مجله اقتصاد و توسعه کشاورزی
سال سی و هفتم شماره 3 (پیاپی 60، پاییز 1402)

 The development process of organic cultivation in Iran is not favorable because the average growth rate of organic agriculture development from 2008 to 2019 according to FAO statistics in 2021 is equal to -0.47% and this is while foods contaminated with various substances Chemicals have an unpleasant effect on the general health of society. According to the statistics of 2021, 600 million people in the world, i.e. 1 out of every 10 people, will get sick after eating food. Since any change in the use of chemicals in agriculture should be based on the behavior of farmers, the purpose of this study is to investigate the behavioral intention to produce organic pistachio production among 5200 pistachio growers in Ardakan county, Yazd province, using the Decomposed Theory of Planned Behavior (DTPB) analysis.

 The current research is classified as a quantitative research and is a descriptive-survey type of research, and in terms of the type of objective, it is considered a part of applied research. Based on Cochran's formula, the sample size was determined to be 358 people. Considering the distribution and dispersion of pistachio growers in different sectors, multi-stage random sampling was used. The face and content validity of the questionnaire was confirmed by a panel of academic experts in the departments of horticulture, agricultural development, plant protection and psychology, as well as experts of Jihad Keshavarzi of the county. To determine the reliability of the questionnaire tool, a pre-test study was conducted among 30 farmers of Aqda Aflatak village, which was part of the villages of Ardakan city, but outside the study sample. The reliability of the questionnaire was estimated using Cronbach's alpha test. Cronbach's alpha coefficient was obtained from 0.649 to 0.836, which indicates acceptable reliability. SPSS22 and SmartPLS2 software were used for data analysis.

Descriptive findings showed that 358 respondents were 336 men and 22 women. Among them, 48 people lived in the village and 310 people lived in the city. The statistical results of the present study showed that the average age of the respondents was 53 years old, who had an average of 9 years of formal education. They had an average of 15 years of experience in the field of pistachio farming, and 30% of household income was dependent on pistachio production. According to the statistical sample of the research in terms of age, the highest frequency (137) were in the 41-50 age group. In terms of pistachio cultivation area, 204 farmers had less than one hectare, which constituted 59.9% of the studied sample. The inferential findings of this research showed that the factors affecting farmers' behavioral intention to produce organic pistachio products were perceived mental norms (β= 0/362) and perceived behavioral control (β=0/185). The findings of this research were in line with the results of Yadavar et al (2018). Also, the findings of this study showed the absence of a significant relationship between attitude and behavioral intention, which was not in line with the results of Safi Sis et al. (2020), Fatemi et al. (2018), Yadavar et al. (2018). According to the research model, the lack of a significant effect between the attitude variable and farmers' perception of the compatibility of organic production methods with their current values and needs, including consumers not purchasing organic pistachios, is notable. This lack of impact may be attributed to consumer-related challenges such as higher prices and insufficient information and awareness about organic products, which could hinder the financial feasibility of implementing organic production. Moreover, the research indicates that the attitude variable did not significantly influence farmers' perception of the ease of applying organic pistachio production methods in the orchard. As a result, the attitude variable did not exert a significant effect on behavioral intention in this context.

 The most important factors in the behavioral intention to produce organic pistachios are the variables of subjective norm and perceived behavioral control. In fact, the issue of environmental protection and measures to prevent water, soil and environment pollution were the popular and accepted behaviors among the pistachio growers in the studied area, and the pistachio growers had come to believe that the use of organic production methods is one of the accepted behaviors of important and prominent people in their accepted social network. Therefore, it is suggested that the extension department of Ardakan Agricultural Jihad Management, by holding various meetings centered on leading farmers in the matter of organic production, provides effective networking for more exposure, contact and communication of pistachio farmers, so as to facilitate their decision making process to enter into organic pistachio production. Also, the findings showed that from the point of view of pistachio farmers, the use of organic production methods and operations is under the control and authority of the farmer and he can use it in his garden if he wishes. Therefore, it is suggested that the extension department of Jihad-Kashawarzi management of Ardakan county continues to provide educational, facilities and services support needed by pistachio farmers and in this regard, planning and providing services in the direction of changing the consumer's attitude towards buying organic products in various ways such as festivals, exhibitions and production Media programs. Considering the importance of removing obstacles to the implementation of organic production in pistachio orchards, it is suggested that necessary support measures be established by the government in the field of covering the operational costs of organic pistachio production until the pistachio farmers reach the markets of organic products inside and outside the country. It is also suggested that due to the diversity in the quality of water, soil and pistachio variety of the farmers, the extension department should organize training courses in such a way that they understand the ease of using this kind of methods and its management in the garden.

