جستجوی مقالات مرتبط با کلیدواژه "optimal cropping pattern" در نشریات گروه "کشاورزی"

Agricultural producers are facing various risks. A group of these risks are production risks that affect the production or performance of the producer; Among these risks, we can mention weather changes, diseases, pests, etc. The second group of risks, so-called price risks, affects the price received by the producer or the price paid for his input, and as a result, causes fluctuations in prices. The third group of risks is called policy-making or institutional risks. Producers always face this group of risks; The fourth group of risks, which are called market risks, are caused by the market conditions of agricultural products and the lack of market infrastructure. The fifth group of risks that the government must take necessary measures to face are health risks. Here, we do not mean the consumer's health, but the producer's health. Because the producer, as a human being, performs a part of the production process, which in many cases has no replacement; Pricing policies and tools include tools whose policy variable is to support the price received by the producer for the product or the price paid for the inputs used in production. This article seeks to the effect of price policies on the optimal cropping pattern (Case study: Kobudarahang Plains).

In this research, to investigate the impact of price policies, the approach of positive mathematical planning is used, in which many limitations and disadvantages of normative mathematical planning have been removed. Therefore, considering the aforementioned advantages and its novelty compared to other agricultural policy analysis methods, and considering that the mentioned method is one of the mathematical planning methods, it has been chosen as the methodology of the present research for the analysis of the desired policies. The secondary data in this research was obtained from the Jihad Organization of Agriculture, Regional Water, Iran Statistics Center, etc., and finally 11 scenarios including price, input, and irrigation efficiency scenarios were compiled and implemented in Kabudar Ahang Plain using GAMS software.

The results of applying the scenario of removing the guaranteed price policy and pricing products with the world price and the exchange rate of 42 thousand Rials in the Kabudar Ahang Plain showed that as a result of applying this policy, the area under cropping in the region has decreased drastically, so that the area under cropping in the area has decreased from 135,439 hectares to 79,501 hectares. (41%) decreases. The largest decrease in the cultivated area is related to dry wheat with a 70% decrease. The results of applying the scenario of removing the guaranteed price policy and pricing products with the world price and the exchange rate of 136 thousand Rials in the Kabodar Ahang plain indicated that by applying this scenario, the area under cropping will decrease by 30%. The third scenario investigated regarding the guaranteed price in this study is the continuation of the policy of guaranteeing the price of agricultural products according to the approved prices of the 2019-2019 crop year in the Kabudar Ahang plain, as a result of the application of this policy, the area under cropping in the entire region will decrease by 39%, which is the largest decrease in the area under cropping It is related to the low-yield crops of rainfed barley (67 percent) and dry wheat (48 percent). On the other hand, as a result of applying this policy and according to the prices of the crop year 2019-400, the area under cropping of cucumber, potato and blue wheat has increased the most and the orders increased by 129%, 82% and 51%. Another important point regarding this policy is that water consumption will be reduced by 39%.

Cropping pattern optimization is an important strategy in the optimal use of water in agriculture. The present study attempted to develop and evaluate four hybrid models based on maximizing economic return rate and minimizing risk based on risk indices including variance (MVar model), semi-variance (MSVar model), absolute value deviation from mean (MADev model) and conditional value at risk (MCOVaR model). The MCOVaR model is governed by observing the rules, which at a selective confidence level allows determining the best cropping pattern scenario with selective return rate and the lowest risk that can be measured in the decision-making stage. The data used are related to the downstream irrigation network of Ardabil Yamchi Dam and for the 1397-98 crop year. The development of the model in MATLAB is based on nonlinear programming and optimization problem solving using particle swarm algorithm in a multi-objective solution. The highest correlation coefficient in regression of the models with Fourier equation was R2=0.9997 with accuracy (RMSE=0.0011) for MADev model, The results showed that the highest yield of 0.31 belonged to potatoes with a maximum risk of 58% and the lowest yield of 0.13 belonged to the maize plant with a maximum risk of 63%. By calculating 50 scenarios of the best possible cropping patterns in terms of satisfying the target functions and governing conditions, the pareto front of each model was drawn and the table of system income values for risk levels of 20% and 30% was extracted and presented. The results obtained in all models indicate an increase in economic efficiency by increasing the risk level of the system in selecting the optimal cropping pattern and this increase in MADev model is more steep than other models and increasing risk-taking leads to increasing the area under cultivation of plants with more water consumption.

