Document Type : Research Article
Authors
1 Department of Agricultural Economics, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran
2 Agricultural Economics, Sari Agricultural Sciences and Natural Resources University, Sari.
3 Sari Agricultural Sciences and Natural resources University-
Abstract
In recent decades, the issue of climate change has become one of the global issues and has affected the agricultural sector. The continuation of agriculture regardless of the water shortage crisis has had an inappropriate effect on the sustainability and growth of this sector. On the other hand, the destructive effect of excessive use of chemical fertilizers and pesticides on water, soil, health of ecosystems, humans and other living beings is undeniable. For this reason, the void of using an efficient model that can provide all economic and environmental aspects at the same time was completely felt. The aim of this study was to provide an optimal cropping pattern using the integrated method of Goal and Grey planning. For this purpose, the farmers of the agronomy sub-sector of Tajan Basin were selected as the statistical population. In this regard, time series information was collected from the aggregation of the average data of 401 settlements located in this area during the years 2017-2021 from the annual reports of experts.
Materials and Methods
The Linear Programming Model quantifies an optimal way of integrating constraints to satisfy the objective function to optimize crop production and profits for irrigation farmers. To use linear programming, you must convert your problem into a mathematical model. To do this, you need an objective such as maximizing profit or minimizing losses. The model must also include decision variables that affect those objectives, and constraints that limit what you can do. So, the Linear Programming Model is a single-objective method. Goal Programming is an extension of Linear Programming in which targets are specified for a set of constraints. Goal programming is used to perform three types of analysis: Determine the required resources to achieve a desired set of objectives. Determine the degree of attainment of the goals with the available resources. Providing the best satisfying solution under a varying amount of resources and priorities of the goals. So, the Goal Programming Model is a multi-objective method. The Grey system theory is identified as an effective methodology that can be used to solve uncertain problems with partially known information. Grey modelling approach is using accident data for estimating the model parameters. The model can reflect the dynamics, balance conflicts of the multidimensional targets of cropping patterns, and promote the sustainable use of cultivated land. For achieving different goals in unstable economic and environmental conditions, we used Goal-Grey that was obtained from the integration of Goal planning and Grey planning. The Goal-Grey model, by considering the uncertainty in the data, leads to overlap between the economic and environmental goals and provides the scope of cultivation for the selected products.
Results and Discussion
By estimating the Linear Model, crops like wheat and canola are deleted from the cropping pattern and the cultivation area of barley and high-yielding long grain rice are increased by 644 and 31%, respectively. Also, in this pattern, the cultivation area of high-quality long grain rice and maize are reduced by 89 and 10%, respectively. The implementation of this model will increase the gross profit of the farmers of Tajan region by 14% without changing in the current amount of inputs and only through changing the crop composition. Also, the findings indicated that by implementing the Linear Model, 5, 13 and 10 percent savings are made in the consumption of phosphate, nitrogen and potash fertilizers, respectively. The amount of herbicide and fungicide consumption in the Linear Model is exactly equal to the current model of the region. However, the implementation of this model will lead to a 5% increase in the consumption of insecticides poison. The amount of irrigation water consumption in the Linear Model was calculated to be 2% less than the current model of the region. In addition, the results indicate that by estimating the Goal-Grey Model, only canola is removed from the cropping pattern. Also, in order to achieve the defined goals in this study, the cultivation area of wheat and maize should be equal to 208 and 7356 hectares respectively. However, because of the amount of inputs are variable, the domain of cultivation of other crops can be flexible; So that high-quality long grain rice can be cultivated between 970 to 18157 hectares. Also, the cultivation area of long-grain rice can vary from 7654 to 9995 hectares. In this model, barley can be removed from the crop composition like the linear pattern or cultivated on a maximum of 2553 hectares. The implementation of the Goal-Grey model will lead to a maximum 2% increase in the gross profit of the farmers of Tajan region compared to the current model of this region. Also, by implementing the Goal-Grey Model, on average, phosphate, nitrogen, and potash fertilizer consumption is saved by 16, 27, and 20 percent, respectively. In addition, with the implementation of the Goal-Grey Model, the consumption of agricultural pesticides will decrease from 733 to 355 thousand liters on average.
Conclusion
The Linear Model is prepared based on the current conditions of the region, and due to it is single-objective and also considers fixed parameters, it cannot provide a suitable program for farmers in drought or wet periods or in the conditions of lack of inputs. The findings indicated that in the current conditions of the region, there is excessive consumption of chemical inputs and irrigation water. The Goal-Gray model, by considering the uncertainty in the data, leads to overlap between the economic and environmental goals and provides the domain of cultivation area for the selected crops.
Acknowledgement
We are grateful to the experts of agronomy management and plant conservation management of Mazandaran Province Agricultural Jihad Organization and Sari City Agricultural Jihad Management who cooperated in data collection. This article is taken from the preliminary results of a doctoral dissertation with material and intellectual rights related to Sari University of Agricultural Sciences and Natural Resources; by this way, that university is appreciated.
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