Qualitative and Quantitative Features Evaluation of Two Methods of Sugarcane Harvesting (with aim of Energy and Sugar Production)

Andekaeizadeh, K.; Sheikhdavoodi, M. J.; Byria, M.

doi:10.22067/jam.v8i1.53629

Document Type : Short Paper

Authors

¹ Shahid Chamran University of Ahvaz

² Department of Biomechanical Mechanics, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran

³ Ph.D. Student in Soil Science, Ramin University of Agriculture and Natural Resources, Ahvaz, Iran

https://doi.org/10.22067/jam.v8i1.53629

Abstract

Introduction
Sugarcane is an important plant in the world that cultivate for the production of sugar and energy. For this purpose, evaluation of Sugarcane (SC) and Energycane (EC) methods is necessary. Energy is vital for economic and social development and the demand for it is rising. The international community look toward alternative to fossil fuels is the aim of using liquid fuel derived from agricultural resources. According to calculations, about 47% from renewable energy sources in Brazil comes from sugarcane so as, the country is known the second largest source of renewable energy. Sugarcane in Brazil provides about 17.5% of primary energy sources. Material such as bagasse and ethanol are derived from sugarcane that provide 4.2% and 11.2 % consumed energy, respectively . In developing countries, the use of this product increase in order to achieve self-sufficiency in the production of starch and sugar and thus independence in bioethanol production. Evaluation of energy consumption in manufacturing systems, show the measurement method of yield conversion to the amount of energy. Many of products of Sugarcane have ability to produce bioenergy. Many materials obtain from sugarcane such as, cellulosic ethanol, biofuels and other chemical materials. Hence, Energycane is introduced as a new method of sugarcane harvesting. But, one of the problems of this method is high cost and high energy consumption of harvester. So that the total cost of Energycane method is 38.4 percent of production total costs, whereas, this cost, in Sugarcane method is 5.32 percent of production total costs.
In a study that was conducted by Matanker et al. (2014) with title “Power requirements and field performance in harvesting EC and SC”, the power requirements of some components of sugarcane harvester and its field capacity, in Sugarcane and Energycane methods were examined. The consumed power by basecutter, elevator and chopper was measured in terms of Mega grams per hour (Mg.h^-1)
Chopper energy consumption in Energycane method was 1.65 KJ more than Sugarcane method. The quantitative parameters including forward speed (km.h^-1), field capacity (ha.h^-1), the field performance (Mg.ha^-1) and reed output (Mg.h^-1) were also measured. Finally, statistical comparison was conducted between the two methods. The aim of this study is to provide Simple Additive Weighting (SAW) method using the calculated parameters by the Matanker et al. This method provides decision-making ability for a manager.

Materials and Methods
In this study, quantitative parameters including fuel consumption (Lit.ha^-1), harvester power (kW), efficiency of engine torque (%), energy of used hydraulic oil in basecutter, chopper and elevator (Mj.Mg^-1), forward speed (km.h^-1), field capacity (ha.h^-1), the field performance (Mg.ha^-1) and reed output (Mg.h^-1 ) and qualitative parameters including the mean of average diameter of the stem (mm), stem height (m), number of stems on the meter (m^-1), the percentage of cut stems and intact, cut stems and partially damaged and strongly damaged stems. The average height of straw and the stubble (mm), average of bulk density (kg.m^-3), the average of moisture content, average of dry matter (biomass), (Mg.ha^-1) were measured. Data analysis was conducted with Simple Additive Weighting (SAW) method. Tables 1 and 2 in terms of qualitative and quantitative parameters for the two methods of A and B, to form of rij matrix and based on measured criteria (C) have arranged, respectively.
Conclusion
Choosing the appropriate method for sugarcane harvesting should be according to the purpose of harvesting. Energycane method has high energy consumption that it increases the operational costs. On the other hand, the quality of the obtained biomass from it is better, but Sugarcane method has high energy efficiency. But in terms of quality, the plant is not in good condition. For this reason, it is necessary, aim of harvesting and its type, be specified before crop planting.

Keywords

20.1001.1.22286829.1397.8.1.17.9

References

1. Abubakar, M., and B. Umar, 2006. Comparison of energy use patterns in Maiduguri and yoke flour mills Nigeria. The CIGR Journal of Scientific Research and Development, Agricultural Engineering International 16. Available at: http://cigrjournal.org/index.php/Ejounral/article/view/671. Accessed to May 2006.

2. Bagheri Neshani, A., A. A. Zeraei, and M. Bahadorifar. 2013. Impact assessment of economic, social and ecological production of bioethanol from SC and maize in rural areas. Second National Conference on Renewable Energy and Clean, Tehran. 10 Pages. (In Farsi).