Changing the cropping pattern due to the climate change and drought persistence is one of the key approaches for agricultural policy makers for adaptation of water scarcity. Also, implementation of changing the cropping pattern in Sarab County is felt as one of the major points of agricultural production in East Azerbaijan province. Since the uncertainty is one of the unavoidable aspects in agricultural planning and decision making, this study introduces and applies the robust goal programming (RGP) model as a tool for optimization of cropping pattern under uncertainty. The required data and information for this study were collected through Sarab County Agriculture Organization and completing the questionnaire in the period of 2017-2018. In addition to the RGP approach, the LP and GP models were solved to determine the optimal cropping pattern. The results showed RGP model in terms of achieving the goals of maximize profit and minimize water consumption was superior to other models, which indicated that the current status of the water operation in the studied area was not optimal. Implementation of optimal cropping pattern based on RGP model would increase profited and employment by 1.7 and 1.32 percent, respectively and it also could reduce water consumption, fertilizer and chemical pesticides consumptions by 7.7, 12.3 and 12 percent, respectively relative to the current cropping pattern. Among the studied crops, wheat had the highest increase regarding cultivated area. Therefore, wheat is an important crop in the region and it should be cultivated as a strategic crop in greater volume.

The increase in water demand and the expansion of water pollution due to the development of agricultural, urban and industrial activities have led to a serious risk of water quality in many places. Therefore, its rational and logical management has become very difficult and complicated. In recent decades, concerns about water pollution from agricultural activities and its consequences have been growing. The existing regulations are not sufficient to limit the water pollution of the agricultural sector and to achieve the desired environmental consequences. Thus, economic tools have increasingly been proposed as an affordable way to limit pollution. Therefore, the side effects of water consumption in agriculture are vital issues for controlling and managing water pollution. The recent challenges in water resources of the Zayandehroud basin have led to the fact that this area has not been safe from water pollution and also the supply of high quality water is a major challenge in this basin. Therefore, providing a purposeful cropping pattern by reducing the side effects of water pollution caused by agricultural activities for the Zayandehroud basin can play an effective role in the quantitative and qualitative management of watershed resources.

In this study, the water resources management system of Zayandehroud basin has been modeled based on a multi-objective programming model. This model includes hydrological functions, land allocation, resource transfer and exploitation capacities, and the objective function is to maximize the net present value of the total benefits at the basin level. Also, the amount of water available in different sub-basins, the crop yield and net water requirements was simulated using the WEAP model for the 2040 horizon. This data was used as input in the economic model. In the next step, the side effects of water pollution are estimated and internalized in the economic model using permissible limit of water pollution in constraint and the cost of water pollution in the objective function. The mechanism designed to internalize the side effects of water pollution is simulated using the SWAT model and added to the integrated water management model of the basin as environmental constraint and cost of nitrate losses in objective function. Therefore, by comparing the results of these two models, it is possible to evaluate the internalization of the side effects of water pollution on farmers' livelihoods and the cropping pattern in the basin.

Cropping pattern under basic conditions was applied in WEAP software for different regions. Yield and net water requirements of products were simulated using MABIA tools. The results were extracted by each region and then estimated at basin level. The results of the optimal cropping pattern after simulating the hydrological parameters of the basin showed that the gross margin compared to the current conditions for Najafabad, North Mahyar, Lenjanat, Kuhpayeh-Segzi, Isfahan-Borkhar and Ben-Saman regions was 14, 5, 15,18, 15 and 20 million Rials per hectare, respectively. The increase in the share of irrigation technologies in the economic model compared to the current model for Najafabad, Lenjanat, Kuhpayeh-Segzi, Isfahan-Borkhar and Ben-Saman regions was 40, 57, 35, 45 and 91 percent, respectively.Therefore, it can be expected that by changing the cropping pattern and also increasing the use of new irrigation systems, it is possible to improve the livelihood of farmers in the basin according to the current and future hydrological conditions. But these changes have increased the side effects of pollution on the basin. Therefore, it is necessary to provide a model that, in addition to improving the benefit, also reduces the cost of nitrate losses. The results of the optimal bioeconomic model indicate that with the application of this model, the rate of gross margin and the cost of nitrate losses have been obtained at 58 and 28 million Rials per hectare, respectively. Comparison of this model and the optimal economic model shows that farmers' gross margin and nitrate losses have decreased about 3 and 2 million Rials per hectare, respectively. Comparison of the current and optimal bioeconomic model also shows that while improving the gross margin by 12 million Rials, the rate of nitrate losses below the allowable level in the basin can be realized.

