IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v48y2015icp27-34.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032115001823
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2015.03.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    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. Blancard, Stéphane & Martin, Elsa, 2014. "Energy efficiency measurement in agriculture with imprecise energy content information," Energy Policy, Elsevier, vol. 66(C), pages 198-208.
    6. 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.
    7. 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.
    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. 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.
    11. 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.
    12. 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.
    13. Rahman, Sanzidur & Hasan, M. Kamrul, 2014. "Energy productivity and efficiency of wheat farming in Bangladesh," Energy, Elsevier, vol. 66(C), pages 107-114.
    14. 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.
    15. 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.
    16. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
    2. 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.
    3. Ruiz de la Hermosa González-Carrato, Raúl, 2018. "Wind farm monitoring using Mahalanobis distance and fuzzy clustering," Renewable Energy, Elsevier, vol. 123(C), pages 526-540.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sara Ilahi & Yongchang Wu & Muhammad Ahsan Ali Raza & Wenshan Wei & Muhammad Imran & Lyankhua Bayasgalankhuu, 2019. "Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis," Sustainability, MDPI, vol. 11(12), pages 1-16, June.
    2. Elsoragaby, Suha & Yahya, Azmi & Mahadi, Muhammad Razif & Nawi, Nazmi Mat & Mairghany, Modather, 2019. "Energy utilization in major crop cultivation," Energy, Elsevier, vol. 173(C), pages 1285-1303.
    3. 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.
    4. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Mousazadeh, Hossein & Rajaeifar, Mohammad Ali, 2014. "Application of artificial neural networks for prediction of output energy and GHG emissions in potato production in Iran," Agricultural Systems, Elsevier, vol. 123(C), pages 120-127.
    5. Taheri-Rad, Alireza & Khojastehpour, Mehdi & Rohani, Abbas & Khoramdel, Surur & Nikkhah, Amin, 2017. "Energy flow modeling and predicting the yield of Iranian paddy cultivars using artificial neural networks," Energy, Elsevier, vol. 135(C), pages 405-412.
    6. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Mousazadeh, Hossein, 2013. "Applying data envelopment analysis approach to improve energy efficiency and reduce GHG (greenhouse gas) emission of wheat production," Energy, Elsevier, vol. 58(C), pages 588-593.
    7. Morteza Zangeneh & Narges Banaeian & Sean Clark, 2021. "Meta-Analysis on Energy-Use Patterns of Cropping Systems in Iran," Sustainability, MDPI, vol. 13(7), pages 1-28, March.
    8. Kazemi, Hossein & Bourkheili, Saeid Hassanpour & Kamkar, Behnam & Soltani, Afshin & Gharanjic, Kambiz & Nazari, Noor Mohammad, 2016. "Estimation of greenhouse gas (GHG) emission and energy use efficiency (EUE) analysis in rainfed canola production (case study: Golestan province, Iran)," Energy, Elsevier, vol. 116(P1), pages 694-700.
    9. 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.
    10. Houshyar, Ehsan & Azadi, Hossein & Almassi, Morteza & Sheikh Davoodi, Mohammad Javad & Witlox, Frank, 2012. "Sustainable and efficient energy consumption of corn production in Southwest Iran: Combination of multi-fuzzy and DEA modeling," Energy, Elsevier, vol. 44(1), pages 672-681.
    11. Pritpal Singh & Gurdeep Singh & G. P. S. Sodhi, 2022. "Data envelopment analysis based optimization for improving net ecosystem carbon and energy budget in cotton (Gossypium hirsutum L.) cultivation: methods and a case study of north-western India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2079-2119, February.
    12. Hamed Rafiee & Milad Aminizadeh & Elham Mehrparvar Hosseini & Hanane Aghasafari & Ali Mohammadi, 2022. "A Cluster Analysis on the Energy Use Indicators and Carbon Footprint of Irrigated Wheat Cropping Systems," Sustainability, MDPI, vol. 14(7), pages 1-19, March.
    13. Bhunia, Snehasish & Karmakar, Subrata & Bhattacharjee, Suvendu & Roy, Kingshuk & Kanthal, Sahely & Pramanick, Mahadev & Baishya, Aniket & Mandal, Biswapati, 2021. "Optimization of energy consumption using data envelopment analysis (DEA) in rice-wheat-green gram cropping system under conservation tillage practices," Energy, Elsevier, vol. 236(C).
    14. Elahi, Ehsan & Weijun, Cui & Jha, Sunil Kumar & Zhang, Huiming, 2019. "Estimation of realistic renewable and non-renewable energy use targets for livestock production systems utilising an artificial neural network method: A step towards livestock sustainability," Energy, Elsevier, vol. 183(C), pages 191-204.
    15. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    16. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    17. Vlontzos, G. & Pardalos, P.M., 2017. "Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 155-162.
    18. Barut, Zeliha Bereket & Ertekin, Can & Karaagac, Hasan Ali, 2011. "Tillage effects on energy use for corn silage in Mediterranean Coastal of Turkey," Energy, Elsevier, vol. 36(9), pages 5466-5475.
    19. Naseri, Hakim & Parashkoohi, Mohammad Gholami & Ranjbar, Iraj & Zamani, Davood Mohammad, 2021. "Energy-economic and life cycle assessment of sugarcane production in different tillage systems," Energy, Elsevier, vol. 217(C).
    20. Chang, Ming-Chung, 2016. "Applying the energy productivity index that considers maximized energy reduction on SADC (Southern Africa Development Community) members," Energy, Elsevier, vol. 95(C), pages 313-323.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:48:y:2015:i:c:p:27-34. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.