https://doi.org/10.4081/jae.2025.1721
Investigating the impact of integrating land consolidation with agricultural mechanization on the technical, energy, and environmental dimensions of paddy production
Published: 11 February 2025
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This research investigates how the integration of land consolidation and agricultural mechanization can enhance the technical efficiency, energy consumption, and environmental sustainability of paddy cultivation compared to conventional farming practices. Our primary objective is to assess whether consolidated and mechanized farming systems result in higher productivity and lower energy use, while also reducing environmental impacts such as greenhouse gas emissions, water consumption, and soil erosion. Conventional farming methods, characterized by fragmented land holdings, often lead to inefficiencies and environmental harm. By merging smaller plots into larger, contiguous fields, we aim to boost farming efficiency and facilitate the adoption of agricultural machinery. This study will analyze three distinct cultivation scenarios: i) conventional fragmented fields relying on manual labor, ii) integrated fields utilizing manual labor, and iii) integrated fields employing mechanization. We will evaluate key technical indicators, including crop yield, labor productivity, and crop quality, alongside energy consumption metrics like fuel and electricity usage. Furthermore, will assess the environmental implications of each scenario, focusing on greenhouse gas emissions, water usage, and soil erosion. The findings from this research will enhance our understanding of the combined effects of land consolidation and mechanization in paddy farming. Additionally, the insights gained will provide valuable guidance for policymakers and farmers, promoting sustainable practices in paddy cultivation that support food security while minimizing negative environmental impacts. This investigation aims to distinguish itself by examining the synergistic potential of land consolidation and mechanization, rather than considering them in isolation as has been done in previous studies.
Algarni, S., Tirth, V., Alqahtani, T., Alshehery, S., Kshirsagar, P., 2023. Contribution of renewable energy sources to the environmental impacts and economic benefits for sustainable development. Sustain. Energy Technol. Assess. 56:103098.
DOI: https://doi.org/10.1016/j.seta.2023.103098
Askari Sari, A., Mohammadi, M., 2015. Evaluation and comparison of arsenic metal in muscle and liver of farmed fish of silver carp, common carp, grass carp, carp and rainbow trout in Ahvaz and Shahrekord. Wetl. Ecol. 6:69-76.
Brentrup, F., Küsters, J., Kuhlmann, H., Lammel, J., 2004. Environmental impact assessment of agricultural production systems using the life cycle assessment methodology: I. Theoretical concept of a LCA method tailored to crop production. Eur. J. Agron. 20:247-264.
DOI: https://doi.org/10.1016/S1161-0301(03)00024-8
Canakci, M., Akinci, I., 2006. Energy use pattern analyses of greenhouse vegetable production. Energy 31:1243-1256.
DOI: https://doi.org/10.1016/j.energy.2005.05.021
Chamsing, A., Salokhe, V.M., Singra, G. 2006. Energy consumption analysis for selected crops in different regions of Thailand. Agric. Eng. Int. CIGR J. 8:EE06013.
Cheng, H., Zhou, X., Yang, Y., Xu, L., Ding, Y., Yan, T., Li, Q., 2024. Environmental damages, cumulative exergy demand, and economic assessment of Panus giganteus farming with the application of solar technology. Sci. Total Environ. 907:168020.
DOI: https://doi.org/10.1016/j.scitotenv.2023.168020
Devendra, C., Leng, R.A., 2011. Feed resources for animals in Asia: Issues, strategies for use, intensification and integration for increased productivity. Asian-Australasian J. Anim. Sci. 24:303-321.
DOI: https://doi.org/10.5713/ajas.2011.r.05
Dreyer, L.C., Niemann, A.L., Hauschild, M.Z., 2003. Comparison of three different LCIA methods: EDIP97, CML2001 and eco-indicator 99: Does it matter which one you choose? Int. J. Life Cycle Assess. 8:191-200.
DOI: https://doi.org/10.1007/BF02978471
Elyasi, S.N., Marami, H., He, L., Kaab, A., Pan, J., Liu, H., Khoshnevisan, B., 2022. Up and downstream technologies of anaerobic digestion from life cycle assessment perspective. In: Sinharoy, A., Lens, P.N.L. (eds.), Renewable energy technologies for energy efficient sustainable development. Applied environmental science and engineering for a sustainable future. Cham, Springer. pp. 361.389.
