Antanasijević, D., V. Pocajt, M. Ristić, and A. Perić-Grujić. 2015. Modeling of energy consumption and related GHG (greenhouse gas) intensity and emissions in Europe using general regression neural networks. Energy 84: 816-824.
2. Aydin, G. 2014. Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections. Renewable and Sustainable Energy Reviews 35: 382-389.
3. Aydinalp-Koksal, M., and V. I. Ugursal. 2008. Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector. Applied Energy 85: 271-296.
4. Change, I. P. O. C. 2006. IPCC guidelines for national greenhouse gas inventories.
5. Contreras, A., G. Diaz, L. Gallardo, and R. Loaiza. 2010. Energy ratio analysis of genetically-optimized potato for ethanol production in the Chilean market. Spanish journal of agricultural research 559-569.
6. Dalgaard, T., N. Halberg, and J. R. Porter. 2001. A model for fossil energy use in Danish agriculture used to compare organic and conventional farming. Agriculture, Ecosystems & Environment 87: 51-65.
7. Dyer, J., and R. Desjardins. 2003. Simulated farm fieldwork, energy consumption and related greenhouse gas emissions in Canada. Biosystems Engineering 85: 503-513.
8. Erdal, G., K. Esengün, H. Erdal, and O. Gündüz. 2007. Energy use and economical analysis of sugar beet production in Tokat province of Turkey. Energy: 35-41.
9. França, D. d. A., K. M. Longo, T. G. S. Neto, J. C. Santos, S. R. Freitas, B. F. Rudorff, E. V. Cortez, E. Anselmo, and J. A. Carvalho. 2012. Pre-harvest sugarcane burning: determination of emission factors through laboratory measurements. Atmosphere 3: 164-180.
10. Hatirli, S. A., B. Ozkan, and C. Fert. 2005. An econometric analysis of energy input–output in Turkish agriculture. Renewable and Sustainable Energy Reviews 9: 608-623.
11. Hatirli, S. A., B. Ozkan, and C. Fert. 2006. Energy inputs and crop yield relationship in greenhouse tomato production. Renewable Energy 31: 427-438.
12. Khan, S., M. A. Khan, M. A. Hanjra, and J. Mu. 2009. Pathways to reduce the environmental footprints of water and energy inputs in food production. Food Policy 34: 141-149.
13. Khoshnevisan, B., Sh. Rafiee, M. Omid, M. Yousefi, and M. Movahedi. 2013a. Modeling of energy consumption and GHG (greenhouse gas) emissions in wheat production in Esfahan province of Iran using artificial neural networks. Energy 52: 333-338.
14. Khoshnevisan, B., Sh. Rafiee, M. Omid, H. Mousazadeh, and P. Sefeedpari. 2013b. Prognostication of environmental indices in potato production using artificial neural networks. Journal of Cleaner Production: http://dx.doi.org/10.1016/j.jclepro.2013.1003.1028.
15. Kiani, M. K. D., B. Ghobadian, T. Tavakoli, A. Nikbakht, and G. Najafi. 2010. Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol-gasoline blends. Energy 35: 65-69.
16. Kitani, O., T. Jungbluth, R. M. Peart, and A. Ramdani. 1999. CIGR handbook of agricultural engineering, Volume 5: Energy and biomass engineering. American Society of Agricultural Engineers (ASAE).
17. Mobtaker, H. G., A. Keyhani, A. Mohammadi, Sh. Rafiee, and A. Akram. 2010. Sensitivity analysis of energy inputs for barley production in Hamedan Province of Iran. Agriculture, Ecosystems & Environment 137: 367-372.
18. Mohammadi, A., and M. Omid. 2010. Economical analysis and relation between energy inputs and yield of greenhouse cucumber production in Iran. Applied Energy 87: 191-196.
19. Nemecek, T., D. Dubois, O. Huguenin-Elie, and G. Gaillard. 2011. Life cycle assessment of Swiss farming systems: I. Integrated and organic farming. Agricultural Systems 104: 217-232.
20. Ozkan, B., A. Kurklu, and H. Akcaoz. 2004. An input–output energy analysis in greenhouse vegetable production: a case study for Antalya region of Turkey. Biomass and Bioenergy 26: 89-95.
21. Pishgar-Komleh, S., M. Ghahderijani, and P. Sefeedpari. 2012. Energy consumption and CO2 emissions analysis of potato production based on different farm size levels in Iran. Journal of Cleaner production 33: 183-191.
22. Rajaeifar, M. A., A. Akram, B. Ghobadian, Sh. Rafiee, and M. D. Heidari. 2014. Energy-economic life cycle assessment (LCA) and greenhouse gas emissions analysis of olive oil production in Iran. Energy 66: 139-149.
23. Ramedani, Z., Sh. Rafiee, and M. Heidari. 2011. An investigation on energy consumption and sensitivity analysis of soybean production farms. Energy 36: 6340-6344.
24. Samavatean, N., Sh. Rafiee, H. Mobli, and A. Mohammadi. 2011. An analysis of energy use and relation between energy inputs and yield, costs and income of garlic production in Iran. Renewable Energy 36: 1808-1813.
25. Sami, M., M. J. Shiekhdavoodi, M. Pazhohanniya, and F. Pazhohanniya. 2014. Environmental comprehensive assessment of agricultural systems at the farm level using fuzzy logic: A case study in cane farms in Iran. Environmental Modelling & Software 58: 95-108.
26. Sandhu, H. S., R. A. Gilbert, G. Kingston, J. F. Subiros, K. Morgan, R. W. Rice, L. Baucum, J. M. Shine Jr and L. Davis. 2013. Effects of sugarcane harvest method on microclimate in Florida and Costa Rica. Agricultural and Forest Meteorology 177: 101-109.
27. Wang, X., Y. Chen, P. Sui, W. Gao, F. Qin, J. Zhang, and X. Wu. 2014. Emergy analysis of grain production systems on large-scale farms in the North China Plain based on LCA. Agricultural Systems 128: 66-78.
28. Zangeneh, M., M. Omid, and A. Akram. 2010. A comparative study on energy use and cost analysis of potato production under different farming technologies in Hamadan province of Iran. Energy 35: 2927-2933.
)
ارسال نظر در مورد این مقاله