Document Type : Research Article
Authors
1 Department of Biosystems Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz
2 Shahid Chamran University of Ahvaz
3 Department of Biosystems Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz,
4 Assistant professor, Biosystems engineering Dept., Faculty of Agriculture, Shahid Chamran University of Ahvaz
Abstract
Introduction The development of mechanization and machine technology has positive and negative consequences on the economic, social, and environmental conditions of each region. Conflicts in these dimensions complicate the selection and allocation of sustainable mechanization systems. Therefore, one of the basic questions in the selection of sustainable agricultural mechanization is how and with what methodology it is possible to propose the closest mechanization model to sustainability goals and to overcome the simultaneous contradictions of the three pillars of sustainability, considering the natural and technical limitations in agricultural production. What is the appropriate approach to consider its economic, environmental, and social dimensions? The current research aims to provide a framework in which the optimal mechanization model can be achieved in order to achieve the goals of agricultural sustainability so that it can be implemented and applied in a practical way, and it is possible to provide a model that addresses all the conflicting economic, social and environmental aspects. Quantitatively optimize the leveling of mechanization systems.
Materials and Methods In this study, a framework is applied whereby contradictory goals of agricultural sustainability can be achieved. After selecting the indices and data collection, by combining Shannon entropy and TOPSIS, the similarity index was obtained for dimensions with two or more indices. The similarity indices and the values of the Benefit-Cost Ratio calculated for each system were considered as coefficients of three objective functions (economic, social and environmental) in multi-objective optimization. A multi-objective optimization model was applied to achieve sustainable agricultural mechanization patterns and solved using the NSGA-II algorithm. In order to validate the framework, mechanization systems in paddy production in the Ramhormoz region located in southwestern Iran were analyzed with constraints namely land, water, and machine. The five mechanization systems of paddy production included Puddled Transplanted, Un-puddled Transplanted, Water Seeded, Dry Seeded, and No-Till.
Results and Discussion
Pareto-optimal solutions of different scenarios with water and machine constraints showed that by using the framework, not only can sustainable goals be met to identify the optimal allocation of mechanization systems, but also the possibility of examining the effect of different scenarios under different constraints. The contradictions of the sustainability goals in the system of no-tillage and planting with paddling are highly visible. The no-tillage system with the highest score in the environmental dimension has the lowest score in the social and economic dimension. This modern system, developed in Ramhormoz for three years, has faced technical, economic, and social challenges. The cultivated area of this system in 2019 was 43 hectares. This system, despite the speed and ease of planting and its direct environmental benefits, due to the presence of wheat residues from previous cultivation and the warm and humid environment of cultivation, the possibility of mushroom development has increased, and due to periodic irrigation, weed outbreaks have greatly affected the satisfaction and profitability of this system. This point has also weakened the environmental indicators so that the highest consumption of poisons has been recorded in this system. The results of multi-objective optimization of sustainable rice mechanization systems in Ramhormoz city showed that the total surface area of optimal point systems is in the range of 2700 to 3200, which is close to the area under rice cultivation in Ramhormoz, which is 3310 hectares, and it indicates that the output of the model according to the restrictions applied is close to reality. The limitation of machines and water has made the two planting systems without paddling and dry farming have higher levels than other systems. Now, if the machine restriction is removed, despite the water restriction, the area under rice cultivation can be increased by about 700 hectares. This means that the requirement for the development of sustainable rice cultivation in Ramhormoz is to strengthen and support modern mechanized systems of no-tillage, drying, and planting with paddling, and they need to focus on systems with less water consumption, which are systems with a higher level of mechanization and the use of mechanized methods. If there is no water limitation and the model is subject to the current machine limitations, the optimal mechanization points with more levels rely on non-peddling plating and transplanting systems.
Conclusions One of the most fundamental challenges in the development of mechanization is to identify the systems that establish the best balance between economic, social, and environmental dimensions and bring the most minor ecological damage while achieving the most economic and social benefits. Using the framework of sustainable mechanization can not only provide sustainable goals in identifying the best leveling of mechanization systems but also allows the researchers and implementers of the agricultural sector to examine the effect of different scenarios under different constraints. This framework can be used to find the optimal model of mechanization of all stages of tillage, planting, harvesting, and post-harvest in different geographical areas.
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