IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v37y2012i1p171-176.html
   My bibliography  Save this article

Energy input–output analysis and application of artificial neural networks for predicting greenhouse basil production

Author

Listed:
  • Pahlavan, Reza
  • Omid, Mahmoud
  • Akram, Asadollah

Abstract

In this study, various Artificial Neural Networks (ANNs) were developed to estimate the production yield of greenhouse basil in Iran. For this purpose, the data collected by random method from 26 greenhouses in the region during four periods of plant cultivation in 2009–2010. The total input energy and energy ratio for basil production were 14,308,998 MJ ha−1 and 0.02, respectively. The developed ANN was a multilayer perceptron (MLP) with seven neurons in the input layer, one, two and three hidden layer(s) of various numbers of neurons and one neuron (basil yield) in the output layer. The input energies were human labor, diesel fuel, chemical fertilizers, farm yard manure, chemicals, electricity and transportation. Results showed, the ANN model having 7-20-20-1 topology can predict the yield value with higher accuracy. So, this two hidden layer topology was selected as the best model for estimating basil production of regional greenhouses with similar conditions. For the optimal model, the values of the models outputs correlated well with actual outputs, with coefficient of determination (R2) of 0.976. For this configuration, RMSE and MAE values were 0.046 and 0.035, respectively. Sensitivity analysis revealed that chemical fertilizers are the most significant parameter in the basil production.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:37:y:2012:i:1:p:171-176
    DOI: 10.1016/j.energy.2011.11.055
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544211007869
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2011.11.055?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. Nassiri, Seyed Mehdi & Singh, Surendra, 2009. "Study on energy use efficiency for paddy crop using data envelopment analysis (DEA) technique," Applied Energy, Elsevier, vol. 86(7-8), pages 1320-1325, July.
    2. 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.
    3. Canakci, M. & Akinci, I., 2006. "Energy use pattern analyses of greenhouse vegetable production," Energy, Elsevier, vol. 31(8), pages 1243-1256.
    4. Chaudhary, V.P. & Gangwar, B. & Pandey, D.K. & Gangwar, K.S., 2009. "Energy auditing of diversified rice–wheat cropping systems in Indo-gangetic plains," Energy, Elsevier, vol. 34(9), pages 1091-1096.
    5. Ozkan, Burhan & Fert, Cemal & Karadeniz, C. Feyza, 2007. "Energy and cost analysis for greenhouse and open-field grape production," Energy, Elsevier, vol. 32(8), pages 1500-1504.
    6. 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.
    7. 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.
    8. Kalogirou, Soteris A., 2001. "Artificial neural networks in renewable energy systems applications: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 5(4), pages 373-401, December.
    9. 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.
    10. 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.
    11. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    12. Singh, Surender, 2007. "A Study on Technical Efficiency of Wheat Cultivation in Haryana," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 20(1).
    13. 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.
    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. 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.
    2. 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.
    3. Tao Liang & Weilin Tao & Yan Wang & Na Zhou & Wei Hu & Tao Zhang & Dunxiu Liao & Xinping Chen & Xiaozhong Wang, 2023. "The Extension of Vegetable Production to High Altitudes Increases the Environmental Cost and Decreases Economic Benefits in Subtropical Regions," Land, MDPI, vol. 12(3), pages 1-15, March.
    4. Soltanali, Hamzeh & Nikkhah, Amin & Rohani, Abbas, 2017. "Energy audit of Iranian kiwifruit production using intelligent systems," Energy, Elsevier, vol. 139(C), pages 646-654.
    5. Yongqiang Zhang & Hao Sun & Maosheng Ge & Hang Zhao & Yifan Hu & Changyue Cui & Zhibin Wu, 2023. "Difference in Energy Input and Output in Agricultural Production under Surface Irrigation and Water-Saving Irrigation: A Case Study of Kiwi Fruit in Shaanxi," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    6. Chakrabarty, Sayan & Boksh, F.I.M. Muktadir & Chakraborty, Arpita, 2013. "Economic viability of biogas and green self-employment opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 757-766.
    7. Adewole, Bamiji Z. & Abidakun, Olatunde A. & Asere, Abraham A., 2013. "Artificial neural network prediction of exhaust emissions and flame temperature in LPG (liquefied petroleum gas) fueled low swirl burner," Energy, Elsevier, vol. 61(C), pages 606-611.
    8. Stanisław Bielski & Renata Marks-Bielska & Paweł Wiśniewski, 2022. "Investigation of Energy and Economic Balance and GHG Emissions in the Production of Different Cultivars of Buckwheat ( Fagopyrum esculentum Moench): A Case Study in Northeastern Poland," Energies, MDPI, vol. 16(1), pages 1-24, December.
    9. Wang, Xiaozhong & Liu, Bin & Wu, Gang & Sun, Yixiang & Guo, Xisheng & Jin, Zhenghui & Xu, Weining & Zhao, Yongzhi & Zhang, Fusuo & Zou, Chunqin & Chen, Xinping, 2018. "Environmental costs and mitigation potential in plastic-greenhouse pepper production system in China: A life cycle assessment," Agricultural Systems, Elsevier, vol. 167(C), pages 186-194.
    10. Elsoragaby, Suha & Yahya, Azmi & Mahadi, Muhammad Razif & Nawi, Nazmi Mat & Mairghany, Modather, 2019. "Analysis of energy use and greenhouse gas emissions (GHG) of transplanting and broadcast seeding wetland rice cultivation," Energy, Elsevier, vol. 189(C).
    11. Khamis, Aziah & Shareef, Hussain & Bizkevelci, Erdal & Khatib, Tamer, 2013. "A review of islanding detection techniques for renewable distributed generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 483-493.
    12. Elahi, Ehsan & Zhang, Zhixin & Khalid, Zainab & Xu, Haiyun, 2022. "Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms," Energy, Elsevier, vol. 244(PB).
    13. 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.
    14. 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.
    15. 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.
    16. Khoshnevisan, Benyamin & Shariati, Hanifreza Motamed & Rafiee, Shahin & Mousazadeh, Hossein, 2014. "Comparison of energy consumption and GHG emissions of open field and greenhouse strawberry production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 316-324.
    17. Laila Ouazzani Chahidi & Marco Fossa & Antonella Priarone & Abdellah Mechaqrane, 2021. "Evaluation of Supervised Learning Models in Predicting Greenhouse Energy Demand and Production for Intelligent and Sustainable Operations," Energies, MDPI, vol. 14(19), pages 1-15, October.
    18. Duarte, Rosa & Langarita, Raquel & Sánchez-Chóliz, Julio, 2017. "The electricity industry in Spain: A structural analysis using a disaggregated input-output model," Energy, Elsevier, vol. 141(C), pages 2640-2651.
    19. Xiaobo Xue Romeiko & Zhijian Guo & Yulei Pang & Eun Kyung Lee & Xuesong Zhang, 2020. "Comparing Machine Learning Approaches for Predicting Spatially Explicit Life Cycle Global Warming and Eutrophication Impacts from Corn Production," Sustainability, MDPI, vol. 12(4), pages 1-19, February.

