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Energy audit of Iranian kiwifruit production using intelligent systems

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  • Soltanali, Hamzeh
  • Nikkhah, Amin
  • Rohani, Abbas

Abstract

Optimizing the energy flows of agricultural production is a concern in order to find the most appropriate mix of agricultural inputs, which would in turn minimize energy consumption and maximize energy output. Thus, the aim of this study is to model the energy flows of kiwifruit production in Guilan province of Iran (as a case study) using Artificial Neural Network (ANN) + Genetic Algorithm (GA) modeling and Multiple Linear Regressions (MLR) + GA modeling. The results indicated that the highest energy consumption were attributed to electricity and chemical fertilizers with the shares of 42% and 25%, respectively. Energy indices such as energy use efficiency, energy productivity, specific energy and net energy were determined to be 0.48, 0.25 kgMJ−1, 4.01 MJkg−1, and -54,644 MJha−1. The performance indices such as coefficient of determination (R2) and efficiency (EF) for the best MLR model were determined to be 0.61 and 0.60%, respectively. Moreover, the same indices for the best developed ANN model were 0.73 and 0.72%, respectively. Overall, it was concluded that the ANNs models could better predict the energy output than the MLRs models and the performance of ANN highlighted that this model may be applied to prognosticate the energy output of kiwifruit production. To conclude, a comparison between ANN + GA and MLR + GA clearly demonstrated the better performance of ANN + GA to optimize the energy flows of Iranian kiwifruit production.

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  • Soltanali, Hamzeh & Nikkhah, Amin & Rohani, Abbas, 2017. "Energy audit of Iranian kiwifruit production using intelligent systems," Energy, Elsevier, vol. 139(C), pages 646-654.
    • Handle: RePEc:eee:energy:v:139:y:2017:i:c:p:646-654
    DOI: 10.1016/j.energy.2017.08.010
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    as
    1. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    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. Kalogirou, Soteris A., 2004. "Optimization of solar systems using artificial neural-networks and genetic algorithms," Applied Energy, Elsevier, vol. 77(4), pages 383-405, April.
    4. Betiku, Eriola & Okunsolawo, Samuel S. & Ajala, Sheriff O. & Odedele, Olatunde S., 2015. "Performance evaluation of artificial neural network coupled with generic algorithm and response surface methodology in modeling and optimization of biodiesel production process parameters from shea tr," Renewable Energy, Elsevier, vol. 76(C), pages 408-417.
    5. 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.
    6. 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.
    7. Mohammadi, Ali & Rafiee, Shahin & Mohtasebi, Seyed Saeid & Rafiee, Hamed, 2010. "Energy inputs – yield relationship and cost analysis of kiwifruit production in Iran," Renewable Energy, Elsevier, vol. 35(5), pages 1071-1075.
    8. Gueguim Kana, E.B. & Oloke, J.K. & Lateef, A. & Adesiyan, M.O., 2012. "Modeling and optimization of biogas production on saw dust and other co-substrates using Artificial Neural network and Genetic Algorithm," Renewable Energy, Elsevier, vol. 46(C), pages 276-281.
    9. 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.
    10. Mardani, Aref & Taghavifar, Hamid, 2016. "An overview on energy inputs and environmental emissions of grape production in West Azerbayjan of Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 918-924.
    11. Ozkan, Burhan & Ceylan, R. Figen & Kizilay, Hatice, 2011. "Comparison of energy inputs in glasshouse double crop (fall and summer crops) tomato production," Renewable Energy, Elsevier, vol. 36(5), pages 1639-1644.
    12. 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.
    13. 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.
    14. 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.
    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. 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.
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