3. Balocco, C., and D. Verdesca. 2007. Shannon entropy for energy technologies ex-ante evaluation. International Journal of Environmental Technology and Management 7(1/2): 197-217. Available at: http://dx.doi.org/10.1504/IJETM.2007.013245. Accessed may 2007.

4. Brasil. 2012. Ministe´ rio de Minas e Energia. Balanc¸o energe´tico nacional. Brası´lia. Available at: https://ben.epe.gov.br/downloads/S%c3%adntese%20do%20Relat%c3%b3rio%20Final_2012_Web.pdf.

5. Chen, S. J., and C. L. Hwang. 1992. Fuzzy Multiple Attribute Decision Making: Methods and Applications. Springer Verlag, New York.

6. Heragu, S. 1997. Facilities Design. PWS Publishing, Boston. Massachusetts.

7. Hwang, C. L., and Yoon, K. 1981. Multiple Attribute Decision Making – Method and Applications, A State of the Art Survey. Springer Verlag, New York.

8. Kabassi, K., and M. Virvou. 2004. Personalised adult e-training on computer use based on multiple attribute decision making. Interacting with Computers 16, 115–132. Available at: http://www.sciencedirect.com/science/article/pii/S0953543803001127. Accessed February 2004.

9. Knoll, J. E., W. F. Anderson, T. C. Strickland, R. K. Hubbard, and R. Malik. 2012. Low-input production of biomass from perennial grasses in the coastal plain of Georgia, USA. Bioenergy Research 5 (1): 206-214. Available at: http://link.springer.com/article/10.1007%2Fs12155-011-9122-x. Accessed May 2012.

10. Maccrimmon, K. R. 1968. Decision making among multiple attribute alternatives: A survey and consolidated approach. RAND Memorandum, RM-4823-ARPA. 78 pages. Available at: http://www.rand.org/pubs/research_memoranda/RM4823.html. Accessed December 1968.

11. Mantoam, J. E., M. Milan, M. L. Gimenez, and L. Th. Romaneli. 2014. Embodied energy of SC harvesters. Biosystem Engineering. 155-166. Available at: http://www.sciencedirect.com/science/article/pii/S1537511013001992. Accessed January 2014.

12. Mathanker, S. K., H. Gan, J. C. Buss, B. Lawson, A. C. Hansen, and K. C. Ting. 2015. Power requirements and field performance in harvesting EC and SC. Biomass and Bioenergy 75: 227-234. Available at: http://www.sciencedirect.com/science/article/pii/S0961953415000616. Accessed April 2015.

13. Mislevy, P., and R. C. Fluck. 1992. Harvesting operations and energetics of tall grasses for biomass energy production: a case study. Biomass Bioenergy 3 (6): 381-387. Available at: http://www.sciencedirect.com/science/article/pii/096195349290033M. Accessed June 1992.

14. Mislevy, P., F. G.Martin, M. B. Adjei, and D. J. Miller. 1995. Agronomic characteristics of US 72-1153 energycane for biomass. Biomass and Bioenergy. 449-457. Available at: http://www.sciencedirect.com/science/article/pii/096195349500050X. Accessed May 1995.

15. Richard, E. P., and W. F. Anderson. 2014. SC, EC, and napiergrass. In: Karlen DL, editor. Cellulosic energy cropping systems. John Wiley & Sons, Ltd. p. 91-108.

16. Salassi, M. E. and Barker, F.G. 2008. Reducing harvest costs through coordinated SC harvest and transport operations in Louisiana. Journal Assoc SC Technol 28: 32-41. Available at: http://agris.fao.org/agris-search/search.do?recordID=US201301692925.

17. Shakouri, H., M. Nabaee, and S. Aliakbarisani. 2014. A quantitative discussion on the assessment of power supply technologies: DEA (data envelopment analysis) and SAW (simple additive weighting) as complementary methods for the “Grammar”. Energy (64): 640-647. Available at: http://www.sciencedirect.com/science/article/pii/S0360544213008712. Accessed January 2014.

18. Wang, Y. J. 2015. A fuzzy multi-criteria decision-making model based on simple additive weighting method and relative preference relation. Applied Soft Computing 30: 412-420. Available at: http://www.sciencedirect.com/science/article/pii/S1568494615000903. Accessed May 2015.

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Journal of Agricultural Machinery

Qualitative and Quantitative Features Evaluation of Two Methods of Sugarcane Harvesting (with aim of Energy and Sugar Production)

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Volume 8, Issue 1 - Serial Number 15
Spring and Summer
2018
Pages 212-221

Qualitative and Quantitative Features Evaluation of Two Methods of Sugarcane Harvesting (with aim of Energy and Sugar Production)

References

References

Send comment about this article

Volume 8, Issue 1 - Serial Number 15Spring and Summer 2018Pages 212-221

Volume 8, Issue 1 - Serial Number 15
Spring and Summer
2018
Pages 212-221