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Sustainability assessment and optimization of legumes production systems: energy, greenhouse gas emission and ecological footprint analysis

Published online by Cambridge University Press:  04 June 2021

Nahid Aghili Nategh Open the ORCID record for Nahid Aghili Nategh [Opens in a new window] ,
Narges Banaeian ,
Alireza Gholamshahi  and
Mohammad Nosrati
Nahid Aghili Nategh*
Affiliation:
Department of Agricultural Machinery Engineering, Sonqor Agriculture Faculty, Razi University, Kermanshah, Iran
Narges Banaeian*
Affiliation:
Department of Agricultural Mechanization Engineering, Faculty of Agricultural Sciences, University of Guilan, Guilan, Rasht, Iran
Alireza Gholamshahi
Affiliation:
Department of Agricultural Machinery Engineering, Sonqor Agriculture Faculty, Razi University, Kermanshah, Iran
Mohammad Nosrati
Affiliation:
Department of Agricultural Machinery Engineering, Sonqor Agriculture Faculty, Razi University, Kermanshah, Iran
*
Author for correspondence: Nahid Aghili Nategh, E-mail: [email protected]; Narges Banaeian, E-mail: [email protected]
Author for correspondence: Nahid Aghili Nategh, E-mail: [email protected]; Narges Banaeian, E-mail: [email protected]
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Abstract

This study examined energy, greenhouse gas emission and ecological footprint analysis (EFA) of chickpea and lentil cultivation with different mechanization production systems. In lentil production, except for tillage operations, other operations are performed manually and the remaining straw is burned in the field; while in chickpea production, most of the agricultural operations are mechanized and residues are collected, baled and transferred to the warehouse for animal feed. In this paper, for the first time, some of the sustainability indicators are investigated and compared in two different legume production systems. Energy productivity and net energy for chickpea and lentil production were calculated at 0.036, 0.161 and 2373 and 5900 MJ per hectare, respectively. The CO2 emission and ecological carbon footprint were 173 kg CO2−eq and 0.15 global hectare for lentil and 484 and 0.87 for chickpea production. Totally, due to excessive consumption of diesel fuel and lack of proper management, the social cost of emission from straw baling in chickpea production (27.65 dollars per hectare) was higher than burning straw in lentil production (8.77). Multi-objective genetic algorithm results showed the potential of minimizing diesel fuel and fertilizer consumption and no chemical for chickpea production. Overall audition results of two different production systems revealed that traditional lentil production is more sustainable. Therefore, implementations of modern agricultural practices alone are not enough to achieve sustainability in agricultural production systems.