The growing importance of energy resources in the formation and growth of economic processes, as well as the need to exploit these resources based on environmental considerations and sustainable economic development, the issue of energy saving as an important issue in all economic infrastructures, including industry. Global warming, declining crop yields, climate change and acid rain are the result of fossil fuel consumption. Hence, in recent years, there has been a growing global emphasis on renewable energy across both developed and developing nations. The primary objective is to decrease reliance on conventional energy sources, mitigate environmental pollution, and attain sustainable energy practices.

Materials and Ways:

In the present study, a multi-objective mathematical planning model was designed, in which the optimal crop cultivation model in the southern grove area of Babol city, taking into account the maximum profit from the sale of crops, relying on expanding the use of renewable energy sources in the supply basket Irrigation water and reduction of fossil energy consumption used in irrigation water supply were determined. The objective functions of the study are in the form of two

profit maximization and minimization of greenhouse gas emissions. The amount of profit considered in the present study is equal to the difference between income from crop production and total costs, including irrigation, planting and harvesting costs, seed costs, fertilizers and pesticides, and labor costs. The greenhouse gases considered in this study encompass CO2, N2O, and CH4, with the objective of minimizing their emissions for the determination of an optimal crop pattern. The study endeavors to resolve the proposed nonlinear multi-objective pattern utilizing the constraint epsilon method. Subsequently, employing the energy link indexes (E), the optimal solution is identified among the proposed alternatives through the TOPSIS multi-criteria decision model. The statistical population for this investigation comprises farmers in the southern forest area of Babol city. The analysis of results has been conducted using Matlab, Lingo, and Excel software.

In this study, a multi-objective model with objective functions of profit maximization and minimization of greenhouse gas emissions subject to energy, energy flow, water, fertilizer, and capital and land constraints using the method the constraint is resolved and eventually the study decision variables are obtained. In terms of recyclable energy, the model suggests that four types of Tarom rice, Shiroodi rice, soybean, and corn be grown with 0.40, 0.34, 0.14 and 0.12 ha / ha, respectively. As can be seen, in accordance with the outputs of the optimal model in terms of renewable energy, most of the cultivated land is allocated to Tarom and Shiroodi rice. The total amount of energy required in the optimal model in terms of renewable energy was 2518 kWh, of which fossil energy is 79% and solar energy is 21%. According to the calculations made in Equation 3, to provide 21% (518 kWh) of solar electricity required by the irrigation system in order to irrigate one hectare of the proposed model of the optimal model in the study area, a solar panel with a capacity of 0.22 kW will be required. The results of the model show that in terms of renewable energy, with the implementation of the proposed model, the profit of farmers in the region per hectare increases from 14776.21 to 14778.18 million rials compared to the situation of non-renewable energy in the entire growing season. In other words, in the current situation, people cultivate crops regardless of energy consumption and production costs (traditional method of rice production by local farmers), while by choosing the right model, the farmer's economic benefits can be increased by 0.013%. At the same time, it saved a significant amount of fossil energy consumption.The minimum emission target of the model in terms of renewable energy states that for the cultivation of 0.40 hectares of Tarom rice, 0.34 hectares of Shiroodi, 0.14 hectares of soybean and 0.12 hectares of corn, at the rate of 2836 kg equivalent to CO2 pollution Fertilizers, pesticides and fossil fuel consumption will be released, which is 9% less than the current situation where only fossil fuels are used to irrigate crops.

In the present study, the interests of farmers were considered by considering the maximum profit from the sale of agricultural products by relying on the use of renewable energy sources in the energy basket of the agricultural sector (by reducing the fuel consumption of fossil energy sources used) in determining the cultivation pattern. Optimally calculated and compared with current conditions. The results show that the optimal model in terms of renewable energy, shows a more appropriate achievement of goals than in the absence of renewable energy. To this end, it is suggested that agricultural policy makers, by promoting the use of solar energy in irrigation and the use of this large capacity in the country, justify farmers to the potential benefits of solar energy (in the agricultural sector) and its widespread use, reduce current agricultural subsidies in the energy sector. Fossilization and subsidizing solar energy, encouraging the private sector to invest in solar projects can help power irrigation projects.

