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Mardani Najafabadi, M., Abdeshahi, A., Ahani, E. (2023). Determining the Eco-Efficiency of Major Crops in Selected Rigions of Khuzestan Province. , 37(3), 271-287. doi: 10.22067/jead.2023.78856.1158
M. Mardani Najafabadi; A. Abdeshahi; E. Ahani. "Determining the Eco-Efficiency of Major Crops in Selected Rigions of Khuzestan Province". , 37, 3, 2023, 271-287. doi: 10.22067/jead.2023.78856.1158
Mardani Najafabadi, M., Abdeshahi, A., Ahani, E. (2023). 'Determining the Eco-Efficiency of Major Crops in Selected Rigions of Khuzestan Province', , 37(3), pp. 271-287. doi: 10.22067/jead.2023.78856.1158
Mardani Najafabadi, M., Abdeshahi, A., Ahani, E. Determining the Eco-Efficiency of Major Crops in Selected Rigions of Khuzestan Province. , 2023; 37(3): 271-287. doi: 10.22067/jead.2023.78856.1158

Determining the Eco-Efficiency of Major Crops in Selected Rigions of Khuzestan Province

مجله اقتصاد و توسعه کشاورزی
Article 3, Volume 37, Issue 3 - Serial Number 60, October 2023, Pages 271-287    PDF (773.94 K)
Document Type: Research Article
DOI: 10.22067/jead.2023.78856.1158
Authors
M. Mardani Najafabadi* 1; A. Abdeshahi1; E. Ahani2
1Department of Agricultural Economics, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran
2Department of Accounting and Economics, Bozorgmehr Qaenat and Torbat Heydarieh University,, Iran
Abstract
Introduction
The relationship between economic development and the environment is known as one of the most important issues facing societies. If in the context of sustainable development, economic and environmental activities are considered together, the environment and economic development are two complementary factors and, as a result, it will lead to ecological balance. In this case, economic activities will not disturb this balance. Presently, the imperative of safeguarding the environment and attaining sustainable development has ascended to a prominent position on the agendas of diverse societies, Iran included. This commitment is underscored by the execution of comprehensive economic, social, and cultural initiatives aimed at fostering long-term ecological resilience and balanced societal progress. Therefore, to preserve the environment and meet the goals of sustainable development, as well as to guide and rationally manage plans and projects, especially in the agricultural sector, serious measures should be taken. Therefore, this study was carried out to evaluate the operational, environmental, and eco-efficiency of the major agricultural products of the irrigation and drainage networks of Gotvand.
The irrigation and drainage network of Gotvand is located in the southwest of Iran in Khuzestan province. This network is designed to irrigate lands located in three regions of Gotvand, Aghili, and Dimcheh, enclosed between two rivers, Karun and Lor. According to the official statistics of government organizations, the consumption of fertilizers and chemical poisons in the lands covered by this network is 3.6 times the average limit in Iran. The excess irrigation water in this network is returned to the rivers by the built-in drains and causes water pollution downstream of the network. Therefore, considering that environmental protection is one of the most important aspects of sustainable development, it is very important to investigate the effects of the use of pesticides and chemical fertilizers in agriculture and to introduce solutions to improve the efficiency of the environment in the study area.
 
Materials and Methods
Eco-efficiency includes operational and environmental impacts, which are presented as the ratio of the weighted sum of outputs to the weighted sum of inputs (operational inputs + environmental inputs). However, since agricultural activities are carried out in uncertain environmental conditions, there is uncertainty regarding inputs and outputs. The uncertainty in some of the effective input and output parameters in the ranking of networks, and as a result, the inaccuracy of the model calculation results, and the need to pay attention to the use of uncertainty models, make it more obvious. Therefore, in the present study, to include the conditions of uncertainty and risk, the robust data envelopment analysis (RDEA) model was used, which is one of the most powerful and useful models in conditions of uncertainty. The required data were collected by completing a questionnaire of the Gotvand, Aghili, and Dimche regions using a simple random sampling method in 2019.
 