DOI: https://doi.org/10.1007/978-3-030-87633-3_14
Fallahpour, F., Aminghafouri, A., Ghalegolab Behbahani, A., Bannayan, M., 2012. The environmental impact assessment of wheat and barley production by using life cycle assessment (LCA) methodology. Environ. Dev. Sustain. 14:979.992.
DOI: https://doi.org/10.1007/s10668-012-9367-3
Ghasemi-Mobtaker, H., Kaab, A., Rafiee, S., 2020. Application of life cycle analysis to assess environmental sustainability of wheat cultivation in the west of Iran. Energy 193:116768.
DOI: https://doi.org/10.1016/j.energy.2019.116768
Ghasemi-Mobtaker, H., Kaab, A., Rafiee, S., Nabavi-Pelesaraei, A., 2022. A comparative of modeling techniques and life cycle assessment for prediction of output energy, economic profit, and global warming potential for wheat farms. Energy Rep. 8:4922-4934.
DOI: https://doi.org/10.1016/j.egyr.2022.03.184
Goossens, Y., Annaert, B., De Tavernier, J., Mathijs, E., Keulemans, W., Geeraerd, A., 2017. Life cycle assessment (LCA) for apple orchard production systems including low and high productive years in conventional, integrated and organic farms. Agric. Syst. 153:81-93.
DOI: https://doi.org/10.1016/j.agsy.2017.01.007
Grados, D., Schrevens, E., 2019. Multidimensional analysis of environmental impacts from potato agricultural production in the Peruvian Central Andes. Sci. Total Environ. 663:927-934.
DOI: https://doi.org/10.1016/j.scitotenv.2019.01.414
Guo, Y., Xiao, L., Jin, L., Yan, S., Niu, D., Yang, W., 2022. Effect of commercial slow-release urea product on in vitro rumen fermentation and ruminal microbial community using RUSITEC technique. J. Anim. Sci. Biotechnol. 13:56.
DOI: https://doi.org/10.1186/s40104-022-00700-8
Habibi, E., Niknejad, Y., Fallah, H., Dastan, S., Tari, D.B., 2019. Life cycle assessment of rice production systems in different paddy field size levels in north of Iran. Environ. Monit. Assess. 191:202.
DOI: https://doi.org/10.1007/s10661-019-7344-0
Hakeem, I.G., Sharma, A., Sharma, T., Sharma, A., Joshi, J.B., Shah, K., et al., 2023. Techno-economic analysis of biochemical conversion of biomass to biofuels and platform chemicals. Biofuel. Bioprod. Biorefin. 17:718–750.
DOI: https://doi.org/10.1002/bbb.2463
Hauschild, M., Barlaz, M.A., 2010. LCA in waste management: introduction to principle and method. In: Christensen, T.H. (ed.), Solid Waste Technology & Management. Chichester, J. Wiley & Sons. pp. 111-136.
DOI: https://doi.org/10.1002/9780470666883.ch10
Hokazono, S., Hayashi, K., 2012. Variability in environmental impacts during conversion from conventional to organic farming: a comparison among three rice production systems in Japan. J. Clean. Prod. 28:101-112.
DOI: https://doi.org/10.1016/j.jclepro.2011.12.005
Ibrahim, H., Ibrahim, H.Y., Ibrahim, H.I., 2012. Energy use analysis for rice production in Nasarawa State, Nigeria. Trop. Subtrop. Agroecosyst. 15:649-655.
IPCC, 2006. 2006 IPCC guidelines for national greenhouse gas inventories. 2. Inst. Glob. Environ. Strateg. Hayama, Japan.
Iriarte, A., Rieradevall, J., Gabarrell, X., 2010. Life cycle assessment of sunflower and rapeseed as energy crops under Chilean conditions. J. Clean. Prod. 18:336–345.
DOI: https://doi.org/10.1016/j.jclepro.2009.11.004
Jirapornvaree, I., Suppadit, T., Kumar, V., 2021. Assessing the economic and environmental impact of jasmine rice production: life cycle assessment and life cycle costs analysis. J. Clean. Prod. 303:127079.
DOI: https://doi.org/10.1016/j.jclepro.2021.127079
Jolliet, O., Margni, M., Charles, R., Humbert, S., Payet, J., Rebitzer, G., Rosenbaum, R., 2003. IMPACT 2002+: a new life cycle impact assessment methodology. Int. J. Life Cycle Assess. 8:324.
