سیدعلی حسینی یکانی

The purpose of this study is to determine the role of location along with other influencing factors on the status of agricultural processing industries in Mazandaran. Data were collected from 230 managers of agricultural industries via completing questionnaires in 2017-2018. The cluster sampling method was done with the assignment technique. The validity of the research tool was confirmed by experts and its reliability by calculating Cronbach's alpha coefficient (0.71). The studied units are divided into three groups based on the level of utilization of potential capacity: weak, medium and complete, and two-level ordinal logit model has been used to determine the influencing factors. Stata 14 software was used. The findings showed that the contribution of the location variable in the changes in the utilization levels is 10.45%. According to the changes in the share of location, it can be concluded that the individual characteristics explain 61-87% of the changes in the utilization of the potential capacity of the unit. Life of unit, manager education, size of the unit, how to supply the raw materials and initial capital were negative effect on the level of utilization of potential capacity. The results of this research showed that focusing on the internal characteristics of units leads to the achievement of greater efficiency in the transformation and supplementary agricultural industries of Mazandaran province, hence suggestions such as holding training courses, providing facilities, supporting small conversion industries, priority Licensing clause based on type of ownership and type of activity was presented.

Agriculture, as one of the main parts of development, plays a fundamental role in the economic development of countries. To develop this sector, farmers need suitable and acceptable policies and programs. It is important to pay attention to the fact that today, not only economic goals should be considered in agriculture, but as a source of damage in different areas, it is necessary to examine the environmental issues related to this sector. Furthermore, agriculture is an activity that comes with risk. Farmers live with risk and make decisions that affect agricultural yields. Therefore, this study aimed at concurrently reducing the usage of fertilizers and chemical pesticides, while also mitigating production risks.

To attain the study objectives, the Fuzzy Goal Programming (FGP) model was utilized, with all estimations carried out in GAMS. Additionally, the Conditional Value at Risk (CVaR) model was employed to capture and assess risk within the model framework. In the context of a fuzzy environment, goal programming can be formulated as FGP, incorporating three types of fuzzy goals as described in the equation as follows:Where the sign ~ shows the fuzziness of the goal value. To establish the levels of goals within the model, initially, a distinct linear model was estimated for each of the study objectives.Top of Form The products in this study included wheat, barley, rice, corn, peas, lentils, sunflower, potato, onion, and Soybeans.

The comparison of the current situation and the results of single-objective models showed that considering the two goals of minimizing fertilizer and pesticide together would reduce the consumption of these two inputs in the final model. In the next step, the objective of risk minimization was incorporated as a significant factor in the goal-fuzzy model. The model was then simultaneously estimated based on the three goals: minimizing fertilizer, minimizing pesticides, and minimizing risk. The results of the model indicated that the consumption of fertilizer and pesticides in the final model had decreased compared to other models and the current situation. Additionally, this approach resulted in a model with lower associated risk.

Results of calculations showed that the FGP model considering three goals in comparison to the risk-free model would offer better results with nearer results to real conditions. Accordingly, this study suggested the concerned model to be used for each crop separately.

In this study, two mathematical programming patterns were solved in order to determine the diet consistent with the environment for dairy cows. In first, the optimal diet was determined with the aim of minimizing ration cost, and in the next model, the optimal ration was determined with minimizing greenhouse gas emissions with non-increasing costs. According to the results in the conditions of determining the optimal ration based on the minimizing the ration cost, sugar beet pulp, wheat bran, wheat straw and barley make the most of it. Also, materials such as corn, fish, and soybeans are removed from the diet. In order to reduce greenhouse gas emissions in different scenarios, materials such as corn silage, beet pulp and wheat bran have a higher share than other materials. Barley and Wheat straw are also products that reduce the amount of greenhouse gases in the diet. Based on the results, in order to reduce the greenhouse gas emissions by 26.6%, it is necessary to spend about 20% more than the cost of conventional models.

Today, rapid changes in climate, trade policies and technology have led to production, price and income shocks in the grain market. This study aimed at investigating the food security of different groups of society due to production, price and income shocks using the multiple market equilibrium model. Due to the importance of cereal products, especially bread, rice and pasta in the food basket of Iranian households, production, price and income shocks for this group of food and their effects on food security of the households by urban and rural income groups as well as government and freelance jobs were surveyed. The required information was extracted from the raw cost and income data of urban and rural households from 2008 to 2018 through the Statistics Center of Iran (SCI). The results showed that the food security of the society is mostly influenced by the production shocks of grain products, so that with a twenty percent decrease in the production of grain products, the poor and middle rural households, respectively, with an average percentage of calorie changes of -15.6 and -10.9 were among the most sensitive groups; on the other hand, poor households with government jobs would suffer the most from the increase in the price of cereal products, with an average percentage change of 7.9 calories. Also, increasing the income of poor households might play an effective role in improving their food security, while increasing the income of middle-income households would change the consumption pattern of these households. Therefore, it is necessary to adopt appropriate price and income support policies in order to maintain the welfare of poor households.

