Evaluation and Comparison of Environmental Indicators of Hybrid Corn (Zea mays L.) Production by Three Different Harvesting Methods in Alborz Province using Life Cycle Assessment

Document Type : Scientific - Research

Authors

• Majid Khanali
• behzad elhami
• Hadi Eslami
• soleiman hosseinpour

University of Tehran

10.22067/jag.v9i4.52447

Abstract

Introduction
Agriculture itself serves a dual role as an energy user and also energy supplier in the form of bio-energy. Recently, the energy use in agriculture has been intensified in response to the rising population, the increasing of standards of living and the limitation sources of energy. Efficient use of energy is a possible pathway for reducing the environmental impacts of energy inputs in agriculture, and providing sustainable agricultural production, since it brings financial savings, fossil resources preservation and air pollution reduction. Life cycle assessment (LCA) is defined as the compilation and evaluation of the inputs, outputs and potential environmental impacts of a product system throughout its life cycle. Hybrid seed in agriculture is produced by cross-pollinated plants. Hybrid seed production is one of the main contributors to the dramatic rise in agricultural output during the last half of the 20th century. The alternatives to hybridization are open pollination and cloonal propagation. All of the hybrid seeds planted by the farmer will produce similar plants while the seeds of the next generation from those hybrids will not consistently have the desired characteristics. Controlled hybrids provide very uniform characteristics because they are produced by crossing two inbred strains.

Materials and Methods
The purpose of this study was to compare the energy consumption pattern and environmental consequences caused by the use of agricultural inputs in the production of seed corn harvested by hand, combine and picker husker. Information required was prepared by the questionnaire method in Alborz Province using census the total producers of hybrid corn in the Province. The investigated inputs were labor, agricultural machinery, diesel fuel, chemical pesticides, fertilizers, gas, electricity, water and seed. The energy of each input was calculated by multiplying the amount of that input with its energy equivalent. The ten environmental indicators including eutrophication potential (EP), global warming potential (GWP), acidification potential (AP), ozone layer depletion (OD), abiotic depletion (AD), photochemical oxidation (PO), human toxicity (HT), terrestrial ecotoxicity (TE), marine aquatic ecotoxicity (MAE) and fresh water aquatic ecotoxicity (FAE) were investigated. LCA was conducted using Sima Pro software from cradle to grave, i.e., from the production of raw materials to the production of hybrid corn considering the both farming and processing stages. One ton of produced hybrid corn was chosen as the functional unit in this study.

Results and Discussion
Total energy input to produce hybrid corn harvested by hand, combine and picker husker methods were calculated as 118711, 111335 and 120403 MJ ha-1, respectively. Electricity and nitrate fertilizer were the most important energy inputs for their investigated harvesting methods. The results of life cycle assessment revealed that electricity and diesel fuel used for irrigation had the most environmental impact in production of hybrid corn in the farm, while the consumption of fungicides had the largest environmental impacts in the processing stage. On the other hand, in harvesting method by picker husker, environmental indicators such as GWP, EU, HT, AP, AD and PO were higher than other harvesting methods. The different harvesting methods had no significant effect on OD and TE. MAE and FAE were higher than those of other harvesting methods because of the high consumption of diesel fuel and electricity in hand harvesting method,. Combine harvesting method had less environmental damage than other methods.

Conclusion
The combine harvesting method was recognized as the best harvesting method from environmental viewpoint. Electricity and diesel fuel consumption for supplying irrigation alter had the most environmental burdens in the agricultural stage. The right application of inputs such as herbicides and chemical fertilizers, substitution of non-renewable energy resources with renewable ones and green manure application can reduce the environmental burdens in hybrid corn production.

Acknowledgments
The authors would like to acknowledge the University of Tehran for providing the financial support for this research.

Keywords

• Environmental indicators
• Harvesting method
• Hybrid seed corn
• life cycle assessment

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References

Anonymous. 2013. Annual agricultural statistics, Ministry of Jahad-e-Agriculture of Iran (www.maj.ir). (In Persian)

Brasseur, G., and Granier, C. 1992. Mount Pinatubo aerosols, chlorofluorocarbons, and ozone depletion. Science 257: 1239-1242.

Brentrup, F., Küsters, J., Lammel, J., and Kuhlmann, H. 2000. Methods to estimate on-field nitrogen emissions from crop production as an input to LCA studies in the agricultural sector. International Journal of Life Cycle Assessment 5(6): 349-357.

CalderonIglesias, L., Laca, A., Herrero, M., and Diaz, M. 2010.The utility of life cycle assessment in the ready meal food industry. Resources, Conservation and Recycling 54(12): 1196-1207.

Cellura, M., Longo, S., and Mistretta, M. 2012. Life Cycle Assessment (LCA) of protected crops: An Italian case study. Journal of Cleaner Production 28: 56-62.