DOI: https://doi.org/10.1007/BF02978505
Kaab, A., Ghasemi-Mobtaker, H., Sharifi, M., 2023. A study of changes in energy consumption trend and environmental indicators in the production of agricultural crops using a life cycle assessment approach in the years 2018-2022. Iran. J. Biosyst. Eng. 54:1-18.
Kaab, A., Sharifi, M., Mobli, H., 2020. Life cycle assessment and estimation of environmental pollutants emission in sugarcane production (Saccharum officinarum L.) using artificial neural network. J. Agroecol. 12:87-106.
Kaab, A., Sharifi, M., Mobli, H., Nabavi-Pelesaraei, A., Chau, K., 2019a. Use of optimization techniques for energy use efficiency and environmental life cycle assessment modification in sugarcane production. Energy 181:1298-1320.
DOI: https://doi.org/10.1016/j.energy.2019.06.002
Kaab, A., Sharifi, M., Mobli, H., Nabavi-Pelesaraei, A., Chau, K., 2019b. Combined life cycle assessment and artificial intelligence for prediction of output energy and environmental impacts of sugarcane production. Sci. Total Environ. 664:1005-1019.
DOI: https://doi.org/10.1016/j.scitotenv.2019.02.004
Kazemi, N., Gholami Parashkoohi, M., Mohammadi, A., Mohammad Zamani, D., 2023. Environmental life cycle assessment and energy-economic analysis in different cultivation of microalgae-based optimization method. Results Eng. 19:101240.
DOI: https://doi.org/10.1016/j.rineng.2023.101240
Kazemipoor, M., Hajifaraji, M., Radzi, C. wan J.B. wan M., Shamshirband, S., Petković, D., Mat Kiah, M.L., 2015. Appraisal of adaptive neuro-fuzzy computing technique for estimating anti-obesity properties of a medicinal plant. Comput. Meth. Progr. Biomed. 118:69-76.
DOI: https://doi.org/10.1016/j.cmpb.2014.10.006
Keramati, A., Pajoum Shariati, F., Tavakoli, O., Akbari, Z., Rezaei, M., 2021. The effect of audible sound frequency on the growth and beta-carotene production of Dunaliella salina. South African J. Bot. 141:373–382.
DOI: https://doi.org/10.1016/j.sajb.2021.05.026
Khan, S., Khan, M.A, Latif, N., 2010. Energy requirements and economic analysis of wheat, rice and barley production in Australia Introduction of Rain Water Harvesting in a remote area of Dera Ismail Khan District of Pakistan. Soil Env. 29:61-68.
Khan, S., Khan, M.A., Hanjra, M.A., Mu, J., 2009. Pathways to reduce the environmental footprints of water and energy inputs in food production. Food Policy 34:141-149.
DOI: https://doi.org/10.1016/j.foodpol.2008.11.002
Khanali, M., Mobli, H., Hosseinzadeh-Bandbafha, H., 2017. Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks. Environ. Sci. Pollut. Res. 24:26324-26340.
DOI: https://doi.org/10.1007/s11356-017-0234-5
Khosruzzaman S, Asgar, M.A., Karim N, Akbar S, 2010. Energy intensity and productivity in relation to agriculture-Bangladesh perspective. J. Agric. Technol. 6:615-630.
Koga, N., Tajima, R., 2011. Assessing energy efficiencies and greenhouse gas emissions under bioethanol-oriented paddy rice production in northern Japan. J. Environ. Manage. 92:967-973.
DOI: https://doi.org/10.1016/j.jenvman.2010.11.008
Kosemani, B.S., Bamgboye, A.I., 2020. Energy input-output analysis of rice production in Nigeria. Energy 207:118258.
DOI: https://doi.org/10.1016/j.energy.2020.118258
Kouchaki-Penchah, H., Nabavi-Pelesaraei, A., O’Dwyer, J., Sharifi, M., 2017. Environmental management of tea production using joint of life cycle assessment and data envelopment analysis approaches. Environ. Prog. Sustain. Energ. 36:1116-1122.
DOI: https://doi.org/10.1002/ep.12550
Mardani, M., Sabouni, M., Azadi, H., Taki, M., 2022. Rice production energy efficiency evaluation in north of Iran; application of robust data envelopment analysis. Clean. Eng. Technol. 6:100356.