Given the important role of the agricultural sector in ensuring Iran's food security, it seems necessary to simultaneously focus on the quantity and quality of products. The study aimed at comparing the efficient production and standard production of energy and key nutrients in livestock and poultry sub-sectors of the country's provinces using data envelopment analysis method. The required information was collected from the Ministry of Agriculture-Jahad (MAJ), USDA database and the Statistical Center of Iran (SCI) in 2016. The results showed that the average technical efficiency of production in the provinces of the country was 90.8 percent and the average amounts of food security effectiveness in energy, protein, vitamin A, riboflavin, calcium and iron production were 93.9, 98.9, 88.2, 95.7, 59.9 and 99.8 percent, respectively. Also, the provinces were divided into three groups including efficient and effective, inefficient and effective, inefficient and ineffective. It is suggested that the production model of the provinces of the first group might be used as a model, taking into account the requirements of other provinces; in addition, in the provinces of the second group, the composition of production could be changed in such a way that the effectiveness of food security would be achieved in ineffective factors (mainly, calcium and vitamin A); finally, in the provinces of the third group, the strategies leading to improved technical efficiency should be used.

In the present study, the effect of sand extraction from the bed and bank of Khatirkuh river in Mazandaran province on social, ecological and environmental issues was investigated using a questionnaire and field visits, experts and local people. Then, by determining the sample size using the Cochran relation and evaluating the reliability and reliability of the questionnaires by Cronbach's alpha method and finally its validity was confirmed by experts and professors. Then 70 questionnaires were distributed between local communities and experts and using the SWOT matrix of external and internal factors, strategies for the effects of sand extraction in the region were identified. The results showed that the total secondary coefficient of strengths and weaknesses were 1.938 and 1.076, respectively, and the total secondary coefficient of opportunities and threats were 2.307 and 1.907, Respectively. According to the SO and WT factors for development planning in the region, offensive strategy is a priority. The above strategy maximize  opportunities and strengths and thereby reducing mining problems.The most important ecological factor of this region is the entry of invasive plants, forest and pasture fires, which have reduced growth, vegetation density and pasture destruction. The most important strength of  mining in this region is direct  and indirect employment related to sand and gravel mines.

In order to develop agricultural exports and despite the importance of the production of citrus in this sector, should be provided the necessary support from the producers in the export, in order to use the production capacity of this products in Iran. In this regard, in the present study, using a mathematical programming model, the optimal level of subsidy for export of orange has been calculated and evaluated its effect on the welfare of the domestic suppliers of orange. The information required in this study was based on 2017, which has been collected in the form of documents. The results of the research indicate that the export subsidy for orange in 2017 has not been optimal and for optimization, the subsidy increases from 5,000 Rials to 7918 Rials per kg of orange exports. By paying this subsidy, the export and supply of orange increased by 73.6% and 0.41%, respectively, and demand decreased by 0.66%. Rising supply along with rising domestic prices will lead to 0.82% increase in the welfare of the orange suppliers.

The use of multiple risk management tools at the same time is a common practice among the farming communities around the world. Therefore, this study is designed to investigate the Factor affecting of Simultaneous adoption of managing custom catastrophic risks tools such as diversification and precautionary savings in agriculture in Khorram Abad Area of Tonekabon. So bivariate probit model was used to cope the possible correlation between the risk management adoption decisions. The results highlighted that, age, education of the household head, family size, in farm income, land size and risk aversion coefficient has the significant effect on the decisions to adopt diversification and precautionary savings to manage farm risks. Risk aversion coefficient has the most effects on decisions to adopt managing catastrophic risks tools; Increasing in risk aversion coefficient, was increased the probability of simultaneously use of risks management tools by 0.22 percentage. Therefore, due to the positive impact of education and income on the use of risk management tools, increasing farmers 'awareness and increasing farmers' income through modifying their cropping pattern has been suggested.