Choghan, R. 2004. The Production of‌‌‌ Maize Seed. Tehran, Iran: Education and Agricultural Extension p. 103. (In Persian)

Dalgaard, R., Schmidt, J., Halberg, N., Christensen, P., Thrane, M., and Pengue, W.A. 2007. LCA of soybean meal. International Journal of LCA 15: 1-15.

Elhami, B., Akram, A., and Khanali, M. 2016. Optimization of energy consumption and environmental impacts of chickpea production using data envelopment analysis (DEA) and multi objective genetic algorithm (MOGA) approaches. Information Processing in Agricuture 3(3):190-225.

EPA.1995. Compilation of air pollutant emissions factors (http://www.epa.gov.).

Erickson, J., Cisar, J., Volin, J., and Snyder, G. 2001. Comparing nitrogen run off and leaching between newly established St. Augustinegrass turf and an alternative residential landscape. Crop Science 41: 1889-1895.

Esmaeelpour, B., Khorramdel, S., and Amin Ghafouri, A. 2015. Investigation of environmental impacts in potato production systems in Iran based on nitrogen fertilizer using Life Cycle Assessment. Electronic Journal of Crop Production 8(3):199-224. (In Persian with English Summary)

Galloway, J.N., Schlesinger, W.H., Levy, H., Michaels, A., and Schnoor, J.L. 1995. Nitrogen fixation: Anthropogenic enhancement‐environmental response. Global Biogeochemical Cycles 9: 235-252.

Hauschild, M., and Wenzel, H. 1998. Environmental Assessment of Products. Scientific Background. London, NY: Chapman and Hall p. 237.

Iriarte, A., Rieradevall, J., and Gabarrell, X. 2009. Life Cycle Assessment of sunflower and rapeseed as energy crops under Chilean conditions. Journal of Cleaner Production 18: 336-345.

ISO. 2006. ISO 14040- Environmental Management– Life Cycle Assessment– Principles and Framework (www.iso.org).

Khoshnevisan, B., Rafiee, S., Omid, M., Mousazadeh, H., and Sefeedpari, P. 2013a. Prognostication of environmental indices in potato production using artificial neural networks. Journal of Cleaner Production 52: 402-409.

Khoshnevisan, B., Rafiee, S., Omid, M., Yousefi, M., and Movahedi, M. 2013b. 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.

Khoshnevisan, B., Rafiee, S., and Mousazadeh, H. 2013c. Environmental impact assessment of open field and greenhouse strawberry production. European Journal of Agronomy 50: 29-37.

Martinez-Blanco, J., Munoz, P., Anton, A., and Rieradevall, J. 2011. Assessment of tomato mediterranean production in open-field and standard multi-tunnel greenhouse, with compost or mineral fertilizers, from an agricultural and environmental standpoint. Journak of Cleaner Production 19: 985-997.

Mohammadi, A., Rafiee, S., Jafari, A., Dalgaard, T., Trydeman, M., Knudsen, M.T., Keyhani, A., Mousavi Avval, H., and Hermansen, J. 2013. Potential greenhouse gas emission reductions in soybean farming: A combined use of Life Cycle Assessment and data envelopment analysis. Journal of Cleaner Production 54: 89-100.

Nemecek, T., and Kagi, T. 2007. Life cycle inventories of agricultural production systems. Final report ecoinvent V2.0: No. 15, Dübendorf, CH: Swiss Centre for Life Cycle Inventories (http://www.EcoInvent.org/ documentation/reports).

Nemecek, T., Dubois, D., Huguenin-Elie, O., and Gaillard, G. 2011. Life cycle assessment of Swiss farming systems: I. Integrated and organic farming. Agricultural Systems 104: 217-232.

Ozkan. B., Akcaoz, H., and Fert, C., 2004. Energy input–output analysis in Turkish agriculture. Renewable Energy 29: 39-51.

Pourghasemian, N., and Moradi, R. 2017. Greenhouse gases emission and global warming potential as affected by chemical inputs for main cultivated crops in Kerman province: Horticultural Crops. Journal of Agroecology 9(3): 689-704. (In Persian with English Summery)

PRe Consultants, 2003. SimaPro 5 Database Manual.

Rahimyan, B. 2015. Determination of economic, energy and environmental indicators of some crops (sugarbeet, wheat and pea) in West Azarbaijan province (Boukan Region) using computional intelligence techniques. University of Tehran, College of Agriculture and Natural Resources, Faculty of Agricultural Engineering and Technology pp. 129. (In Persian)

Reddy, K.R., and Hodges, H.F. 2000. Climate Change and Global Crop Productivity. CABI p. 488.

Suh, S., Lenzen, M., Treloar, G.J., Hondo, H., Horvath, A., Huppes, G., Jolliet, O., Klann, U., Krewitt, W., and Moriguchi, Y. 2004. System boundary selection in life cycle inventories using hybrid approaches. Environmental Science and Technology 38: 657-664.