    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. Pishgar Komleh, S.H. & Keyhani, A. & Rafiee, Sh. & Sefeedpary, P., 2011. "Energy use and economic analysis of corn silage production under three cultivated area levels in Tehran province of Iran," Energy, Elsevier, vol. 36(5), pages 3335-3341.
    2. Pahlavan, Reza & Omid, Mahmoud & Akram, Asadollah, 2011. "Energy use efficiency in greenhouse tomato production in Iran," Energy, Elsevier, vol. 36(12), pages 6714-6719.
    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. 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.
    5. Kuswardhani, Nita & Soni, Peeyush & Shivakoti, Ganesh P., 2013. "Comparative energy input–output and financial analyses of greenhouse and open field vegetables production in West Java, Indonesia," Energy, Elsevier, vol. 53(C), pages 83-92.
    6. 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.
    7. Banaeian, Narges & Zangeneh, Morteza, 2011. "Study on energy efficiency in corn production of Iran," Energy, Elsevier, vol. 36(8), pages 5394-5402.
    8. 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.
    9. Pishgar-Komleh, S.H. & Sefeedpari, P. & Rafiee, S., 2011. "Energy and economic analysis of rice production under different farm levels in Guilan province of Iran," Energy, Elsevier, vol. 36(10), pages 5824-5831.
    10. Torki-Harchegani, Mehdi & Ebrahimi, Rahim & Mahmoodi-Eshkaftaki, Mahmood, 2015. "Almond production in Iran: An analysis of energy use efficiency (2008–2011)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 217-224.
    11. Bojacá, Carlos Ricardo & Casilimas, Héctor Albeiro & Gil, Rodrigo & Schrevens, Eddie, 2012. "Extending the input–output energy balance methodology in agriculture through cluster analysis," Energy, Elsevier, vol. 47(1), pages 465-470.
    12. 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.
    13. Elahi, Ehsan & Zhang, Zhixin & Khalid, Zainab & Xu, Haiyun, 2022. "Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms," Energy, Elsevier, vol. 244(PB).
    14. 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.
    15. Özgöz, Engin & Altuntaş, Ebubekir & Asiltürk, Murat, 2017. "Effects of soil tillage on energy use in potato farming in Central Anatolia of Turkey," Energy, Elsevier, vol. 141(C), pages 1517-1523.
    16. Pishgar-Komleh, Seyyed Hassan & Omid, Mahmoud & Heidari, Mohammad Davoud, 2013. "On the study of energy use and GHG (greenhouse gas) emissions in greenhouse cucumber production in Yazd province," Energy, Elsevier, vol. 59(C), pages 63-71.
    17. 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.
    18. Samavatean, Naeimeh & Rafiee, Shahin & Mobli, Hossein & Mohammadi, Ali, 2011. "An analysis of energy use and relation between energy inputs and yield, costs and income of garlic production in Iran," Renewable Energy, Elsevier, vol. 36(6), pages 1808-1813.
    19. Rajabi Hamedani, Sara & Keyhani, Alireza & Alimardani, Reza, 2011. "Energy use patterns and econometric models of grape production in Hamadan province of Iran," Energy, Elsevier, vol. 36(11), pages 6345-6351.
    20. 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).

    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:energy:v:37:y:2012:i:1:p:171-176. 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.journals.elsevier.com/energy .

    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.