Optimization of Energy Consumption and Greenhouse Gas Emissions from Orange Production Using Data Envelopment Analysis and Genetic Algorithms (Case Study: Dezful Province)

Subject Areas : Agriculture and Environment

fatemeh sabzalipour ¹ , hossein bagherpour ^{2 *}

1 - M.Sc. Student, Department of Biosystems Engineering, Bu-Ali Sina University, Hamedan, Iran.
2 - Assistant professor, Department of Biosystems Engineering, Bu-Ali Sina University, Hamedan, Iran. *(Corresponding Author)

Received: 2018-02-07 Accepted : 2019-06-03 Published : 2021-10-23

Keywords: Genetic algorithm, Data Envelopment Analysis, Orange, Optimization,

Abstract :

Background and Objective: Saving on inputs, preservation of fossil fuels and decreasing air pollution are the advantages to using energy efficiently.  The purpose of this study was to optimize energy inputs and greenhouse gas emissions of orange product in Dezful County, with two methods of data envelopment analysis and multi-objective genetic algorithm optimization techniques.Material and Methodology:  Data from 60 farmers were randomly collected through face-to-face interviews and a questionnaire during the year 2016 and using two methods of data envelopment analysis and multi-objective genetic algorithm were analyzed.Findings: Regarding the results of data envelopment analysis technique based on fixed and variable return scale models and input-axis measurement, technical efficiency, net technical efficiency and scale efficiency were calculated to be 0.95, 0.98 and 97%. The results of optimization of energy consumption and greenhouse gas emissions by using data envelopment analysis showed that about 4.36% of orange energy has storage potential, that chemical fertilizers and diesel fuel have the highest amount of stored energy of all stored energy. Data envelopment analysis can reduce 34.38 kg of carbon dioxide per hectare from greenhouse gas emissions in orange crops. The results of the genetic algorithm showed that if all inputs were completely optimized, it could reduce the energy consumption of orange production in the study area by 26.1%. Also, the energy input for ideal orange production system could be 32810.6 MJ per ha.Discussion and Conclusion: According to the results of this study, it is recommended to use of new machines and encourage farmers to conduct soil tests before using of fertilizer.

References:

1. FAO, 2016. Food and Agriculture Organization. FAO.org


2. 1394. Agricultural Statistics, Volume 3, Horticultural Products, Crop Year 1394. Ministry of Agricultural Jihad, Deputy Director of Planning and Economics, Office of Statistics and Information Technology.


3. Uhlin, H. 1998. Why energy productivity is increasing: an I–O analysis of Swedish Agri. Sys. 56: 443-465.


4. Nemecek, T., Huguenin-Elie, O., Dubois, D., Gaillard, G., Schaller, B., and Chervet, A. 2011. Life cycle assessment of Swiss farming systems: II. Extensive and intensive production. Agri. Sys. 104: 233-245.


5. Khoshnevisan, B., Rafiee, S., Omid, M., Yousefi, M., and Movahedi, M. 2013a. Modeling of energy consumption and GHG (greenhouse gas) emissions in wheat production in Esfahan province of Iran using artificial neural networks. Energy 52: 333-338.


6. Nabavi-Pelesaraee. A.1393. Modeling and Optimization of Energy Consumption and Pollution Emissions Using Expert Systems in Dominant Cultures in Astaneh Ashrafieh and Langrood, Guilan Province. Master's thesis. Tabriz University. (Pearsian)


7. Mirshekari, F. 1390. Introducing Genetic Algorithms with Multi-Objective Optimization Approach. Master's Seminar, Agricultural Mechanization Engineering, Faculty of Engineering and Technology of Agriculture, University of Tehran. (In Pearsian)


8. Charnes, A., Cooper, W.W., Rhodes, E. 1978. Measuring the efficiency of decision-making units. European Journal of Operational Research, 2: 429-44.


9. Jacobs, R. 2006. An introduction to measuring efficiency in public sector organization.


10. Sattari-Yuzbashkandi, S., Khalilian, S., Mortazavi, S.A. 2014. Energy efficiency for open-field grape production in Iran using Data Envelopment Analysis (DEA) approach. International Journal of Farming and Allied Sciences. 3(6): 637-646.


11. Elhami, B. Akram, A. Khanali, M. 1395. Optimization of Energy Consumption and Reduction of Greenhouse Gas Emissions in Lentil Production Using Data Envelopment Analysis. Engineering Biotechnology in Iran. 47 (4): 701-710. (In Pearsian)


12. Akram, A. Khanali, M. Golchin-Kamakoli, S. Hossein Zadeh Bandbafha, H. 1395. Optimization of energy consumption in the production of warm water using the method of data envelopment analysis and genetic algorithm. Iranian Natural Resources Journal. 69 (4): 431-442 (In Pearsian)


13. Kitani, O. 1999. Energy and Biomass Engineering. CIGR Handbook of Agricultural Engineering. Vol. (5) ASAE.


14. Pishgar-Komleh, S.H., Ghahderijani, M., Sefeedpari. P. 2012. Energy consumption and CO2 emissions analysis of potato production based on different farm size levels in Iran. Journal of Cleaner Production 33: 183-191.


15. Banaeian, N., Zangeneh, M., Omid, M. 2010. Energy use efficiency for walnut producers using data envelopment analysis (DEA). Australian Journal of Crop Science, 4(5):359-362.


16. Mousavi-Aval, S.H. 1390. Comparison of Energy Consumption Patterns and Analysis of Mechanization Indicators in Soybean, Rapeseed and Sunflower Production in Gorgan, Ali Abad and Kaleh County in Golestan Province. Master's thesis. University of Tehran. (In Pearsian)


17. Omid, M., Ghojabeige, F., Delshad, M. and Ahmadi, H. 2011. Energy use pattern and benchmarking of selected greenhouses in Iran using data envelopment analysis. Energy Conversion and Management, 52: 153-162.


18. Ozkan, B., Kurklu, A., Akcaoz, H. 2004. An input–output energy analysis in greenhouse vegetable production: a case study for Antalya region of Turkey. Biomass & Bioenergy, 26:189–95.


19. Lal, R. 2004. Carbon emission from and farm operations, Environ. Int., 30: 981- 990.


20. Dyer, J.A., and Desjardins, R.L. 2006. Simulated farm fieldwork, energy consumption and related greenhouse gas emissions in Canada. Biosys. Eng. 85 (4): 503-513.


21. Nassiri, S.M., and Singh, S. 2009. Study on energy use efficiency for paddy crop using data envelopment analysis (DEA) technique. Appl. Energy 86: 1320-1325.


22. Hu, J.L. and Kao, C.H. 2007. Efficient energy-saving targets for APEC economies. Energy Policy, 35: 373–82.


23. Alireza, M. 1385. Introduction to Genetic Algorithm and its Applications. Naghus Andisheh Publications. (In Pearsian)


24. Chauhan, N.S., Mohapatra, P.K.J., Pandey, K.P. 2006. Improving energy productivity in paddy production through benchmarking-An application of data envelopment analysis. Energy Conversion and Management 47, 1063-1085.