Zayandehroud basin is one of the most important watersheds in the country, which is facing the challenge of quantitative and qualitative water shortages. The main purpose of this study is to quantitatively and qualitatively manage water resources and evaluate the consequences of internalizing the side effects of water pollution on this type of management. The results of the study showed that using the optimal economic cropping pattern will increase the farmers' gross margin and improve their livelihoods.  Also, comparing the results of the economic model with the multi-objective bioeconomic model showed that considering the side effects of water resources pollution in some areas is effective and in others is ineffective. Therefore, it is recommended that in future studies, considering the effective role of different policies in the field of water resources quality, the effects of different scenarios of climate change, drought, population growth, etc. be examined and analyzed.

The high share of agricultural water consumption compared to other sectors and the serious crisis of dehydration in recent years reform and offer optimal crop pattern that reduces water consumption and increases the efficiency of its use, the requirements of most forbiddens and critical plains of the country. The purpose of this study was to provide optimal cropping pattern in relation to Allocable Water agriculture communicated by the Ministry of Energy and the long-term cumulative accumulation deficit of aquifers and the emphasis on agricultural sustainability indicators in the twenty-year planning horizon, Qom-Kahak study area. To simulate rainfall component behavior, outcomes of A2 scenario for the HADCM3 climatic model were used and using the continuity equation balance,the volume of water allocated to the crop sector was estimated each year. Then, using fuzzy utopian planning models, sustainable agriculture patterns were presented within the framework of technical constraints. The results showed that the implementation of the proposed agronomic models will in addition to offset the deficit of 536 million cubic meters and aquifer balance in the study area over the planning horizon, It will increase labor force and physical productivity of water, fertilizers and pesticides consumption will increase by 10.7%, 106%, 4.1% and 8.8% respectively, and water resources, fertilizers and chemicals consumption will reduce by 48.2%, 3.9%, 8 respectively.. Therefore, it is suggested to regional authorities to prioritize the implementation of proposed agro-projects, which requires the development of legal requirements, incentive and punitive policies, and conducting training and extension courses.

The aim of this study was evaluating the economic and financial profitability of different cotton cultivation systems and its effects on cropping pattern in Gorgan County during 2014-15. Required information has been collected by stratified random sampling method from 50 farmers who cultivate cotton in three systems of crop cultivation including mono cropping, double cropping (cotton-bean), and intercropping (cotton-sesame). Data between three cotton cultivation systems was analyzed by using SPSS software. After that, the optimal cropping pattern of Gorgan County was determined by using 295 farmers in Gorgan and using mathematical programming model with GAMS software. The results of profitability showed that, double cropping systems of cotton compared to mono cropping and inter cropping systems has more than 18 and 26 percent economic profitability and 20 and 22 percent financial profitability respectively.The results of determining the optimal cropping pattern of Gorgan county showed that, double cropping system due to more economic and financial profitability than other products, was included in the copping pattern of the county and other cotton cropping systems removed from the model. According to the results of this study, it is suggested that by encouraging farmers to use a double cropping system, the total cultivation area of cotton could be increased in Gorgan County.

The main objective of this study was to determine an optimal cropping pattern in a productive unit located in Pishva County based on regional and national comparative advantage analysis. In order to achieve this goal, the physical indices of the comparative advantage of production including scale advantage, efficiency advantage, and aggregative advantage with the export advantage of both agronomic and greenhouse crops were calculated. The research was an empirical study based on field survey. Data were gathered through a questionnaire, interview with experts from Varamin Agricultural unit and statistical reports from the Ministry of Jihad-Iran Agriculture and FAO. The results of the study showed that the current cropping pattern of Varamin production unit has scale, efficiency and aggregative advantage and therefore the current farming pattern should be continued. These crops also had efficiency advantage in regional level according to Pishva County cropping pattern Analysis. The analysis of the comparative advantage of greenhouse products at the regional level showed that cucumber, colored pepper and tomatoes had comparative advantage in the province of Tehran. The revealed comparative advantage also showed that cucumbers, colored peppers and greenhouse tomatoes, along with cabbage (leaves, flowers and broccoli), have an export advantage at the national level. Therefore, the optimal cropping pattern of the agricultural unit can be reached through continuing the current cropping pattern along with the addition of greenhouse products with regional advantage and cabbage crop with national and export advantage.

