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Developing a fuzzy clustering model for better energy use in farm management systems

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  • Khoshnevisan, Benyamin
  • Rafiee, Shahin
  • Omid, Mahmoud
  • Mousazadeh, Hossein
  • Shamshirband, Shahaboddin
  • Hamid, Siti Hafizah Ab

Abstract

Wheat is considered as one of the most important strategic crops in Iran, and Iran agricultural ministry has some special plans to encourage farmers to cultivate this crop, so that farmers are willing to cultivate this crop through the country. The previous studies carried out by researchers in Iran showed that the energy consumption in cultivation of this crop is not efficient and there is a high degree of inefficiency in wheat cultivation in Iran. Also, wheat cultivation in Iran is responsible for a high amount of greenhouse gas (GHG) emissions. In order to differentiate between efficient and inefficient farms, a c-means fuzzy clustering model has been developed and the surveyed wheat farms have been clustered based on three features, i.e. GHG emission, energy ratio and benefit cost ratio. The results showed that the farms which were selected as cluster 2 had the best performance where the total input energy and total GHG were calculated as 38,826.9MJ per ha and 3185kgCO2,eq per tonne of crop. In other words, the farms in cluster 2 outperformed cluster 1 and 3 where they performed 34 and 19% better than the two other clusters in terms of energy input and 9 and 27% in CO2 emission per tonne of produced crop. The higher output energy and lower input energy in farms of cluster 2 have caused a better economic performance where the benefit cost ratio was calculated as 1.9. The results of this study demonstrate the successful application of fuzzy clustering approach for better use of energy in cropping systems which can lead to a better environmental and economic performance.

Suggested Citation

  • Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Mousazadeh, Hossein & Shamshirband, Shahaboddin & Hamid, Siti Hafizah Ab, 2015. "Developing a fuzzy clustering model for better energy use in farm management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 27-34.
  • Handle: RePEc:eee:rensus:v:48:y:2015:i:c:p:27-34
    DOI: 10.1016/j.rser.2015.03.029
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    1. 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.
    2. 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.
    3. 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.
    4. Blancard, Stéphane & Martin, Elsa, 2014. "Energy efficiency measurement in agriculture with imprecise energy content information," Energy Policy, Elsevier, vol. 66(C), pages 198-208.
    5. 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.
    6. Rahman, Sanzidur & Hasan, M. Kamrul, 2014. "Energy productivity and efficiency of wheat farming in Bangladesh," Energy, Elsevier, vol. 66(C), pages 107-114.
    7. Tabatabaie, Seyed Mohammad Hossein & Rafiee, Shahin & Keyhani, Alireza & Heidari, Mohammad Davoud, 2013. "Energy use pattern and sensitivity analysis of energy inputs and input costs for pear production in Iran," Renewable Energy, Elsevier, vol. 51(C), pages 7-12.
    8. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Mousazadeh, Hossein, 2013. "Reduction of CO2 emission by improving energy use efficiency of greenhouse cucumber production using DEA approach," Energy, Elsevier, vol. 55(C), pages 676-682.
    9. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Mohammadi, Ali, 2011. "Optimization of energy consumption and input costs for apple production in Iran using data envelopment analysis," Energy, Elsevier, vol. 36(2), pages 909-916.
    10. 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.
    11. Mohammadi, Ali & Rafiee, Shahin & Jafari, Ali & Keyhani, Alireza & Mousavi-Avval, Seyed Hashem & Nonhebel, Sanderine, 2014. "Energy use efficiency and greenhouse gas emissions of farming systems in north Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 724-733.
    12. Taghavifar, Hamid & Mardani, Aref, 2015. "Energy consumption analysis of wheat production in West Azarbayjan utilizing life cycle assessment (LCA)," Renewable Energy, Elsevier, vol. 74(C), pages 208-213.
    13. 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.
    14. 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.
    15. Shamshirband, Shahaboddin & Khoshnevisan, Benyamin & Yousefi, Marziye & Bolandnazar, Elham & Anuar, Nor Badrul & Abdul Wahab, Ainuddin Wahid & Khan, Saif Ur Rehman, 2015. "A multi-objective evolutionary algorithm for energy management of agricultural systems—A case study in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 457-465.
    16. 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.
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    3. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Sharifi, Mohammad & Hosseinpour, Soleiman & Shah, Ajay, 2017. "Combined application of Life Cycle Assessment and Adaptive Neuro-Fuzzy Inference System for modeling energy and environmental emissions of oilseed production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 807-820.

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