The relationship between economic development and the environment is known as one of the most important issues facing societies. If in the context of sustainable development, economic and environmental activities are considered together, the environment and economic development are two complementary factors and, as a result, it will lead to ecological balance. In this case, economic activities will not disturb this balance. Presently, the imperative of safeguarding the environment and attaining sustainable development has ascended to a prominent position on the agendas of diverse societies, Iran included. This commitment is underscored by the execution of comprehensive economic, social, and cultural initiatives aimed at fostering long-term ecological resilience and balanced societal progress. Therefore, to preserve the environment and meet the goals of sustainable development, as well as to guide and rationally manage plans and projects, especially in the agricultural sector, serious measures should be taken. Therefore, this study was carried out to evaluate the operational, environmental, and eco-efficiency of the major agricultural products of the irrigation and drainage networks of Gotvand.The irrigation and drainage network of Gotvand is located in the southwest of Iran in Khuzestan province. This network is designed to irrigate lands located in three regions of Gotvand, Aghili, and Dimcheh, enclosed between two rivers, Karun and Lor. According to the official statistics of government organizations, the consumption of fertilizers and chemical poisons in the lands covered by this network is 3.6 times the average limit in Iran. The excess irrigation water in this network is returned to the rivers by the built-in drains and causes water pollution downstream of the network. Therefore, considering that environmental protection is one of the most important aspects of sustainable development, it is very important to investigate the effects of the use of pesticides and chemical fertilizers in agriculture and to introduce solutions to improve the efficiency of the environment in the study area.

Eco-efficiency includes operational and environmental impacts, which are presented as the ratio of the weighted sum of outputs to the weighted sum of inputs (operational inputs + environmental inputs). However, since agricultural activities are carried out in uncertain environmental conditions, there is uncertainty regarding inputs and outputs. The uncertainty in some of the effective input and output parameters in the ranking of networks, and as a result, the inaccuracy of the model calculation results, and the need to pay attention to the use of uncertainty models, make it more obvious. Therefore, in the present study, to include the conditions of uncertainty and risk, the robust data envelopment analysis (RDEA) model was used, which is one of the most powerful and useful models in conditions of uncertainty. The required data were collected by completing a questionnaire of the Gotvand, Aghili, and Dimche regions using a simple random sampling method in 2019.

The alfalfa producers in the Gotvand region assigned the highest environmental and Eco-efficiency by obtaining points in the range of 81 to 89 percent and 90 to 96 percent, respectively. The rice crop in the Aghili region had the highest types of operational efficiency based on different levels of deviation probability in the range of 77-87%, environmental efficiency in the range of 80-90%, and environmental-economic efficiency in the range of 87-95%. Dimanche sugarcane region has the highest average of efficiency types for different levels of deviation probability by obtaining points in the range of 78 to 90, 80 to 89, and 87 to 95 respectively for operational, environmental, and Eco-efficiency. Comparing the results of technical efficiency with environmental efficiency shows the lack of attention and skill of farmers in the correct and optimal use of production inputs. Therefore, it is necessary to hold educational and promotional classes to empower farmers to improve production methods and optimal consumption of inputs to improve farmers' income and increase their profits. Given that a substantial portion of energy consumption within the agricultural sector is attributed to fuels and diesel, optimizing energy usage and promoting the adoption of newer, less polluting energy sources emerge as crucial imperatives. Enhancing environmental efficiency in this context involves a strategic focus on reducing reliance on traditional, environmentally taxing energy forms in favor of more sustainable alternatives.

The average operating efficiency in all different probability levels for the studied products in Goutvand , Aghili, and Dimche areas, except for beans in the Gatund area, was estimated to be lower than the average environmental efficiency. This shows the lack of ability and skill of farmers to produce a certain product with the lowest amount of input, while the farmers of these areas pay great attention and care to environmental issues.