Food security and its side effects is an issue that has directly or indirectly posed serious challenges to all countries in the world, especially developing countries such as Iran. Given the importance of nutrition and food consumption in household budget planning and the direct impact of prices on it, this article seeks to examine the effects of price shocks along with the nominal income compensation policy on household food security. To achieve this goal, four food groups are cereals (bread, rice and pasta), livestock products (red meat, white meat, dairy and eggs), and other agricultural products (potatoes, vegetables, fruits). Cereals and processed products (oil and sugar) were considered due to their high share in the household food basket.Using the multi-market equilibrium model, the effects of price shocks of this group of products along with the nominal income compensation policy on the amount of calories received by households were evaluated separately for urban and rural income groups.The results showed that the increase in income will lead the consumption pattern of poor households to consume more livestock products assuming the price of these products is stable and the consumption pattern of middle households to more consumption of agricultural products despite the increase in prices of these products. In this regard, the results showed that the sensitivity of poor households in the community, especially poor rural households to changes in income is very high. And increasing or decreasing the income of this group of households can play a decisive role in improving or weakening their food security. Therefore, it is suggested that the government men play an important role in supporting these households in the conditions of inflation in products and food, by granting subsidies and allocating the necessary funds to poor households, especially the rural poor. Due to the different influence of households with different income levels, it is necessary to establish the necessary support policies based on the income level of the household. Based on this, it is suggested to use support policies that are a combination of price and income policies for household consumption management.

The changing environment of agricultural activities face farmers to a variety of risks and uncertainties that influence the decisions of production, sustainability and profitability of these activities. Income risk as a result of both price and crop yield risks is one of the most important risks for farmers. In this study, optimal cropping pattern of crops as a tool for managing income risk was determined using diversification-consistent Data Envelopment Analysis (DEA) model based on directional-distance measures. For this purpose, the expected profit and the conditional value at risk at different probability levels were used as return and risk measures. The results showed that in the optimal cropping pattern, the share of wheat decreased and the share of more profitable crops such as medium rice grain with high-quality increased; in addition, crops such as soybeans and cotton with less profit and more risk were eliminated from the optimal cropping pattern. Based on the study results, it is suggested to use tools such as income insurance, compensating payments and a revenue stabilization fund for the development of rice cultivation in the region.

In recent years, fluctuations in the livestock products market have caused dissatisfaction among all groups in society.

The purpose of this study is to investigate the food security of different urban and rural income groups due to production, price and income shocks of livestock products in the form of a multi market equilibrium model. The required information was extracted from raw cost and income data of urban and rural households during the years 2008 to 2018 of the Statistics Center of Iran.

The results of the study showed that the food security of the community is more affected by the price shock of livestock products. Among the various urban and rural income groups, poor rural households will suffer the most from rising commodity prices. With a 30 percent increase in the price of livestock products, the average caloric intake of poor rural households will decrease by about 51 percent, which indicates that livestock products are not essential goods for poor households.

Eventually, the results show that the negative effects of rising livestock prices on food security will be somewhat mitigated by a 17% increase in household incomes assuming other food prices remain stable, but the worrying food security situation of poor rural households will remain strong. Therefore, to provide the calories needed by the most vulnerable sections of society to production and price shocks, the same nominal increase in the nominal income of this group of households in accordance with other sections of society is not enough and it is necessary to consider different scenarios of granting supportive food baskets and increasing income more including nominal than other household groups.

In this study, a polynomial goal programming approach based on the mean-variance-skewness-kurtosis model is used to select the optimal portfolio based on different investor preferences structure. Then systematic risk is considered as a constraint in the model because of its importance in decision making. Extreme Downside Hedge is considered as the measurement of systematic risk. The data used in this study include daily stock price of selected food industry companies and market index for 2015-2019. The results showed that investor preferences influence portfolio selection and allocation of capital, so individuals can choose their portfolio based on their preferences. The risk entry into the model also indicated that given this limitation, portfolio selection would shift to the stocks of companies that are less affected by market volatility. Based on results, it is suggested that in future studies the model be developed based on other limitations such as different degree of risk aversion in decision making. The model can also be designed based on fuzzy logic and its performance be investigated under such conditions. Also, results of each estimation can be considered as an investment patern for individuals.

Livestock activity in Mazandaran province has a significant share in employment and production of related products in the country. To achieve economic development, identifying the challenges and potentials for progress in this sector are important factors. The purpose of this study is to analyze the resources, activities and institutions of Mazandaran province with an economic approach to strengthen production and employment and find a suitable strategy to increase the employment and production of livestock in Mazandaran province.

in this study, by considering the production capabilities of livestock products in Mazandaran province, and using a SWOT analysis based on the AHP approach, the problems, and opportunities in the livestock sub-sector in Mazandaran province were identified and examined. To extract pairwise comparisons of internal and external factors, 15 experienced experts in the livestock subdivision of the Agricultural Jihad Organization and Departments of Mazandaran Province were interviewed in 2018. Finally, using the Quantitative Strategic Planning Matrix (QSPM) approach, strategies for developing this subsector were prioritized. Excel and GAMS software were used to estimate the results.

The results of SWOT analysis in the analysis of internal and external factors showed that to develop the livestock sub-sector in Mazandaran province, aggressive strategies can be useful. Also, the results of prioritizing strategies through the QSPM approach showed that according to the aggressive strategies in the livestock sub-sector, "export development and entry into global markets", "product and market development", " Creating facilities for the export of Caspian Sea littoral states " and " Modified breeds of livestock to increase production " with scores of 6.467, 6.147, 5.442 and 4.947, respectively, can be considered as strategies for developing production and employment in the livestock sub-sector of Mazandaran province .

