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Modeling of energy consumption and GHG (greenhouse gas) emissions in wheat production in Esfahan province of Iran using artificial neural networks

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  • Khoshnevisan, Benyamin
  • Rafiee, Shahin
  • Omid, Mahmoud
  • Yousefi, Marziye
  • Movahedi, Mehran

Abstract

This study was carried out in Esfahan province of Iran. Data were collected from 260 farms in Fereydonshahr city with face to face questionnaire method. The objective of this study was to predict wheat production yield and (greenhouse gas) GHG emissions on the basis of energy inputs. Accordingly, several (artificial neural network) ANN models were developed and the prediction accuracy of them was evaluated using the quality parameters. The results illustrated that average total input and output energy of wheat production were 80.1 and 38 GJ ha−1, respectively. Electricity, chemical fertilizers and water for irrigation were the most influential factors in energy consumption with amount of 39.5, 23.3 and 6.17 GJ ha−1, respectively. Energy use efficiency and energy productivity were 0.032 GJ kg−1 and 34.1 kg GJ−1, respectively. The ANN model with 11-3-2 structure was the best one for predicting the wheat yield and GHG emissions. The coefficients of determination (R2) of the best topology were 0.99 and 0.998 for wheat yield and GHG emissions, respectively.

Suggested Citation

  • Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Yousefi, Marziye & Movahedi, Mehran, 2013. "Modeling of energy consumption and GHG (greenhouse gas) emissions in wheat production in Esfahan province of Iran using artificial neural networks," Energy, Elsevier, vol. 52(C), pages 333-338.
    • Handle: RePEc:eee:energy:v:52:y:2013:i:c:p:333-338
    DOI: 10.1016/j.energy.2013.01.028
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    as
    1. Zangeneh, Morteza & Omid, Mahmoud & Akram, Asadollah, 2010. "A comparative study on energy use and cost analysis of potato production under different farming technologies in Hamadan province of Iran," Energy, Elsevier, vol. 35(7), pages 2927-2933.
    2. Singh, Satwinder & Singh, Surendra & Pannu, C. J. S. & Singh, Jasdev, 1999. "Energy input and yield relations for wheat in different agro-climatic zones of the Punjab," Applied Energy, Elsevier, vol. 63(4), pages 287-298, August.
    3. Tabatabaie, Seyed Mohammad Hossein & Rafiee, Shahin & Keyhani, Alireza, 2012. "Energy consumption flow and econometric models of two plum cultivars productions in Tehran province of Iran," Energy, Elsevier, vol. 44(1), pages 211-216.
    4. Safa, M. & Samarasinghe, S., 2011. "Determination and modelling of energy consumption in wheat production using neural networks: “A case study in Canterbury province, New Zealand”," Energy, Elsevier, vol. 36(8), pages 5140-5147.
    5. Nemecek, Thomas & Huguenin-Elie, Olivier & Dubois, David & Gaillard, Gérard & Schaller, Britta & Chervet, Andreas, 2011. "Life cycle assessment of Swiss farming systems: II. Extensive and intensive production," Agricultural Systems, Elsevier, vol. 104(3), pages 233-245, March.
    6. Deh Kiani, M. Kiani & Ghobadian, B. & Tavakoli, T. & Nikbakht, A.M. & Najafi, G., 2010. "Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol- gasoline blends," Energy, Elsevier, vol. 35(1), pages 65-69.
    7. Al-Ghandoor, A. & Jaber, J.O. & Al-Hinti, I. & Mansour, I.M., 2009. "Residential past and future energy consumption: Potential savings and environmental impact," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1262-1274, August.
    8. Pathak, H. & Wassmann, R., 2007. "Introducing greenhouse gas mitigation as a development objective in rice-based agriculture: I. Generation of technical coefficients," Agricultural Systems, Elsevier, vol. 94(3), pages 807-825, June.
    9. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach," Energy, Elsevier, vol. 36(5), pages 2765-2772.
    10. Nemecek, Thomas & Dubois, David & Huguenin-Elie, Olivier & Gaillard, Gérard, 2011. "Life cycle assessment of Swiss farming systems: I. Integrated and organic farming," Agricultural Systems, Elsevier, vol. 104(3), pages 217-232, March.
    11. Heidari, M.D. & Omid, M., 2011. "Energy use patterns and econometric models of major greenhouse vegetable productions in Iran," Energy, Elsevier, vol. 36(1), pages 220-225.
    12. Mohammadi, Ali & Omid, Mahmoud, 2010. "Economical analysis and relation between energy inputs and yield of greenhouse cucumber production in Iran," Applied Energy, Elsevier, vol. 87(1), pages 191-196, January.
    13. Rafiee, Shahin & Mousavi Avval, Seyed Hashem & Mohammadi, Ali, 2010. "Modeling and sensitivity analysis of energy inputs for apple production in Iran," Energy, Elsevier, vol. 35(8), pages 3301-3306.
    14. Uhlin, Hans-Erik, 1998. "Why energy productivity is increasing: An I-O analysis of Swedish agriculture," Agricultural Systems, Elsevier, vol. 56(4), pages 443-465, April.
    15. Pahlavan, Reza & Omid, Mahmoud & Akram, Asadollah, 2012. "Energy input–output analysis and application of artificial neural networks for predicting greenhouse basil production," Energy, Elsevier, vol. 37(1), pages 171-176.
    16. Esengun, Kemal & Erdal, Gülistan & Gündüz, Orhan & Erdal, Hilmi, 2007. "An economic analysis and energy use in stake-tomato production in Tokat province of Turkey," Renewable Energy, Elsevier, vol. 32(11), pages 1873-1881.
    17. Erdal, Gülistan & Esengün, Kemal & Erdal, Hilmi & Gündüz, Orhan, 2007. "Energy use and economical analysis of sugar beet production in Tokat province of Turkey," Energy, Elsevier, vol. 32(1), pages 35-41.
    18. Kizilaslan, Halil, 2009. "Input-output energy analysis of cherries production in Tokat Province of Turkey," Applied Energy, Elsevier, vol. 86(7-8), pages 1354-1358, July.
    19. Ramedani, Z. & Rafiee, S. & Heidari, M.D., 2011. "An investigation on energy consumption and sensitivity analysis of soybean production farms," Energy, Elsevier, vol. 36(11), pages 6340-6344.
    20. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach," Applied Energy, Elsevier, vol. 88(11), pages 3765-3772.
    21. Hatirli, Selim Adem & Ozkan, Burhan & Fert, Cemal, 2005. "An econometric analysis of energy input-output in Turkish agriculture," Renewable and Sustainable Energy Reviews, Elsevier, vol. 9(6), pages 608-623, December.
    22. Ermis, K. & Midilli, A. & Dincer, I. & Rosen, M.A., 2007. "Artificial neural network analysis of world green energy use," Energy Policy, Elsevier, vol. 35(3), pages 1731-1743, March.
    23. Pishgar-Komleh, Seyyed Hassan & Keyhani, Alireza & Mostofi-Sarkari, Mohammad Reza & Jafari, Ali, 2012. "Energy and economic analysis of different seed corn harvesting systems in Iran," Energy, Elsevier, vol. 43(1), pages 469-476.
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