The agricultural sector is one of the most basic and vital component in the social and economic structures of any country. Today, with increasing in the world's population and needing to provide food on the other hand, and increasing in the price fluctuations of agricultural products on the other hand, traditional agriculture is no longer responsible for the sustainable food security of the world population. In recent years, the occurrence of two incidents of the spread of the corona virus and the outbreak of war in Ukraine, have made the price of agricultural products extremely unstable. Today, even many farmers and agricultural associations in developing countries are not aware of the changes in market prices and the latest technological developments in the field of agricultural product prices, and they do not have the ability to discover the optimal price for selling their products. In such a situation, the use of intelligent models in order to accurately forecast the price of agricultural goods is vitally important for farmers and agricultural sector activists.Smart agriculture is an emerging concept that involves the integration of advanced technologies to collect and analyze data in order to solve the challenges and problems of the agricultural sector. In the meantime, forecasting the price of agricultural products involves with some basic challenges; including: 1) Data of agricultural product price is mostly non-linear, unstable, non-normal, and noisy and follows chaotic behavior, 2) There is uncertainty in the forecasted data obtained from different models, 3) In the studies related to price forecasting, the "publishable base model" is not provided in order to provide the forecasted price values. Therefore, the aim of this study is to provide a non-linear hybrid intelligent model for accurate forecasting of the future price of pistachios in the field of smart agriculture through managing the multidimensional nature of data, considering uncertainty in the forecasting data and finally building a publishable base model in the field of product price prediction.The hybrid model proposed in this study has the following innovations; 1) the deep learning neural network model and the Auto-Encoder network have been used to forecast the agricultural product price and determine the optimal lag of price as an input variable simultaneously, 2) The Monte Carlo method has been used as a non-parametric method to provide a confidence interval and calculate the most likely price that can happen, 3) The practical application of price forecasting models, i.e., "publishable base model" is presented in order to provide forecasted price values.

The implementation of the proposed hybrid model in this study includes the steps of "data preparation", "data feature engineering", "training and testing the final deep learning neural network model", "building the optimal base model", "creating the most likely price scenarios" using the Monte Carlo method and "inferring new prices or making out-of-sample forecasting" with new data sets” by feeding new price data into the deep learning neural network model. In the proposed hybrid model, data mining techniques are used, including Wavelet Transform (WT), Long-Short Term Memory (LSTM), Auto-Encoder network (AE), Monte Carlo-Markov chain (MCMC) simulation method and the concept of "inferring new prices".In the data preparation stage, using methods such as data smoothing, data rebuilding, correction of duplicate data in several consecutive days, and correction of missing data, the continuous set of pistachio future price time series is prepared to enter the primary model. Also, the wavelet transform function has been used for de-noising the data, the Auto-Encoder network has been used to determine the optimal lag, the Monte Carlo-Markov chain simulation has been used to create the most probable price scenarios, and the deployment concept has been used for out-of-sample forecasting with new data sets. The data used in this study is the time series of the daily price of pistachio futures on the Iran Commodity Exchange in the period from 10/13/2019 to 12/14/2021 in Rials per kilogram.

The results of this study showed that 1) by using the wavelet theory to de-noise the data, the error rate of the price data was reduced and the data had a stable trend, 2) the results of the implementation of the Auto-Encoder network showed that the optimal lag of one can be used as an input variable to forecast the future price of pistachios, 3) The outcomes derived from employing Monte Carlo-Markov chain simulation, coupled with out-of-sample forecasting using the new dataset, reveal compelling insights into the future pricing of pistachios on the Iranian Commodity Exchange. According to the analysis, the most probable and sanguine projection places the future price at the price ceiling of 213 thousand Tomans. Impressively, the forecasted price exhibits a minimal variance of merely 0.7% from the actual observed price, attesting to the precision of the proposed model. The overall accuracy of the model stands commendably high at approximately 93%.

Based on the results, firstly, the forecasted price has a small error with the actual price and this small error shows the power of the built model in forecasting the future price trend of pistachios. Secondly, the alignment of the price resulting from the Monte Carlo simulation with the new price can also be used as a confidence index in risk management for traders and market participants. Thirdly, the process set is the most complete value chain in the production of price forecasting models. Therefore, the use of the proposed hybrid model and the use of the components used in it, i.e. wavelet transform function, Auto-Encoder network, deep learning neural network, Monte Carlo simulation and the concept of inferring new prices; are suggested.

The market and the conditions governing it, especially the food industry, are always important issues for policymakers, decision makers and planners in the public and private sectors. Because market conditions are important in terms of the level of competition or monopoly on access to goods from the point of view of government decision-makers and the price from the point of view of production and private sector suppliers. In addition, both access and price factors greatly impact the amount of consumption and, consequently, the level of consumer’s welfare. Dairy products, especially milk and cheese, from the consumer's point of view, in addition to being good for health, from the point of view of agricultural producers, it is a strategic product, and from the point of view of government decision-makers, it is a factor in changing the level of social welfare. Of course, the market behavior has an important effect on the price and the motivation to produce and finally consume milk and cheese. However, factors such as encouraging consumption through public advertising can have a great effect on consumption motivation (Shahbazi, 2015). But the lack of competitive conditions in the production of products can reduce the consumption of milk and cheese and, as a result, create lost welfare for consumers and society. In other words, having a large share of the milk market by a small number of companies and production companies has made the market of dairy products a monopoly market and the existence of a monopoly in the market is considered one of the most important factors that cause lost welfare for consumers. (Gisser, 1982; Shahbazi, et al., 2009).