According to the results of internal and external factors in SWOT analysis, the optimal strategy in livestock activity in Mazandaran province is the aggressive strategy of SO.  According to the results of this study, strategies such as development and promotion of traditional livestock to semi-industrial and industrial, reducing mediation and intermediation and regulating market by collecting accurate statistics and information sources, Modifying breeds of livestock, supporting exports especially exports to Caspian Sea littoral states, improving the quality and standard of processed products for sale in regional and trans-regional markets, recognizing the needs of target markets and Such cases are suggested.

Determination of the cropping pattern and optimal combination of crops by diversification of cultivation, as an approach to reduce income risk given the economic issues and resources. Income risk as combination of price and performance risks is one of the most important risks for farmers. In this study optimal cropping pattern of crops was determined to reduce income risk by applying risk and return measures in Gorgan County in 2018. For this purpose, the diversification-consistent DEA model based on directional-distance criterion was used. The results showed that 0.05 and 11 percent decreases, respectively, in the risk measures of the coefficient of variation and conditional value at risk. Also, a 24 percent increase of the expected profit measure in the optimal cropping pattern compared to the current pattern. Furthermore, the share of more profitable crops such as medium and long rice grain with high quality and rapeseed increased in the optimal cropping pattern and share of crops such as wheat and potatoes decreased. Due to the 60 percent share of medium and long rice grain with high quality in the optimal pattern, it is recommended to use tools such as income insurance and compensating for the development of rice cultivation in the region.

The gap between the price received by the producer and the price paid by the consumer is referred to as the marketing margin. How decision-makers, consumers and supply chain brokers make decisions is affected by various shocks.

In this study, a stochastic dynamic general equilibrium model and impact-response functions were used to investigate shocks during the period 1974-2014.

The results showed that the shock of good news and technology leads to a positive deviation in production and a negative deviation in the marketing margin of the agricultural sector. Also, price fluctuations due to news and technology shocks in the Iranian economy move in line with the cycle of recession and prosperity. Thus, news and technology shocks play an important role in the fluctuations of important economic variables. Also, the impact of the media on the marketing margin of the agricultural sector, the importance of news and transparency in the economic environment should be considered by policy makers.

news shock in general leads to a negative deviation in the marketing margin and the marketing margin of the agricultural sector in particular. Also, price fluctuations due to technological shocks in the Iranian economy move in line with the cycle of recession and news boom, because the emergence of technological shocks leads to a positive deviation of production.

Non-certainty is a prominent feature of real world issues. Since the change in the input data, though small, can dramatically change the results of the DEA models, applying ways to deal with non-certainty is an inevitable aspect of the use of these models. Therefore, in this research, the combination of robust optimization with Data Envelopment Analysis was used to study the technical efficiency of broiler farms with the capacity of over 30,000 broilers in Sari city. The results of Robust Data Envelopment Analysis model indicate that in the given uncertainty level (ε=0.1), as the level of conservatism increases from 0 to 8, the average of efficiency scores decreases from 96 to 93 percent and the number of efficient farms decrease from 23 to 18 farms. In addition, the greatest difference between the amount of optimal and actual consumption of inputs belongs to the cost of taking drugs and vaccines. Given that the largest part of drugs and vaccines costs are spent when a disease spreads, Applying appropriate policies to prevent the spread of epidemic diseases such as choosing healthy broilers in the same age, using proper nutrition, providing comfortable aviary, choosing proper density of broilers, dissolving the carcasses of ill broilers, using disinfectants properly and also using experts to determine the appropriate time and amount of drugs and vaccines can greatly help to enhance the efficiency of inefficient farms.

Diameter at the breast and height of trees are the most important components in the forest inventory. Measuring the diameter of trees is simpler and less costly than height; hence, some equations are used to predict height by diameter of trees. In the present study, the ability to use different diameter-height models for estimating the height of beech trees (Fagus oriantalis Lipsky) in uneven age and mixed stands in Hyrcanian forest, North of Iran. In this study, a systematic-randomly sampling method with 150 × 200m network (0.1 ha) was used. Diameter and height of the thickest and nearest trees (690 individuals) to the center of circular sample plots (345) was measured. 70% of the data was used for modeling and the remaining 30% was used for evaluating estimated models. Using 20 nonlinear regression models including 11 two-parameter models and 9 three-parameter models, the relationship between height as a dependent variable and diameter as an independent variable was considered and analyzed. In order to evaluate the models and select the best model, the validity of the statistical models was evaluated using RMSE and BIAS. The results of the model evaluation criteria did not differ significantly. Korf, Ratkowsky, Naslund and Weibull models with root mean square error of 4.17, 4.19, 4.21, and 4.23 and BIAS of 0.17, -0.38, -0.55 and -0.1, respectively had a good ability to accurately estimate the height of beech trees. According to the region conditions, these models can be used to estimate the height of beech trees in broadleaved and mixed forest of northern Iran.