Results and Discussion
The alfalfa producers in the Gotvand region assigned the highest environmental and Eco-efficiency by obtaining points in the range of 81 to 89 percent and 90 to 96 percent, respectively. The rice crop in the Aghili region had the highest types of operational efficiency based on different levels of deviation probability in the range of 77-87%, environmental efficiency in the range of 80-90%, and environmental-economic efficiency in the range of 87-95%. Dimanche sugarcane region has the highest average of efficiency types for different levels of deviation probability by obtaining points in the range of 78 to 90, 80 to 89, and 87 to 95 respectively for operational, environmental, and Eco-efficiency. Comparing the results of technical efficiency with environmental efficiency shows the lack of attention and skill of farmers in the correct and optimal use of production inputs. Therefore, it is necessary to hold educational and promotional classes to empower farmers to improve production methods and optimal consumption of inputs to improve farmers' income and increase their profits. Given that a substantial portion of energy consumption within the agricultural sector is attributed to fuels and diesel, optimizing energy usage and promoting the adoption of newer, less polluting energy sources emerge as crucial imperatives. Enhancing environmental efficiency in this context involves a strategic focus on reducing reliance on traditional, environmentally taxing energy forms in favor of more sustainable alternatives.
 
Conclusion
The average operating efficiency in all different probability levels for the studied products in Goutvand , Aghili, and Dimche areas, except for beans in the Gatund area, was estimated to be lower than the average environmental efficiency. This shows the lack of ability and skill of farmers to produce a certain product with the lowest amount of input, while the farmers of these areas pay great attention and care to environmental issues.
Keywords
Khuzestan; Operational efficiency; Robust data envelopment analysis; Undesirable output; Undesirable input
References
    1. Agricultural Jihad Organization, Khuzestan. (2019).
    2. Barghi, H., Hosni-nejad, A., & Shayan, M. (2016). Evaluation of the effects of agricultural chemicals on the environment of villages (case study: villages of Zarin-Dasht city), Natural Hazards Management, 4(3), 247-262. (In Persian with English abstract).
    3. Boucekkine, R., Jacek, K., & Thomas, V. (2011). "Environmental quality versus economic performance: a dynamic game approach". Optimal Control Applications and Methods, 32(1), 29–46. https://doi.org/10.1002/oca.927
    4. Beshartadeh, , Nowrozi, A., & Faizabadi, Y. (2021). Evaluation of economic-environmental efficiency of tangerine production in Mazandaran province with the approach of rural economic development, Space Economy and Rural Development Quarterly, 4, 195-219. (In Persian with English abstract)
    5. Charles, A., & Cooper, W.W. (1962). Programming with linear fractional functionals. Naval Res. Logistics. Q, 9, 181–186. https://doi.org/10.1002/nav.3800100123.
    6. Despotis, K., Maragos, E.K., & Smirlis, Y.G. (2006). Data envelopment analysis with missing values: An interval DEA approach. European Journal of Operational Research, 140, 24–36. https://doi.org/10.1016/j.amc.2005.10.028
    7. Department of Environment Environmental Organization. (2019).
    8. Forleo, B., Palmieri, N., & Salimei E. 2018. The Eco-Efficiency of the Dairy Cheese Chain: an Italian case study, Italian Journal of Food Science, 30(2), 112-128. https://doi.org/10.14674/IJFS-1077
    9. Han, , Geng. Z., Zhu, Q., & Qu, Y. (2015). Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in the chemical industry. Energy, 83, 685-695. https://doi.org/10.1016/j.energy.2015.02.078
    10. Lertworasirikul, S., Shu-Cherng, F., Joines, J.A., & Nuttle, H.L.W. (2003). Fuzzy data envelopment analysis (DEA): A possibility approach. Fuzzy Sets and Systems, 139, 379–394. https://doi.org/10.1016/S0165-0114(02)00484-0
    11. Kazemi, , Bourkheili, S. H., Kamkar, B., Soltani, A., Gharanjic, K., & Nazari, N. M. (2016), Estimation of greenhouse gas (GHG) emission and energy use efficiency (EUE) analysis in rainfed canola production (case study: Golestan province, Iran), Energy, 116, 694-700. http://dx.doi.org/10.1016/j.energy.2016.10.010