The agricultural sector plays an important role in the national economy, employment and food security of various communities. During recent decades, population increasing growth and the need to food security increased pressure on natural resources especially in developing countries. Therefore, it is necessary to use the resources of production in this sector in the best way possible, while reducing the consumption of these resources, the profit and welfare of farmers also will increase. Therefore in this study, the optimal cropping pattern consistent with sustainable agriculture with cross section data of year 1394-1395 and using multi objective fractional programming approach in Ardebil county determined and compared with present cropping pattern. The required data were collected from statistical yearbook of agriculture organization. The results indicated that in order to achieve some sustainability goals such as reducing the use of chemical and water inputs, it is necessary to exclude part of gross income from total agricultural production in the short term. However, taking into account the many indirect costs that non-compliance with the principles of sustainability affects society and the agricultural environment, this reduction in the gross income of farmers can be justified.

As societies grow, human survival and well-being depend heavily on the efficient management of natural resources and the pursuit of sustainable agricultural dimensions. The aim of this study was to develop an optimal model of crop production planning in Varamin Agricultural Complex as one of the leading units in the agricultural sector of this city, with simultaneous integration of economic and environmental priorities. For this purpose, the statistical information of this agricultural unit was used during the 2015-2016 in formulating a multi-criteria mathematical programming model. In this model, it's possible to explicitly address all the priorities of future production plans. Therefore, the results showed that in optimum conditions for planning the production of crops in this unit, the goals of maximum gross margin, maximum net energy generated and minimum utilization of agricultural machinery as economic ideals and the minimum use of chemical pesticides as an environmental goal will be available simultaneously. Moreover, by combining economic and environmental priorities, wheat, barley silage, herbs and forage corn are the main combinations of optimal planning pattern.

This study aimed to determine the optimal cropping pattern and the optimal amount of water usage emphasizing on sustainability of water resources and optimizing the economic and environmental factors in Fariman-Torbatjam plain. In the first section of this research, the status of sustainability of water resource were analyzed using the sustainability indices and calculation the water balance of underground water in wet, normal and dry water years. Considering that the study aimed to propose the optimal crop pattern by emphasizing on agricultural sustainability and water resource along with maximizing gross margin, the Multi Objective Programming Models like Multi Objective Fractional Programming must be employed. The defined goals of this model are maximizing sustainable indices which involve the ratio of gross margin to water resource usage, chemical fertilizers and pesticides. By implementation of the optimal cropping pattern, the usage of water, chemical fertilizers and chemical pesticides compared to the current crop pattern will decrease by 10, 5.11 and 12.52 percent respectively and gross margin will be increased by 0.6 percent. Also, sustainability index of water, chemical fertilizers and chemical pesticides compared to current cropping pattern, will be increased by 11.78, 6.02 and 15 percent. In order to achieve to the quantitative sustainability of water resources, the ratio of water usage in agricultural sector to renewable water was used. With the implementation of the proposed optimum model, the water consumption will be reduced by 10 percent yearly, then the amount of water usage in agricultural sector in sudied area will be decreaesd by 0.7 of renewable water in 8 years, and then the quantitative and qualitative of sustainability of water resources will be achieved.

At the river catchments, different strategies at the whole or different parts of the basin can be applied for water resources management. One of these strategies is optimal water allocation and crop pattern. In this study, an optimization model for water allocation and cropping pattern is presented based on the cooperative game theory. To measure the performance of the developed model, the cultivated area of Ordibehesht Canal in the Doroodzan irrigation network has been studied. First, using a fuzzy model and considering the fuzzy coefficients values in the objective function and constraints, the optimal crop pattern and allocated water has been determined for each crop. Second, benefits of stakeholder’s coalitions have been determined by developing a cooperative game model and based on the structure and properties of the irrigation water distribution network and water rights of each part. Then, the total net benefit has been reallocated to the different stakeholder in a rational and equitable way using Least Core games. The results show that by allocating more water to the sectors with more potential production, more profits are generated and water productivity increases. For example when players cooperate together and form the grand coalition, the net benefit increases from 8.906 billion Tomans to 9.724 billion Tomans that show an increase in the economic productivity of water.