In this research, an attempt has been made to provide a structural framework for examining the performance of the dairy industry, especially milk and cheese (in terms of measuring the level of competition or monopoly). Based on the theory of NEIO, it is possible to quantify firms' market behavior in the absence of marginal cost data. The choice of demand model is of key importance in this type of analysis, since modeling a firm’s market behavior relies on correct representation of consumer preferences (Hovhannisyan & Bozic, 2013). In explaining consumer behavior, the functions selected for demand should be compatible with consumer theory, satisfy its theoretical characteristics, be easy to estimate, and have high predictive power. If, as the research shows, there is a non-linear relationship between demand and income, using a linear expenditure model will lead to an error and provide incorrect parameters. Recently, discrete choice demand models, such as the Logit specification, have increased in popularity in applied industrial organization research (Werden & Froeb, 1994). The random coefficient logit demand model is of particular interest, which allows for product differentiation and consumer heterogeneity. Finally, in this study, like some leading studies in the field of estimating the demand function of goods such as Hovhannisyan and Bozic (2013), uses an inverse demand system to create a structural framework of market behavior. In this approach, prices are endogenous. To model the inverse demand function and supply function, Leunberger's profit function approach (Luenberger, 1992) is used. Also, using the CV approach based on the study of Hovhannisyan & Bozic (2013), the amount of markup due to the existence of market power at the retail level is estimated for the years 2015-2021 in 7 selected provinces.

The choice of demand specification may significantly affect the estimation of structural coefficients. Therefore, several demand determination tests are performed using the Bewley likelihood ratio test (Bewley, 1986). The results show that there are quadratic utility effects in inverse demand functions. By using this feature, it is shown that the regional heterogeneity, i.e., , is the same as the lagged quantity, i.e., , the lagged price, i.e.,  and non-linear time effects, i.e., , are significant effects regarding the demand for milk and cheese. But seasonality, i.e., , has a negligible effect on the market for milk and cheese. The final demand relationship is estimated based on the results of the tests of various constraints on the model. The estimation of the complete model is done using the FIML method. Based on Hovhannisyan and Gould (2012), the constraint is applied. The estimation results indicate the presence of nonlinearity effects (effects) in utility function. Also, regional heterogeneity ( ), and the lagged quantity ( ), lagged price ( ) and nonlinear time effects ( ) have essential effects on milk and cheese demand. The results show that in the case of the milk industry, retailers have received the most mark up in B1 brand milk (milk produced by Iranian Dairy Industries Co.-IDIC) during the studied years. In such a way that on average they have received a markup equal to 4.8%, while this markup for milk produced by other brands is equal to 3.9%. Regarding the cheese industry, retailers receive a higher price markup for B2 cheese compared to cheese produced by competing companies of IDIC, averaging at 4.0%. However, the price markup for cheese produced by IDIC is only slightly lower, averaging at 3.9%. Also, the results show that there is a lot of regional heterogeneity among the provinces of the country (the studied provinces) in the dairy products industry that the variation in the degree of advancement of dairy industries across various provinces may be regarded as the foremost contributing factor. So that the surcharge at the retail level is different in different provinces. The price increase in B1 brand milk has changed from 3.3% in East Azarbaijan province to 7% in Razavi Khorasan province. But the retailers have received markup for milk produced by other brands, i.e. B2, from 3% in West Azarbaijan province to 6.9% in Isfahan province. In the case of cheese, the surcharge received by competing companies of IDIC has changed from 2% in Fars province to 6.5% in East Azarbaijan province. However, the retailers have received additional price from 1.5% in East Azarbaijan province to 6.7% in Fars province for the cheese produced in IDIC.

