MONTE CARLO SIMULATION MODEL OF ENERGY CONSUMPTION IN WHEAT PRODUCTION SYSTEMS UNDER EGYPTIAN CONDITIONS

Document Type : Original Article

Authors

1 Professor, Agric. Eng. Dept. Faculty of Agriculture – Cairo University, Egypt.

2 Associate Professor, Soils and water Dept. Faculty of Agriculture – Cairo University, Egypt.

3 Ph. D Student, Agric. Eng. Dept. Faculty of Agriculture – Cairo University, Egypt.

Abstract

The Monte Carlo simulation method was used in this study to examine uncertainty propagation in a modeled irrigated wheat production system in Egypt. After running the Monte Carlo Simulation for 10000 runs for each operation, the alternative with higher frequency in each operation was selected and the energy consumption was calculated. The result of the current study was new system in addition to the nineteen systems involved. The total energy consumption was10205.09MJ/fed. This system consisted of Chisel plow 1st pass+ Disc harrow+ Steel leveler + Wooden Ridger + Mounted seed drill + Surface irrigation + Manual fertilizer Broadcasting + Manual operated knapsack sprayer + Combine. Among the nineteen systems involved in the study, the highest energy consumption system was system thirteen which consumed14650.8 MJ /Fed. The system of minimum energy consumption within the 19 systems used in this study was S4 with 10109.174 MJ /fed. This system consisted of Mould board Plow+ Disc harrow+ Wooden leveller+ Wooden ridger+ Mounted seed drill + Surface irrigation+ Manual fertilizer broadcasting + Manual operated knapsack Sprayer +Self-propelled mower+ Trailer + Stationary threshing machine. It can be concluded from the results of this study that Monte Carlo simulation model is capable of selecting the minimum energy consumption wheat production system.

Keywords

References

Abd EI-Ghany, H.M.; Abd EI-Salam, M.S.; Hozyen, M. and Afifi , M.H.M.(2012). Effect of deficit irrigation on some growth stages of wheat. Journal of applied sciences research, 8(5):2776-2784.ISSN 1819-544X.
Al-Ghandoor, A.; Jaber J.O.; Al-Hinti I. and Mansour I.M. (2009). Residential past and future energy consumption: Potential savings and environmental impact. Renewable and Sustainable Energy Reviews. 13(6-7):1262-74.
Asakereh, A.;Shiekhdavoodi, M.J. and Akram, A.(2010).Investigation of Energy Consumption in Agriculture Sector of Iran and their Effect on Air Pollution and Social Cost. Research Journal of Applied Sciences Engineering and Technology 2(5): 401-406, 2010 ISSN: 2040-7467.
Ayyub, B. and Klir, G. (2006). Uncertainty Modeling and Analysis in Engineering and the Sciences. Taylor & Francis Group, Boca Raton, FL. 378p.
Bonate, P.L. (2001). A Brief Introduction to Monte Carlo Simulation. ClinPharmacokinet, 40 (1): 15-22.
Chaudhary, V.P.;Gangwar B, Pandey, D.K. (2006). Auditing of energy use and output of different cropping systems in India. Agricultural Engineering international the CIGR journal. 5: 1–13.
Davoodi, M.J.  and Houshyar, E. ( 2009). Energy Consumption of Canola and Sunflower Production in Iran. American-Eurasian J. Agric. & Environ. Sci., 6 (4): 381-384.
Embaby, A. T. (1985).A comparison of the different mechanization systems for cereal crop production. M.Sc. thesis, Agric. Eng. Dept. Faculty of agriculture. Cairo University.
FAO(2012). FAO Stat, http://faostat.fao.org/default.aspx
Gupta, A. (2011). Monte Carlo simulations modeling and applications.  Indian institute of technology, Kanpur, Indian.
Huseby, A. B.; Vanem, E. and Natvig, B. (2013). A new approach to environmental contours for ocean engineering applications based on direct Monte Carlo simulations, Ocean Engineering, 60, 124-135.
Jacoboni, C. and Lugli, P. (1989). The Monte Carlo Method for Semiconductor Device Simulation, Springer-VerJag/Wien, 1989.
Karimi, M.; Rajabi, P. A.; Tabatabaeefar, A. and Borghei, A. (2008). Energy Analysis of Sugarcane Production in Plant Orchards A Case Study in DebelKhazai Agro-industry in Iran. American-Eurasian J. Agric. Environ. Sci., 4(2): 165-171.
Kizilaslan, H. (2009). Input-output energy analysis of cherries production in Tokat Province of Turkey. Applied Energy. 86: 1354-1358.
Korytkowski, P.; Wisniewski, T.;Rymaszewski, S., (2013). An evolutionary simulation-based optimization approach for dispatching scheduling, Simulation Modeling Practice and Theory, 35, 69-85
Landau, D. P. and Binder, K. A. (2000).Guide to Monte Carlo Simulations in Statistical Physics, Second Edition, Cambridge university press.
Law, A.M. and Kelton, W.D. (2000). Simulation Modeling and Analysis, Third ed., McGraw-Hill, New York.
Mohammadi, A.; Tabatabaeefar, A.; Shahin,S.;Rafiee, S. and Keyhani, A. (2008). Energy use and economic analysis of potato production in Iran a case study: Ardabil province. Energy Conversion Manage. 49:3566-3570.
Pellizzi, G. (1992). Use of energy and labour in Italian agriculture. Journal of Agricultural Engineering Research. 52:111-9.
Raychaudhuri, S.(2008).Introduction  to Monte Carlo Simulation. Proceedings of the 2008 Winter Simulation Conference.S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. Oracle Crystal Ball Global Business Unit 390 Interlocken Crescent, Suite 130 Broomfield, C.O. 80021, U.S.A.
Richard, C.F. (1992). Energy in farm production. (Elsevier publishing: Netherlands).
Rubinstein, R.Y. (1981). Simulation and the Monte Carlo method. New York: John Wiley and Sons, Inc. Sciences. Taylor & Francis Group, Boca Raton, FL. 378p.
Shrestha, D.S. (1998). Energy use efficiency indicator for agriculture. http://www.usaskca/agriculture/caedac/PDF/mcrae.PDF; Accessed, March 2012.
Singh, A. K.; Goyal, V.; Mishra, A. K. and Parihar, S. S.( 2013). Validation of CropSyst simulation model for direct seeded rice–wheat cropping system. CURRENT SCIENCE, VOL. 104, NO. 10, 25.
 Tester, J. ( 2005). Sustainable energy : choosing among options. Cambridge,Mass.: MIT Press.
Verma, S. (1987). Energy in production agriculture and food processing. Prpceeding of the National Conference held at the Punjab Agricultural University ,Ludhana. October 30-31. 
Villada, J. and  Olaya, Y. (2013), A simulation approach for analysis of short-term security of natural gas supply in Colombia, Energy Policy, 53, 11-26.
Winston, W.L. (1991). Operations Research Applications and Algorithms (2nd Ed.).
Woolfson, M. M. and Pert, G.J. (1999). An Introduction to Computer Simulation, Oxford New York, 1999.
Yilmaz, I.; Akcaoz, H. and Ozkan, B. (2005).An analysis of energy use and input costs for cotton production in Turkey. Renew. Ene. 30:145-155.
Misr Journal of Agricultural Engineering
Volume 31, Issue 2
April 2014
Pages 379-402

Files

Share

How to cite

Statistics