Determining a suitable cropping pattern is an important task for planners and requires an exact and realistic decision-making process based on several goals and criteria corresponding to secure the interest of agricultural beneficiaries in long-term. Accordingly, this study reviews the current pattern operated by farmers in Sari, Iran, and intends to provide a cropping pattern that considers the multifold regional and agricultural sustainability criteria along with economic considerations.
In order to achieve the study goals, a consolidated model of AHP and Linear Programming was applied. For this purpose, we constructed a three-level AHP, including a goal (determining the weight of each crop), seven criteria, and seven alternatives. Profitability, compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop were considered as the criteria in the model. Seven alternative crops including rice, wheat, rapeseed, barley, soybean, clover, and vegetables were considered too. The next step is determining the weight of each criterion with regard to the goal and the weight of each alternative with regard to each criteria. By multiplying these weights, final weights for various crops were obtained from the model. Derived weights for each crop were then applied as objective function coefficients in the Linear Programming model and the model was solved subject to the constraints.
Optimal cropping pattern determined based on the consolidated model of AHP and Linear Programming and the results compared to a scenario that only looks forward to maximizing the economic interests. Due to the low profitability of rapeseed and barley, these crops eliminated from the pattern in the profit-maximizing scenario. According to the results, the scenario provides 11.36% more profit than the current cropping pattern. In the consolidated model, we first calculated final weight for any crop. With a relative weight of 0.23, rice had the highest priority. Wheat, vegetables, clover, barely, rapeseed, and soybean weighed 0.17, 0.16, 0.14, 0.11, 0.1, 0.09 and took the respective priorities. In the next step, we use the weights for each crop as objective function coefficients in the Linear Programming model and solve the model subject to the constraints. Rice cultivation had the largest crop area with 15126 ha (62.52% of the entire crop area). Clover, vegetables, wheat, rapeseed, barely, and soybean stood behind the rice. Comparing the ideal cropping pattern, which was based on multifold criteria, with the current pattern showed that the most significant changes between the patterns occurred for wheat, soybean, and rapeseed crops so the recommended crop area for wheat in the optimal pattern increased by around 165% , however, the recommended crop area for soybean and rapeseed decreased by 96% and 75% respectively. The total profit of the ideal cropping pattern was 1,152,469,874,210 Rials. This shows that the optimal pattern caused an increase in profit by 3.63% compared to the current cropping pattern. Comparison between the results of consolidated model and profit-maximizing scenario shows that the optimal cropping pattern recommended by the consolidated model offers lower profits (lower than 8%) than the pattern offered by profit-maximizing model, however, the optimal pattern allows us to take other important criteria into account, including crop compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop.
Using a consolidated model of AHP and Linear Programming, this study aimed to decide an optimal cropping pattern that considers the multifold regional and agricultural sustainability criteria beside economic considerations in Sari. The results of ideal cropping pattern in consolidated model recommended some changes distribute cropping area between crops and increased the profit compared to the current pattern. Comparison between the results of consolidated model and a scenario that only looks forward to maximizing the economic benefits shows that the ideal cropping pattern recommended by the consolidated model offers lower profits (lower than 8%) than the pattern offered by profit-maximizing scenario, however, the optimal pattern allows us to take other important criteria into account, including crop compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop, which are so vital in current agricultural situation and result in significant long-term effects. Therefore, it is recommended to have the optimal cropping pattern operated in the region or at least, in parts of the district as a pilot project.

Given the role and importance of agricultural farms management, applying the mathematical programming models has also important role in determining the optimal cropping pattern. The objectives of this study included profit (gross margin) maximizing (scenario 1), achieving self-sufficiency of essential agricultural products (scenario 2), sustainable agricultural development (scenario 3), maximizing the employment opportunities (scenario 4), and achieving these goals simultaneously (scenario 5). These objectives are important to achieve sustainable rural development in which the sustainability involves three economic, social and environmental dimensions. In this study, in order to suggest an optimal cropping pattern using simple random sampling method, a sample size of 124 was selected from agricultural areas of Amol Tcounty. Study results showed that scenario 5 made an interaction between scenarios 1 to 4. In addition, in this model, less attention was paid to economic and social goals; in contrast, the self-sufficiency and environmental goals were mostly fulfilled.