    12. Karimi, F., Pirasteh, H., & Zahedi, K. (2012). Determining the efficiency of wheat farming according to the two factors of time and risk using coverage analysis Open data and windowed data coverage analysis, Agricultural economics and development.
    13. Mardani, , Sakhdari, H., & Sabouhi, M. (2011). Application of multi-objective programming and Controller parameters of conservatism in agricultural planning, Case study: Mashhad city. Journal of Agricultural Economics Research, 2, 161-187.
    14. Mardani Najafabadi, M., & Ziaee, S. (2015). Determining the efficiency of irrigated wheat fields in Neishabur city under conditions of uncertainty, Economics and Agricultural Development, (2) 30, 136-147. (In Persian with English abstract). https://doi.org/10.22067/JEAD2.V30I2.49099
    15. Mardani Najafabadi, M., & Abdshahi, A. (2018). Evaluating the efficiency of groves in Ahvaz city under conditions of uncertainty: the application of robust data coverage analysis and Monte Carlo simulation, Agricultural Economics and Development, 33(2): 191-204. (In Persian with English abstract)
    16. Masuda, K. (2016). Measuring eco-efficiency of wheat production in Japan: a combined application of life cycle assessment and data envelopment analysis. Journal of Cleaner Production, 17(22), 373–381. https://doi.org/10.1016/j.jclepro.2016.03.090
    17. Nikkhah, A., Khojastehpour, M., Emadi, B., Taheri-Rad, A., & Khorramdel, S. (2015). Environmental impacts of peanut production system using life cycle assessment methodology, Journal of Cleaner Production, 92, 84-90.
    18. Nabavi-Pelesaraei, A., Rafiee, S., Hosseinzadeh-Bandbafha, H., & Shamshirband, S. (2016). Modeling energy consumption and greenhouse gas emissions for kiwifruit production using artificial neural networks, Journal of Cleaner Production, 133, 924-931. https://doi.org/10.1016/j.jclepro.2016.05.188
    19. Ohadi, N., Ahani, E., & Moradi, E. (2020). Determination of technical efficiency in dairy farms of Sirjan city using fuzzy data envelopment analysis method, Journal of Agricultural Economics Research, Volume 12, Number 47, pp. 252-237. (In Persian).
    20. Ozalp, A., Yilmaz, S., Ertekin, C., & Yilmaz, I. (2018). Energy Analysis and Emissions of Greenhouse Gases of Pomegranate Production in Antalya Province of Turkey, ErwerbsObstbau, 1-9 https://doi.org/10.1007/s10341-018-0380-z
    21. Reports of Khuzestan Province Program Organization, (2016).
    22. Rasakhis. S., Shahrazi, M., Shidaei, Z., Jafari, M., & Dehghan, Z. (2015). The relationship between economic efficiency and environmental efficiency: new evidence for developing and developed countries, Economic Research and Policy Quarterly, No. 78, Year 24, 31-56. (In Persian with English abstract)
    23. Sabouhi, M., & Mardani, M. (2010). Investigating the effect of rainfall on cropping pattern and total gross margin in the right irrigation network of nekouabad diversion dam. Journal of Agricultural Economics Research, 5, 202-221.
    24. Sabouhi, M., & Mardani, M. (2013). Application of robust optimization approach for agricultural water resource management under Uncertainty. Journal of Irrigation and Drainage Engineering, 139, 571-581. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000578
    25. Shokouhi, A.H., Hatami-Marbini, A., Tavana, M., & Saati, S. (2010). A robust optimization approach for imprecise data envelopment analysis. Computers and Industrial Engineering, 59, 387-397. https://doi.org/10.1016/j.cie.2010.05.011
    26. Taate, H., Khosravi, B., Berghae Khatebe, N. (2013). Investigating the effects of technology and its consequences on the environment, the third environmental planning and management conference.
    27. Ullah, A., Perreta, R.S., Gheewala, SH., & Sonia, P. (2015). Eco-efficiency of cotton-cropping systems in Pakistan: an integrated approach of life cycle assessment and data envelopment analysis.
    28. Mardani, M., & Taki, M. (2020). Robust data envelopment analysis with Monte Carlo simulation model for optimization the energy consumption in agriculture. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 1-15. https://doi.org/10.1080/15567036.2020.1777221
    29. Mardani Najafabadi, M., Mirzaei, A., Abdeshahi, A., & Azarm, H. (2020). Determining the efficiency of broiler chicken units in Sistan region, using interval data envelopment analysis and Mont Carlo simulation approach. Iranian Journal of Agricultural Economics and Development Research, 51(2), 179-194. https://doi.org/10.22059/IJAEDR.2019.273150.668695
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