Document Type : Research Paper

Abstract

The increase in mechanized harvesting and harvesting machinery has led to the development of scientific approaches for choosing the best harvesting system. Seed corn is an important crop in Iran that is very sensitive to the harvesting system and has high economic value. There are several systems and machines that can be used to harvest seed corn, but all systems should be evaluated precisely. The present study evaluated a two-stage harvesting system (picker-husker), grain combine, and Wintersteiger combine for seven criteria (harvesting loss, energy usage, rent of machinery, safety and comfort of operator, instruction required, maintenance cost, field capacity) using TOPSIS and SAW models. The results of TOPSIS were CL* values of 0.60, 0.57 and 0.42 for picker-husker, grain combine, and Wintersteiger combine, respectively. A* values for the SAW model were 0.78, 0.55 and 0.49, respectively. The calculations produced the same results for the two models and it was concluded that the best system was the picker-husker harvesting system, followed by the grain combine and then the Wintersteiger combine.

Keywords

Anon. 2006. Agricultural Machinery Management Data. Standards. D497.5. American Society of Agricultural and Biological Engineers (ASABE).
Asgharpour, M. J. 2006. Multiple Criteria Decision Making. Tehran University Press. Tehran. Iran.
(in Farsi)
Azizi, M., Amiri, S. and Memariani, A. 2006. A study of plywood and veneer industry choice location, and identification of provinces in Iran, suitable for establishment of the industry. Iranian J. Nat. Res. 59(2): 446-456. (in Farsi)
Butani, K. M. and Singh, G. 1994. Decision support system for the selection of agricultural machinery with a case study in India. Comput. Electron. Agric. 10, 91-104.
Germain, B. S., Charania, A. and Olds, J. 2005. A stochastic process for prioritizing lunar exploration technology. American Institute of Aeronautics and Astronautics. Aug. 30- Sep.1. Long Beach. California. USA.
Ghanbarpour, M. R. and Hipel, K. W. 2011. Multi-criteria planning approach for ranking of land management alternatives at different spatial scales. Res. J. Environ. Earth Sci. 3(2): 167-176.
Ghazinoori, S. S. and Tabtabaeian, H. 2002. Sensitivity analysis of multi attribute decision making. Manag. Knowl. 56, 129-141. (in Farsi)
Grei, A. 2006. Representation of uniform model for project-based organizations projects basket management. Proceeding of the 3rd International Conference on Project Management. Oct. 7. Tehran. Iran. (in Farsi)
Hwang, C. L. and Yoon, K. 1981. Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag. Berlin.
Kline, D. E., Bender, A., Mc Carl, B. A. and Van Donge, C. E. 1988. Machinery selection using expert systems and linear programming. Comput. Electron. Agric. 3, 45-61.
Lak, M. B. and Borghaee, A. M. 2011. Multi-criteria decision making based in choosing an appropriate tractor (A case study for Hamedan province). J. Agric. Machinery Eng. 1(1): 41-47. (in Farsi)
Mansouri-Rad, D. 2003. Farm Machinery and Tractor. Bu Ali Sina University Press. Hamedan. Iran.
(in Farsi)
Mc Clendon, R. W., Wetzstein, M. E. and Edwards, L. H. 1987. Risk efficiency of machinery selection for double cropping via simulation. T. ASAE. 30(5): 1259-1265.
Momeni, M. 2008. New Topics in Operations Research. Tehran University Press. Tehran. Iran. (in Farsi)
Momeni, M. and Eghbal, Sh. 2004. Sugar cane handling system selection using fuzzy TOPSIS. J. Quant. Econ. 1(2): 21-37. (in Farsi)
Parmar, R. S., Mc Clendon,  R. W. and Potter, W. D. 1996. Farm machinery selection using simulation and genetic algorithms. T. ASAE. 39(5): 1905-1909.
Parthanadee, P. and Buddhakulsomsiri, J. 2010. Simulation modeling and analysis for production scheduling using real-time dispatching rules: a case study in canned fruit industry. Comput. Electron. Agric. 70, 245-255.
Pishgar-Komleh, S. H., Keyhani, A., Mostofi-Sarkari, M. R. and Jafari, A. 2011. The effect of cylinder speed and feeding rate of Wintersteiger combine on seed corn harvesting losses. Proceeding of the 5th National Symposium on Losses of Agricultural Products. Oct. 31. Tehran. Iran. (in Farsi)
Sarkheil, S. and Navid, H. 2010. Evaluating and choosing tractors between four kinds of tractors in
engine power of 30 to 90 KW by applying Analytic Hierarchy Process (AHP). Proceeding of the
6th National Conference on Agricultural Machinery Engineering & Mechanization. Sep. 15-16. Karaj. Iran. (in Farsi)
Sogaard, H. T. and Sorensen, C. G. 2004. A model for optimal selection of machinery sizes within the farm machinery system. Biosystems Eng. 89(1): 13-28.
Wang, T. C. and Chang, T. H. 2007. Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Syst. Appl. 33(4): 870-880.
Wang, Y. M. and Elhag, T. M. 2006. Fuzzy TOPSIS method based on alpha level sets with an application to bride risk assessment. Expert Syst. Appl. 31, 309-319.