DOI: https://doi.org/10.1016/j.clet.2021.100356
Marohn, C., Schreinemachers, P., Quang, D.V., Berger, T., Siripalangkanont, P., Nguyen, T.T., Cadisch, G., 2013. A software coupling approach to assess low-cost soil conservation strategies for highland agriculture in Vietnam. Environ. Model. Softw. 45:116-128.
DOI: https://doi.org/10.1016/j.envsoft.2012.03.020
Ministry of Agriculture Jihad, 2001. [Annual Agricultural Statistics].[in Persian]. Available from: www.maj.ir
Mohammadi, A., Rafiee, S., Jafari, A., Keyhani, A., Dalgaard, T., Knudsen, M.T., Nguyen, T.L.T., Borek, R., Hermansen, J.E., 2015. Joint Life cycle assessment and data envelopment analysis for the benchmarking of environmental impacts in rice paddy production. J. Clean. Prod. 106:521-532.
DOI: https://doi.org/10.1016/j.jclepro.2014.05.008
Mohammadi Kashka, F., Tahmasebi Sarvestani, Z., Pirdashti, H., Motevali, A., Nadi, M., Valipour, M., 2023. Sustainable systems engineering using life cycle assessment: application of artificial intelligence for predicting agro-environmental footprint. Sustainability (Basel) 15:6326.
DOI: https://doi.org/10.3390/su15076326
Mohseni, P., Borghei, A.M., Khanali, M., 2018. Coupled life cycle assessment and data envelopment analysis for mitigation of environmental impacts and enhancement of energy efficiency in grape production. J. Clean. Prod. 197:937–947.
DOI: https://doi.org/10.1016/j.jclepro.2018.06.243
Molaee Jafrodi, H., Gholami Parashkoohi, M., Afshari, H., Mohammad Zamani, D., 2022. Comparative life cycle cost-energy and cumulative exergy demand of paddy production under different cultivation scenarios: A case study. Ecol. Indic. 144:109507.
DOI: https://doi.org/10.1016/j.ecolind.2022.109507
Mostashari-Rad, F., Ghasemi-Mobtaker, H., Taki, M., Ghahderijani, M., Kaab, A., Chau, K. wing, Nabavi-Pelesaraei, A., 2021. Exergoenvironmental damages assessment of horticultural crops using ReCiPe2016 and cumulative exergy demand frameworks. J. Clean. Prod. 278:123788.
DOI: https://doi.org/10.1016/j.jclepro.2020.123788
Nabavi-Pelesaraei, A., Rafiee, S., Mohtasebi, S.S., Hosseinzadeh-Bandbafha, H., Chau, K.-W., 2018. Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production. Sci. Total Environ. 631-632:1279-1294.
DOI: https://doi.org/10.1016/j.scitotenv.2018.03.088
Nikkhah, A., Emadi, B., Firouzi, S., 2015. Greenhouse gas emissions footprint of agricultural production in Guilan province of Iran. Sustain. Energy Technol. Assess.12:10-14.
DOI: https://doi.org/10.1016/j.seta.2015.08.002
Nunes, F.A., Seferin, M., Maciel, V.G., Ayub, M.A.Z., 2017. Life Cycle Assessment comparison between brow parboiled rice produced under organic and minimal tillage cultivation systems. J. Clean. Prod. 161:95-104.
DOI: https://doi.org/10.1016/j.jclepro.2017.05.098
Reyes, J.F., Sepulveda, M.A., 2006. PM-10 emissions and power of a diesel engine fueled with crude and refined biodiesel from salmon oil. Fuel 85:1714-1719.
DOI: https://doi.org/10.1016/j.fuel.2006.02.001
Saber, Z., Esmaeili, M., Pirdashti, H., Motevali, A., Nabavi-Pelesaraei, A., 2020. Exergoenvironmental-Life cycle cost analysis for conventional, low external input and organic systems of rice paddy production. J. Clean. Prod. 263:121529.
DOI: https://doi.org/10.1016/j.jclepro.2020.121529
Saber, Z., van Zelm, R., Pirdashti, H., Schipper, A.M., Esmaeili, M., Motevali, A., Nabavi-Pelesaraei, A., Huijbregts, M.A.J., 2021. Understanding farm-level differences in environmental impact and eco-efficiency: The case of rice production in Iran. Sustain. Prod. Consum. 27:1021-1029.