To protect from the risks of drought and water crisis in the future is needed that guidelines and rules for utilization of limited water resources be taken. In this context, mathematical programming models are used to help solve problems related to water resources management widely. In the present study in order to proper exploitation of groundwater and surface water resources and the optimal allocation of these resources in agriculture sector and also to determination an optimal cropping pattern that conducive to achieve the maximum possible profit for farmers of Roudbar Alamout region, from Fuzzy Goal Fractional Programing (FGFP)model and statistical data related to year 2010-2011 were used. The proposed model was solved in GAMS software version 23/9. The results showed that utilization optimal cropping pattern and optimal allocation of existing water resources in case study region in addition to reducing water used in farms level, the product cost in per hectare of lands reduced, the utilized labor force increased and efficiency indicators "profit ratio to water used" increased about 13 percent. In the end, according to obtained results planning and modeling from bottom to up for development agricultural sector of Qazvin province was proposed.

The purpose of this study was to determine the plant density of sugar beet fields in Qazvin region using satellite images and remote sensing techniques. The plant density can be used to estimate the pre-harvest sugar beet yield and as a result the proper management of agricultural and industrial processes involved in sugar production. Satellite data can be used to remove the cost and time of conventional field methods. In this study, using satellite imagery of TM and GeoEye, the plant density of sugar beet fields in a part of Qazvin region was estimated in 2011. Results derived from the assessment of accuracy of operations and comparison of the maps obtained from remote sensing data with ground samples showed that using satellite data, the plant density of sugar beet can be estimated with relative certainty. The calculation of the overall data showed that the accuracy of maps outputs was 91.7% with Kappai coefficient of 0.84. In addition, remote sensing data can illustrate the density variation in different parts of the field.

In this study, the optimal cropping patterns based on individual aims are presented and followed by a multi-objective cropping pattern with emphasize on the use of conservation tillage methods in Darab region presented. Individual goals consisted of maximizing gross margin and food secIn this study, the optimal cropping patterns based on individual aims were presented and followed by using a multi-objective fuzzy goal programming with emphasize on the use of conservation tillage methods in the Darab region. Individual goals consisted of maximizing gross margin and food security and minimizing water consumption and urea fertilizer use. The results showed that in the multi-objective cropping pattern, gross margin and food security increased by 23.5% and 6.1%, while water and energy consumption decreased by 4% and 5.1%, respectively as compared to the current cropping pattern. The fuzzy composite distance improved by %36, as compared to the current condition. Moreover, having replaced the conventional tillage methods with conservation tillage methods in the cropping pattern, the diesel fuel consumption reduced by 27%. Therefore, replacing multi-objective cropping pattern, on which the conservation tillage methods are emphasized, with the conventional cropping patterns improves economic and environmental conditions. urity index and minimizing water and urea fertilizer.The results showed that in the multi-objective cropping pattern, gross margin and food security index respectively increase by 23.5% and 6.1% and water and energy consumption decrease by 4% and 5.1% respectively as compared to current cropping pattern. The fuzzy composite distance improves by %36 compares to current condition and represents better cropping pattern than the others. Morever in this cropping pattern, conventional tillage method will be replaced by conservation tillage practices, therefore the amount of diesel fuel consumption reduces by 27% that is equivalent to an annual saving of 567 liters of diesel fuel. Also, the reduction of water consumption is expected to be 10000 cubic meters annually.9 In the cropping pattern, minimizing water consumption, water saving was 27.5% that was equivalent to an annual reduction of 69000 cubic meters of water, while maintaining the gross margin equal to current condition. Also urea fertilizer and energy consumption reduced by 23.7% and 28.5% respectively.

The main objective of this study was to develop an optimal cropping pattern for sugar beet growers in Fasa district (Fars province) and to investigate sugar beet importance in cropping pattern. Regarding the effect of risk on producer's decision, two risk sources including price and yield were considered. Data was obtained from Fasa district producers in 2008. In this study multi-objective mathematical programming was used. Results showed 7% difference between current income and optimal cropping pattern. However, they had difference in crop composition. In current pattern, 3.8 hectares out of 6.8 hectares belonged to sugar beet, while in optimal pattern, it reduced to 0.2 hectares. In general, in developed cropping pattern, sugar beet-wheat dominated production composition changes in favor of bean. These changes meet the goal of water use reduction up to 33% in addition to supply the current output. Results showed that farmers pay more attention to price risk in cropping pattern formulation. It was also determined that the inefficiency of sugar beet in using water as a restricting input has lowered its ranking in cropping pattern.