Agriculture as one of the basic pillars of development, has an important role in economic development.  Accordingly,  using cropping pattern optimization is a proper way for agricultural development. Therefore, in the present study, optimal cropping pattern in Goharbaran region of Sari city has been evaluated in terms of multi-objective planning has been done using non-linear programming and genetic algorithm and finally compared each other.

Required data for this study has been collected with interview 250 of farmers during the 2014-2015.

Comparison The results of this study showed that the optimal pattern of non-linear genetic algorithm is superior compared to ordinary non-linear programming model. Because increasing the profit of the genetic algorithm is about 0.2% higher than normal nonlinear planning, while reduced risk the by about 6 percent. Also, the amount of production increases by about 18 percent in the genetic algorithm and the consumption of chemical fertilizer is 7 percent lower than normal nonlinear programming. Based on the results, all four sustainable farming objectives in the framework of multi-objective model in the model obtained from the genetic model have a superiority to the typical nonlinear planning model.

Since the proposed cropping pattern of genetic algorithm causes to increase farmers' gross margin compared to the ordinary nonlinear programming, therefore, the government's encouragement and support is mandatory of the farmers in applying the results of such models.

Selection of suitable crops for cultivation in an uncertain environment is considered as an important management topic in the agricultural sector. When faced with uncertainty, the only solution is to use subjective judgmental of persons in domain field rather than historical data. Based on the provided evidence, the quantification of subjective judgmental in the framework of probability theory and risk programming is not true and should be carried out in another theory called the uncertainty theory and uncertain programming method. With perception these conditions and considering that the agricultural sector is always faced with uncertain variables such as price of crops and weather conditions such as rainfall, in this study the optimal cropping pattern of in Goharbaran region of Sari was determined using uncertain programming in terms of uncertainty in rainfall and crops price. To elicitation the uncertainty distribution of these variables based on the subjective judgments of the farmers, 42 farmers were questioned randomly through cluster sampling in 2017. Subsequently, by calculating a causal relationship between rainfall and crops yield, uncertainty distribution of yield was also extracted and thus expected profit were calculated based on uncertainty theory. In order to calculate and minimize the uncertainty of the model, a Tail Value at Risk index was used. The results showed farmers that predict much uncertainty for prices and rainfall, it is advisable to growth the Tarom rice and tomatoes and to prevent Shiroodi rice and watermelon in order to deal with uncertainty and achieve a certain expected profit.

The resistive economy, in the sense of managing the current situation in the country, minimizes the risks. In other words, establishment of the necessary institution in Iranian economy by using a set of policies, laws, and executive measures in such a way to minimize its risk against harmful shocks and disturbances, especially foreign and international ones, would provide the ground for the country to achieve sustainable economic progress. One of the most important methods in this regard, in creating the infrastructure of a resistive economy, is development of the agricultural sector. In fact, due to the distinctive features of the agricultural sector, this sector can be considered as the driving force of the economy within the framework of the resistive economy. To achieve such an economy, the challenges and potentials facing this sector must be identified while determining optimal investment for the basic sectors. Due to the capabilities of agricultural production in Mazandaran province, in this study, for identifying the problems and opportunities in the subsectors of agriculture and horticulture, a type of SWOT analysis was used in which relative weights are calculated through a linear mathematical programming model. Finally, by using the QSPM approach, prioritization strategies were developed for each subsector.

In the SWOT analysis, the AHP approach was used to extract the pairwise comparisons of internal and external factors from the opinions of the interviewed experts in the subsectors of agriculture and horticulture. SWOT analysis has been used to determine strengths, weaknesses, opportunities, threats, and the combination of linear programming. Therefore, AHP approach is used to calculate the weight for criteria and alternatives at each level. In this research, a two-step linear programming method has been used to calculate the priority vector. In the first step, according to the pairwise comparison matrix, a formulation that provides a consistency limit is used. In the second step, according to the compatibility limits obtained in the previous step, for calculating marginal weights of the criteria, another linear programming model is used. After calculating the relative weights of each of the components of strengths, weaknesses, opportunities and threats, as well as determining some strategies, using expert opinions, the QSPM approach has been used to prioritize strategies. For this purpose, the attractiveness coefficients of each strategy were extracted according to the Swot components and by multiplying the attractiveness coefficients by the relative weights, the total score for each Swot component was calculated for each strategy and finally with the total score of the Swot components, a total score for each strategy was calculated. Finally, Excel and GAMS software were used to estimate the results.