DOI: https://doi.org/10.1016/j.spc.2021.02.033
Šarauskis, E., Romaneckas, K., Kumhála, F., Kriaučiūnienė, Z., 2018. Energy use and carbon emission of conventional and organic sugar beet farming. J. Clean. Prod. 201:428-438.
DOI: https://doi.org/10.1016/j.jclepro.2018.08.077
Soam, S., Borjesson, P., Sharma, P.K., Gupta, R.P., Tuli, D.K., Kumar, R., 2017. Life cycle assessment of rice straw utilization practices in India. Bioresour. Technol. 228:89-98.
DOI: https://doi.org/10.1016/j.biortech.2016.12.082
Taherzadeh-Shalmaei, N., Rafiee, M., Kaab, A., Khanali, M., Vaziri Rad, M.A., Kasaeian, A., 2023. Energy audit and management of environmental GHG emissions based on multi-objective genetic algorithm and data envelopment analysis: An agriculture case. Energy Rep. 10:1507-1520.
DOI: https://doi.org/10.1016/j.egyr.2023.08.020
Taherzadeh-Shalmaei, N., Sharifi, M., Ghasemi-Mobtaker, H., Kaab, A., 2021. Evaluating the energy use, economic and environmental sustainability for smoked fish production from life cycle assessment point of view (case study: Guilan Province, Iran). Environ. Sci. Pollut. Res. 28:53833-53846.
DOI: https://doi.org/10.1007/s11356-021-14437-w
Taki, M., Abdi, R., Akbarpour, M., Ghasemi-Mobtaker, H., 2013. Energy inputs - Yield relationship and sensitivity analysis for tomato greenhouse production in Iran. Agric. Eng. Int. CIGR J. 15:59-67.
Taki, M., Yildizhan, H., 2018. Evaluation the sustainable energy applications for fruit and vegetable productions processes; case study: Greenhouse cucumber production. J. Clean. Prod. 199:164-172.
DOI: https://doi.org/10.1016/j.jclepro.2018.07.136
Van Loon, J., Woltering, L., Krupnik, T.J., Baudron, F., Boa, M., Govaerts, B., 2020. Scaling agricultural mechanization services in smallholder farming systems: Case studies from sub-Saharan Africa, South Asia, and Latin America. Agric. Syst. 180:102792.
DOI: https://doi.org/10.1016/j.agsy.2020.102792
Vural Gursel, I., Moretti, C., Hamelin, L., Jakobsen, L.G., Steingrimsdottir, M.M., Junginger, M., Høibye, L., Shen, L., 2021. Comparative cradle-to-grave life cycle assessment of bio-based and petrochemical PET bottles. Sci. Total Environ. 793:148642.
DOI: https://doi.org/10.1016/j.scitotenv.2021.148642
Yadav, G.S., Babu, S., Das, A., Mohapatra, K.P., Singh, R., Avasthe, R.K., Roy, S., 2020. No-till and mulching enhance energy use efficiency and reduce carbon footprint of a direct-seeded upland rice production system. J. Clean. Prod. 271:122700.
DOI: https://doi.org/10.1016/j.jclepro.2020.122700
Yang, J., Li, X., Hu, H., Zhang, X., Yu, Y., Chen, Y., 2011. Growth and lipid accumulation properties of a freshwater microalga, Chlorella ellipsoidea YJ1, in domestic secondary effluents. Appl. Energy 88:3295-3299.
DOI: https://doi.org/10.1016/j.apenergy.2010.11.029
Zeng, Y., Ji, X.J., Lian, M., Ren, L.J., Jin, L.J., Ouyang, P.K., Huang, H., 2011. Development of a temperature shift strategy for efficient docosahexaenoic acid production by a marine fungoid protist, Schizochytrium sp. HX-308. Appl. Biochem. Biotechnol. 164:249-255.
DOI: https://doi.org/10.1007/s12010-010-9131-9
How to Cite
Maklavani, F. H. (2025) “Investigating the impact of integrating land consolidation with agricultural mechanization on the technical, energy, and environmental dimensions of paddy production”, Journal of Agricultural Engineering, 56(1). doi: 10.4081/jae.2025.1721.
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