Keywords

ChickpeaEFAenergylentilMOGAoptimization
Type
Research Paper
Information
Renewable Agriculture and Food Systems , Volume 36 , Issue 6 , December 2021 , pp. 576 - 586
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Aghili nategh, N, Banaeian, N, Gholamshahi, A and Nosrati, M (2020) Optimization of energy, economic and environmental indices in sunflower cultivation-a comparative analysis. Environmental Progress & Sustainable Energy 40, e13505.Google Scholar
Anielski, M and Wilson, J (2010) Environmental footprinting for agriculture in Alberta: literature review and analysis. Retrieved from Alberta, Canada.Google Scholar
Anonymous (2010) Iran agriculture statistics. Retrieved from Tehran – Iran.Google Scholar
Audsley, E, Stacey, K, Parsons, DJ and Williams, AG (2009) Estimation of the greenhouse gas emissions from agricultural pesticide manufacture and use. Retrieved from Cranfield, Bedford.Google Scholar
Banaeian, N and Zangeneh, M (2011) Study on energy efficiency in corn production of Iran. Energy 36, 5394–5402.CrossRefGoogle Scholar
Banaeian, N, Zangeneh, M and Omid, M (2010) Energy use efficiency for walnut producers using data envelopment analysis (DEA). Australian Journal of Crop Science 4, 359–362.Google Scholar
Banaeian, N, Omid, M and Ahmadi, H (2011) Energy and economic analysis of greenhouse strawberry production in Tehran province of Iran. Energy Conversion and Management 52, 1020–1025.CrossRefGoogle Scholar
Banaeian, N, Zangeneh, M and Clark, S (2020) Trends and future directions in crop energy analyses: a focus on Iran. Sustainability 12, 10002.CrossRefGoogle Scholar
Baran, MF and Gokdogan, O (2016) Determination of energy balance of sugar beet production in Turkey: a case study of Kırklareli Province. Energy Efficiency 9, 487–494.CrossRefGoogle Scholar
Borsato, E, Tarolli, P and Marinello, F (2018) Sustainable patterns of main agricultural products combining different footprint parameters. Journal of Cleaner Production 179, 357–367.CrossRefGoogle Scholar
Cellura, M, Longo, S, Marsala, G, Mistretta, M and Pucci, M (2013) The use of genetic algorithms to solve the allocation problems in the life cycle inventory. In Cavallaro, F (ed.), Assessment and Simulation Tools for Sustainable Energy Systems: Theory and Applications, Green Energy and Technology. London: Springer, pp. 267–284.CrossRefGoogle Scholar
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 Agriculture 3, 190–205.CrossRefGoogle Scholar
Elhami, B, Khanali, M and Akram, A (2017) Combined application of artificial neural networks and life cycle assessment in lentil farming in Iran. Information Processing in Agriculture 4, 18–32.CrossRefGoogle Scholar
FAO, Food and Agriculture Organization of the United Nations (2008) Livestock's long shadow-environmental issues and options. Retrieved from 2020.Google Scholar
Firouzi, S, Nikkhah, A and Rosentrater, KA (2017) An integrated analysis of non-renewable energy use, GHG emissions, carbon efficiency of groundnut sole cropping and groundnut-bean intercropping agro-ecosystems. Environmental Progress & Sustainable Energy 36, 1832–1839.CrossRefGoogle Scholar
GFN, Global Footprint Network (2009) Available at www.footprintnetwork.org/en/index.php/GFN.Google Scholar
Gharakhlou, M, Abdi, N and Shahraki, Z (2009) Analysis of the level of urban sustainability in informal settlements of Sanandaj (Persian). Human Geography Research 42, 1–16.Google Scholar
Haq, ME (2014) Carbon footprint of selected cereal and legume crops cultivated in the old Brahmaputra floodplain soil. (master), Bangladesh agricultural university Mymensingh, Bangladesh.Google Scholar
Hosseinzadeh-Bandbafha, H, Nabavi-Pelesaraei, A, Khanali, M, Ghahderijani, M and Chau, K-W (2018) Application of data envelopment analysis approach for optimization of energy use and reduction of greenhouse gas emission in peanut production of Iran. Journal of Cleaner Production 172(Suppl C), 1327–1335.CrossRefGoogle Scholar
Houshyar, E, Mahmoodi-Eshkaftaki, M and Azadi, H (2017) Impacts of technological change on energy use efficiency and GHG mitigation of pomegranate: application of dynamic data envelopment analysis models. Journal of Cleaner Production 162(Suppl C), 1180–1191.CrossRefGoogle Scholar
Ilahi, S, Wu, Y, Raza, MA, Wei, W, Imran, M and Bayasgalankhuu, L (2019) Optimization approach for improving energy efficiency and evaluation of greenhouse gas emission of wheat crop using data envelopment analysis. Sustainability 11, 1–15. doi: 10.3390/su11123409.CrossRefGoogle Scholar
Khoshnevisan, B, Rafiee, S, Omid, M and Mousazadeh, H (2013) Reduction of CO2 emission by improving energy use efficiency of greenhouse cucumber production using DEA approach. Energy 55(Suppl C), 676–682.CrossRefGoogle Scholar
Khoshnevisan, B, Bolandnazar, E, Shamshirband, S, Shariati, HM, Anuar, NB and Mat Kiah, ML (2015) Decreasing environmental impacts of cropping systems using life cycle assessment (LCA) and multi-objective genetic algorithm. Journal of Cleaner Production 86, 67–77.CrossRefGoogle Scholar
Kissinger, M and Gottlieb, D (2012) From global to place oriented hectares—the case of Israel's wheat ecological footprint and its implications for sustainable resource supply. Ecological Indicators 16, 51–57.CrossRefGoogle Scholar