According to the results of SWOT analysis in the agriculture and horticulture sector, among the important strengths in Mazandaran province, this subsector can be ranked first in the production of various products, variety of climatic conditions and suitable water resources, the existence of fertile and suitable lands and variety of products. In contrast to the above strengths, weaknesses such as traditional and small units of exploitation, lack of guaranteed purchase and non-payment of debts on time by the government and cooperatives, low irrigation efficiency and low productivity of inputs (land, labor, etc.), lack of proper marketing system and the weak role of the government are some of important challenges in the subsectors of agriculture and horticulture in Mazandaran province. The opportunities facing the subsectors of agriculture and horticulture include the existence of ports and export terminals, existence of suitable fields for the construction of processing industries, improvement and establishment of fruit and vegetable terminals, and the existence of agricultural sub-graduates. The most important factors that threaten the activity of subsectors of agriculture and horticulture are related to the problems of financing and bank interest rates, land-use change and land trade, excessive import of agricultural and horticultural products, and small number of related processing industries. The results of prioritizing strategies through the QSPM approach also showed that according to aggressive strategies, in the subsectors of agriculture and horticulture, strategies like "Increased aggressive racial reform research ", "Establishment of fruit and vegetable export terminals" and "Development of processing industries", in the subsector of livestock  strategies like "Export development and entry into global markets", "Product and market development", "Establishment of facilities for export to the Caspian littoral states" and "Improvement of livestock breeds to increase production" , and in the subsector of fisheries "Aquaculture Development", "Development of Fisheries Industry", "Private and public sector support and investment" and "Establishment of facilities for export to international markets" are among strategies for strengthening the economy of the province and the country that can be considered.

According to the results of this study, it is suggested that more attention in terms of capital support, and regional policies should be given to the subsectors of agriculture and horticulture in this situation. Also, appropriate measures should be taken to increase the productivity of the agricultural sector in line with the resistance economy. It is also suggested that solutions such as guaranteed purchase, providing facilities for small and job-creating projects, use of agricultural researchers and graduates for improving and implementing of racial reform research, support and development of processing industry of agricultural products, market development and increasing exports of agricultural products, should be used.

The granted credits of agriculture sector are limited and the number of applicants and sub-sectors for these credits are much, therefore, this study tried to determine optimal portfolios for agricultural bank credits by using of fuzzy logic. For performance of this study, a fuzzy linear programming model based on profit maximization was used in the period of 2011-2015. In this study, two scenarios were considered for maximizing the objective function. The first scenario involves maximizing profits facilities and the second scenario involves maximizing the net intake facility (the profit rate that deducted from that the pending rate). In both scenarios, the absence of risk and existence of risk (fuzzy) is considered. The results of this study showed that due to limitations and existing laws, the current model of credits allocation of agricultural bank was not optimal and it is necessary to review in presents and amounts of credits. Also, the credits allocation model based on risks and uncertainties is closer to reality. Agricultural bank should be made part of agro-based industries, agriculture services, poultry and non-related activities with agricultural sector in the higher priorities. Also, agricultural bank considered the rate of arrears credits to avoid them.

stock market may play a significant role in financing food industries. Nowadays, people select an optimized portfolio with several shares instead of choosing only one in order to cope with the investment risk. For this, the systematic risk could be very important as the market is so fluctuating, especially in Iran. So in this paper, we enter a constraint for systematic risk that helps investors in making decision.

As we said, we want to enter systematic risk in the portfolio selection model. We use Extreme Downside Hedge (hereafter EDH) as the measure for the systematic risk of each company in the food industry. This measure relies on the argument that investors are able to hedge against extreme downside risk. The EDH can be estimated by regressing stock returns on a measure of market tail risk. We use Expected Tail Loss (ETL) to measure market tail risk. ETL is defined as the expected value of the loss given that the loss exceeds VaR. Then, the factor models are introduced to capture the systematic risk. In order to actively allocate the systematic risk, we use the definition of the marginal systematic risk introduced by Li et al (2018) to measure the systematic risk contribution of a risk contributor.  First, we choose some variables as factors that affect the return of each company. After that, we calculate the covariance between factors and then make an equation that shows the systematic risk for each company. We apply our methodology to the return time series of 11 companies and the index for the food industry, all listed on the Tehran Stock Exchange (TSE). The data covers the period from 2015 to 2019. Other variables include oil prices, gold prices and exchange rates extracted from the Economic and Financial Databank of Iran.

