and Zarghami M, 2019. Economic and environmental impacts of cropping pattern elements using systems dynamics. Civil Engineering Journal, 5(5): 1020-1032. (In Persian).
Hosseinzad J, Namvar A, Hayati B and Pishbahar E, 2014. Determination of crop pattern with emphasis on sustainable agriculture in the lands below the alavian dam and its network. Agriculture Science and Sustainable production, 24(2): 41-54. (In Persian).
Ikudayisi A, Adeyemo J, Odiyo J and Enitan A, 2018. Optimum irrigation water allocation and crop distribution using combined Pareto multiobjective differential evolution. Cogent Engineering, 2331-1916.
Kashiri Kolaei F, Hosseini-Yekani A and Mojaverian M, 2020. Optimization of virtual water consumption with emphasis on uncertainty of rainfall and crop price (A case Study: Sari Gherbaran. Agriculture Science and Sustainable Production, 30(3):267-293. (In Persian).
Khoshnavaz s, 2020. Uncertainty analysis of water distribution planning in mian-ab irrigation network in shooshtar plain: application of genetic algorithm and simulated annealing. Iranian Journal of Soil and Water Research, 52(1): 152-163. (In Persian).
Lopez e, Orengo J, Tarjuelo J and Martínez A, 2017. Development of a direct-solution algorithm for determining the optimal crop planning of farms using deficit irrigation. Agricultural Water Management 171. 173-187.
Nouiri I, 2014. Multi-objective tool to optimize the Water resources management using genetic algorithm and the pareto optimality concept. Water Resources Management, 28: 2885–2901.
Mirzaie Sh, Zakerinia M, Shahabifar M and Sharifan H, 2017. Determining optimum cropping pattern using genetic algorithm (case study: Golestan dam irrigation and drainage network. Irrigation Sciences and Engineering, 40(3):181-190.
Ochieng J, Kirimi L and athenge M, 2016. Effects of climate variability and change on agricultural production: The case of small scale farmers in Kenya. 77: 71-78.
Raju K and Kumar D, 2004. Irrigation planing using genetic algorithms. Water Resour Management, 18(2): 163-176.
Rezaee Z, Dourandish A and Nobahar A, 2012. Determination of cultivation pattern under three strategies of economic, social, environmental with application of genetic algorithms: (Case study of Mashhad). Biennial Conference of Agricultural Economics, 1607- 1615. (In Persian).
Saeidian B, Saadi Mesgari M and Ghodousi M, 2015. Optimum allocation of water to the cultivation farms using Genetic Algorithm. International Conference on Sensors & Models in Remote Sensing & Photogrammetry, XL-1/W5. 631-638.
Shabani M and Honar T, (2008). Determining the optimal cultivation pattern in irrigation canals using IPM model.  Journal of Water and Soil (Agricultural Science and Technology), 2(22): 95-106.
Shirshahi F, Babazadeh H, Ebrahimipak N and Khaledian K, (2020). Determining Optimum major Crops Cultivation Areas in Different Levels of deficit Irrigation in Qazvin Irrigation and drainage district. Journal of Soil and Water Science, 30(1): 69-81. (In Persian).
Singh A and Panda S.N, 2012. Development and application of an optimization model for the maximization of net agricultural return. Agricultural Water Management, 115: 267-275. (In Persian).
Yosefdost A, Mohamadrezapur A and Ebrahimi M, 2016. Applying Genetic algorithms in determining optimal cropping pattern in different weather conditions in Qazvin plain.  Journal "Water Research in Agriculture, 3(3):317-331. (In Persian).