Koocheki, A, Ghorbani, R, Mondani, F, Alizade, Y and Moradi, R (2011) Pulses production systems in term of energy use efficiency and economical analysis in Iran. International Journal of Energy Economics and Policy 1, 95–106.Google Scholar
Mishra, PK, Tripathi, A, Tripathi, H and Moses, SC (2017) Energy inputs in production of lentil crop under different types of farming systems. International Journal of Current Microbiology and Applied Sciences 6, 971–977.CrossRefGoogle Scholar
Mobtaker, HG, Taki, M, Salehi, M and Shahamat, EZ (2013) Application of nonparametric method to improve energy productivity and CO2 emission for barley production in Iran. Agricultural Engineering International: CIGR Journal 15, 84–93.Google Scholar
Mohammadi, A, Rafiee, S, Jafari, A, Keyhani, A, Mousavi-Avval, SH and Nonhebel, S (2014) Energy use efficiency and greenhouse gas emissions of farming systems in north Iran. Renewable and Sustainable Energy Reviews 30(Suppl C), 724–733.CrossRefGoogle Scholar
Mousavi-Avval, SH, Rafiee, S, Jafari, A and Mohammadi, A (2011) Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach. Energy 36, 2765–2772.CrossRefGoogle Scholar
Nabavi-Pelesaraei, A, Hosseinzadeh-Bandbafha, H, Qasemi-Kordkheili, P, Kouchaki-Penchah, H and Riahi-Dorcheh, F (2016) Applying optimization techniques to improve of energy efficiency and GHG (greenhouse gas) emissions of wheat production. Energy 103, 672–678.CrossRefGoogle Scholar
Nabavi-Pelesaraei, A, Rafiee, S, Mohtasebi, SS, Hosseinzadeh-Bandbafha, H and Chau, K-W (2017) Energy consumption enhancement and environmental life cycle assessment in paddy production using optimization techniques. Journal of Cleaner Production 162(Suppl C), 571–586.CrossRefGoogle Scholar
Nabavi-Pelesaraei, A, Rafiee, S, Mohtasebi, SS, Hosseinzadeh-Bandbafha, H and Chau, K-W (2019) Comprehensive model of energy, environmental impacts and economic in rice milling factories by coupling adaptive neuro-fuzzy inference system and life cycle assessment. Journal of Cleaner Production 217, 742–756.CrossRefGoogle Scholar
Nassiri, SM and Singh, S (2009) Study on energy use efficiency for paddy crop using data envelopment analysis (DEA) technique. Applied Energy 86, 1320–1325.CrossRefGoogle Scholar
Nguyen, HV, Nguyen, CD, Tran, TV, Hau, HD, Nguyen, NT and Gummert, M (2016) Energy efficiency, greenhouse gas emissions, and cost of rice straw collection in the Mekong river delta of Vietnam. Field Crops Research 198, 16–22.CrossRefGoogle Scholar
Ozkan, B, Akcaoz, H and Karadeniz, F (2004) Energy requirement and economic analysis of citrus production in Turkey. Energy Conversion and Management 45, 1821–1830.CrossRefGoogle Scholar
Qasemi-Kordkheili, P and Nabavi-Pelesarae, A (2014) Optimization of energy required and potential of greenhouse gas emissions reductions for nectarine production using data envelopment analysis approach. International Journal of Energy, Environment and Economics 5, 207–218.Google Scholar
Rao, DLN, Giller, KE, Yeo, AR and Flowers, TJ (2002) The effects of salinity and sodicity upon nodulation and nitrogen fixation in chickpea (Cicer arietinum L.). Annals of Botany 89, 563–570.CrossRefGoogle Scholar
Rathke, G and Diepenbrock, W (2006) Energy balance of winter oilseed rape (Brassica napus L.) cropping as related to nitrogen supply and preceding crop. European Journal of Agronomy 24, 35–44.CrossRefGoogle Scholar
Shamshirband, S, Khoshnevisan, B, Yousefi, M, Bolandnazar, E, Anuar, NB, Abdul Wahab, AW and Khan, SUR (2015) A multi-objective evolutionary algorithm for energy management of agricultural systems—a case study in Iran. Renewable and Sustainable Energy Reviews 44, 457–465.CrossRefGoogle Scholar
Solís-Guzmán, J, Marrero, M and Ramírez-de-Arellano, A (2013) Methodology for determining the ecological footprint of the construction of residential buildings in Andalusia (Spain). Ecological Indicators 25, 239–249.CrossRefGoogle Scholar
Taghavifar, H and Mardani, A (2015) Energy consumption analysis of wheat production in West Azarbayjan utilizing life cycle assessment (LCA). Renewable Energy 74(Suppl C), 208–213.CrossRefGoogle Scholar
Tusher, TR, Pondit, T, Hasan, M, Latif, MB and Binyamin, M (2020) Impacts of resource consumption and waste generation on environment and subsequent effects on human health: a study based on ecological footprint analysis. In Singh, R, Srinagesh, B and Anand, S (eds), Urban Health Risk and Resilience in Asian Cities. Advances in Geographical and Environmental Sciences. Singapore: Springer, pp. 179–203.Google Scholar
Uzunoz, M, Akcay, Y and Esengun, K (2008) Energy input-output analysis of sunflower seed (Helianthus annuus L.) oil in Turkey. Energy Sources, Part B: Economics, Planning, and Policy 3, 215–223.CrossRefGoogle Scholar
Yang, Y, Yuan, G, Zhuang, Q and Tian, G (2019) Multi objective low-carbon disassembly line balancing for agricultural machinery using MDFOA and Fuzzy AHP. Journal of Cleaner Production 233, 1465–1474.CrossRefGoogle Scholar
Yousefi, M and Damghani, AM (2012) Evaluation of energy flow and indicators of chickpea under rainfed condition in Iran. International Journal of Farming and Allied Sciences 1, 57–61.Google Scholar
Zangeneh, M, Omid, M and Akram, A (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.CrossRefGoogle Scholar