The results show the Behshahr Ind, Glucosan, Kalber, Margarin, Pars Mino, Pegah Fars and Salemin have positive EDH. This means for these companies the stock returns are affected by volatility of the market, in other words as the volatility increases, the stock returns decrease. It should be noted that the higher the EDH is, the greater the impact is. Also, Gorji Biscuit, Mahram Mfg, Minoo Co and Azar Pegah have negative EDH, indicating the reverse impactability of these companies' returns from market volatility. The higher the EDH, the lower the companies' volatility, also the higher the negative EDH, the higher the market volatility. After calculating the factor model and entering it in the portfolio model, we obtained the optimized result. According to the results, Azar Pegah and Pars Mino, with 86% and 12% have the highest percentage of the optimal portfolio, while Kalber, Pegah Fars and Salemin altogether have 2% of the portfolio, respectively. As the results show, the largest share belongs to the Azar Pegah Company, which is also according to the EDH of the company, in fact, the results show the company whose shares have the highest negative impact from the market has entered to the model. The presence of four other companies in the portfolio given the positive EDH is due to their high average return rather than other companies, since we consider the return as a constraint in the model because of its importance in decision making. It is also worth noting that, the two companies, kalber and behshahr Ind, with the highest positive EDH are not in the optimal portfolio. In order to investigate the effect of systematic risk the model was estimated without considering this constraint. The results show, without systematic risk constraint the optimal portfolio has shifted to companies with higher return and lower risk. Thus, the results of this study indicate that with systematic risk, based on expectations, portfolios will shift to companies with lower impactability from market volatility on the one hand and higher returns on the other.

Finally, the results of the study show, the systematic risk in the model shift the portfolio towards the stocks of companies that are less affected by market conditions. Therefore, given today's fluctuating conditions, it may be useful to apply a model that considers this part of the risk.

Selecting suitable crops for cultivation in a non-certain environment is considered as an important management topic in the agricultural sector. Despite the multiple application of probability theory in quantifying uncertainty in the form of risk programming, validity of this theory depends on the existence of frequency for uncertain variable. For events that cannot be measured by frequency, the only solution is to use subjective judgment of persons in the domain field rather than historical data. Some experts have mistakenly considered subjective judgmentl as a subjective probability and thus used the probability theory to quantify subjective judgmental. But based on existing evidence, the quantification of subjective judgment should be carried out in another theory called the uncertainty theory. In uncertainty theory, in addition to using the belief degree rather than frequency for calculating mathematical moments, the expected value of multiplicative variables will be different with their corresponding relations in the probability theory. Considering these conditions and having in mind that the agricultural sector is always faced with uncertain variables such as price of crops and weather conditions like rainfall, in this study the revenue uncertainty measures of major crops in the Goharbaran region of Sari have been calculated and compared. There are different measures for uncertainty, which in the present study variance and Tail Value at Risk (TVaR) have been used.

The first step in the application of the uncertainty theory is the elicitation of the belief degree or subjective judgments of the farmers about the crop's price and rainfall during the crop season. To elicit the uncertainty distribution of these variables based on the subjective judgments of farmers, 120 farmers were randomly selected in 2018. After eliciting the farmers' beliefs about uncertain rainfall and prices in the cdf method, it was necessary to select the number of belief degree which current practice was based on previous studies in this field. After calculating the above subjective judgments, while assuming linear, zigzag, normal and normal forms for uncertainty distribution, the parameters of each function were calculated using the least squares method. Among the forms of uncertainty distribution functions, the best form of the uncertainty distribution for each crop's price and rainfall was selected by comparing the RMSE indexes. Subsequently, by calculating a causal relationship between rainfall and crop yield, inverse uncertainty distribution of yield was also extracted. Given the inverse uncertainty distribution functions of crop price and yield, required parameters such as expected revenue, variance and TVaR of revenue at 95% confidence were calculated based on operational laws of uncertainty theory and probability theory. Eviews and Matlab software were used to estimate the yield response function and the uncertainty distribution functions, respectively.

In this study, after collecting the belief degree of farmers in the studied area about different levels of price and rainfall, three groups of comprehensive beliefs about prices and rainfall were determined by goodness of fit test. Then, according to the relationship between crop yield and rainfall, the inverse function uncertainty distribution is also calculated. With the uncertainty distribution function of crops price and yield, the expected revenue, variance (standard deviation) and TVaR measure for revenue per hectare of crops were calculated and compared with the uncertainty theory as well as probability theory. Based on the results of this study, the amount of the above measures varied in different belief degree groups,    which is due to differences in the uncertainty distribution parameters. Also, based on the results of this study in all groups of beliefs for all crops, the probability theory compared to the uncertainty theory has estimated the variance approximately more than 30% less, which is a significant result. In other words, applying probability theory to belief modeling will lead to erroneous and misleading results. In the case of the TVaR measure in binary multiplicative variable conditions, the use of probability theory and uncertainty theory in calculating TVaR does not yield conflicting results.

The purpose of this study was to compare the results of applying probability theory for modeling belief degree rather than uncertainty theory in order to illustrate the necessity of using uncertainty theory in belief degree modeling. Studying the effect of probability theory in modeling the belief degree also suggests that the application of probability theory in the presence of two uncertain variables has no significant effect on expected values and TVaR but has a significant effect on variance size. Based on the results of the present study, assuming the binary multiplicative variable, in calculating higher mathematical moments such as variance, the results of probability theory and uncertainty theory make a considerable difference. This demonstrates the need to promote the uncertainty theory in belief degree modeling. In other words, basic training in the belief degree modeling method should be considered.

The overuse of fertilizers in recent years has led to the production of harmful agricultural products and environmental pollution. Studying the environmental efficiency of agricultural activities and transferring the results of these studies to farmers and making practical use of them is one of the important strategies that can have a significant impact on the production of healthy products with less negative impacts on the environment. The main objective of this research is to measure the technical and environmental efficiency of rice farms in Guilan province. Previous studies in agriculture sector considered pesticides and fertilizers as undesirable inputs in the environmental model but considering undesirable outputs as inputs leads to an unbounded PPS, which is not rational from an economic perspective. So in this study, the nutrient surplus (nitrogen and phosphorus surplus) from rice fields, caused by overuse of chemical fertilizer, was considered as an undesirable product in the environmental model.

The presence of outliers in the dataset may bias efficiency estimates: this could make the results meaningless and misleading. The data cloud method is useful in identifying and removing outliers in the data, thus leading to more accurate efficiency estimates. Therefore, at first, farms that were identified as outliers were deleted from the sample. Then the nitrogen and phosphorus surplus were calculated by material balance condition and farms with negative or zero NS and PS were removed from sample, then the remaining farms were used to estimate the technical and environmental efficiency. To determine efficiency, the directional output distance function method was used. In this method, it is assumed that undesirable output is produced along with the desirable output and that means maximizing optimum output while reducing undesired output. The required data were collected by questionnaires from 427 Rice farmers.

The results indicated that the amount of nitrogen and phosphorus surplus in rice farms of Guilan province were 44.63 and 14.31 kg/ha, respectively. Therefore, if rice farmers continue to use current levels of nitrogen and phosphorus fertilizers, environmental problems caused by NS and PS would increase.The average technical efficiency of farmers in constant and variable returns to scale is 59 and 69 percent, respectively. So, it is possible to improve the efficiency of rice farms. In other words, the technical efficiency of farms under assumption of CRS and VRS can be improved 41% and 31%, respectively, through increasing output. The average environmental efficiency was 52%, it indicates that environmental efficiency is low. So according to the directional nutrients efficiency measure, rice farmers can increase their rice production and reduce environmental pollution simultaneously.Based on the results, environmental efficiency of farmers is lower than technical efficiency and there is a significant difference between the average efficiency with regard to nutrient surplus and without it, so if the nutrient is not considered in the model the efficiency score is estimated more than the actual value by 17%. The results also showed that almost 82% of these rice farmers are technically inefficient and 85% are environmentally inefficient. Spearman correlation coefficient between technical and environmental efficiency was 0.772. This indicated there is a positive relationship between these two kinds of efficiency and units with high technical efficiency also have high environmental efficiency.

One of the reasons for over usage of fertilizers and neglecting chemical fertilizer damages by farmers is that most farmers cultivate rice based on past experiences and they are more concerned with the economic aspect of production and not considering the external effects of increasing production methods. Lack of facilities and appropriate market for introducing and supplying healthy crops and the absence of appropriate agricultural policies are major obstacles to producing healthy crops that leads to continued usage of conventional production methods and the inadequate consumption of pesticides and fertilizers. So controlling fertilizer usage in farms, encouraging the consumption of healthy products, establishing training classes for farmers and raising their awareness about dangers of overuse of chemical fertilizers are essential for improving the environmental efficiency of Rice farmers in Guilan province.

Given the importance of understanding the agricultural risk behavior for useful policy making in agriculture, this study aimed at determining the degree of absolute risk aversion of farmers in Goharbaran region of Sari County in Iran using multi criteria decision making (MCDM) analysis. Then, the relation between the degree of risk aversion of the farmers and their socio-economic characteristics were investigated. Required data were collected through questionnaires and interviews with 250 farmers in 2014. The study results showed that majority of the farmers belonged to the group with high level of risk averse; and among their effective socio-economic characteristics (including age, education, farm size, family size, agricultural income, percentage of income from farming, land ownership, farming experience and loan), the variables of agricultural income, percentage of income from farming and family size were positively and farm size and loan negatively correlated with the absolute degree of risk aversion of the farmers. Considering the high degree of risk aversion among majority of the studied farmers, the risk management would seem to be highly important. Therefore, a number of measures like common cultivation, product diversification and population control by the farmers themselves and strategies such as development of cooperatives, credit expansion, guaranteed prices, insurance and establishment and development of futures markets by policy makers were suggested.