As anticipated, the market dynamics have exerted a significant influence on pricing, thereby shaping the incentives for milk and cheese production and, ultimately, consumption. The lack of competitive conditions in the production of milk and cheese (which has been mentioned in some studies such as Shahbazi et al., 2009 and Shahbazi & Faryadras, 2018 can reduce the consumption of milk and cheese and in the result of creating lost welfare for consumers and society. In other words, the possession of a large share of the milk market by a small number of companies (especially IDIC) and production companies makes the milk market a monopoly market, and the existence of a monopoly in the market is considered one of the most important factors that cause lost welfare for consumers. One of the processes that create competition is the development of the industry in terms of increasing the number of production companies by encouraging people to create dairy companies by providing incentive facilities from the government. Planning and investing in product advertising, especially in brands with a small market size, can help increase competition and transparency in the market. Acknowledging regional disparities in the branding and marketing of milk and cheese commodities is a crucial factor that demands attention. Additionally, factoring in market share dynamics and evolving consumer presumptions can provide valuable insights for making informed decisions regarding production and management strategies.

Introduction:

Grape (Vitis vinifera L.) is one of the most important agricultural products in the Mediterranean. Today, grapes are grown in a large area of the world's gardens. The world production of grapes was about 77.8 million tons in 2018, of which 1.3 million tons were converted into raisins. According to the latest data of FAO, Iran has an annual production of 24.45 million tons of grapes in an area of 213 thousand hectares, accounting for 3% of the world's grape production. The average yield per hectare of vineyard is reported to be 15.5 tons. The purpose of this study is to determine hot spots in terms of energy and cost in the production of Malayer grapes with the approach of material and energy flow costing (MEFCA). The primary focus of material and energy flow cost accounting is on waste (waste of energy, materials and potential human capacity). 

Materials and Methods:

Material flow cost accounting was introduced in the late 1990s in Augsburg, Germany as a tool for green productivity management. This is known as a tool to increase productivity by reducing the use of materials, energy and human resources. Unlike life cycle assessment, which only weighs the environmental impacts of production and does not provide a solution for simultaneously reducing environmental impacts and increasing economic profit, material flow costing is recognized as an efficient tool for managing resources, wastes, and environmental impacts, and has covered the shortcomings of life cycle assessment. Material flow cost accounting helps to discover hidden costs and waste by objectifying the flow of materials in the production process. Based on ISO 14051 material flow analysis occurs in quantitative centers (QCs). In general, each quantitative center divides the production process into several parts. The basis of material flow and energy costing is material flow balance. This means that the inputs must be the same as the outputs. Based on this balance, positive inputs (i.e. consumable inputs) and positive outputs (i.e. product performance) and negative outputs (i.e. wastes and emissions during production) should be equal. The primary focus of material and energy flow costing is on waste (e.g. waste of energy, materials and potential human capacity). Allocation of costs to positive and negative products in each quantitative center is done in the following way:- Material cost (including raw and industrial materials used in the production process)- Energy costs (including electricity or buying diesel fuel)- System costs (including labor costs, transportation costs and system maintenance)- Waste cost (including waste management costs)The system boundary included the background processes that the farmer was directly involved in using and managing. Grape data was collected in the crop year of 2020-2021 from Malayer vineyards. 

Results and Discussion:

Based on the results of the study, the average energy input including renewable, non-renewable, direct and indirect energy for grape production was 42234 MJ ha-1. The negative energy resulting from the wastage of chemical fertilizers, grapes, irrigation water and pesticides was 28650 MJ ha-1. The total positive output energy was calculated as 296180 MJ ha-1. Nitrogen fertilizer with 27% and animal manure with 19% had the largest share in input energy for grape production. In terms of negative energy, grape waste accounted for the largest share with 82% and the Irrigation water wastage was the next with 16%. Energy indices including energy efficiency (6.33), energy productivity (0.59) kgMJ-1), energy intensity (1.68 MJkg-1) and net energy gain (1225295 MJha-1) were calculated for grape production. The cost of grape production per hectare was $2,779. The highest input costs were related to labor and irrigation water, which cost the farmer 1644 and 680 dollars per hectare, respectively. The calculated negative production in grape production was equal to 2560 dollars per hectare. The main negative production in grape was related to wastage of grapes and irrigation water, which brought hidden costs of 2108 and 442 dollars to the farmer, respectively. The economic indicators of gross income (13954 $ha-1) and cost-benefit ratio (4.5) were calculated. 

Conclusion:

Transitioning from flood irrigation to drip irrigation is anticipated to enhance irrigation efficiency by 50%, resulting in an incremental addition of $221 to the farmer's income while concurrently reducing labor costs. Additionally, emphasizing training for workers can prove pivotal in minimizing grape yield wastage within the region.

In order to meet the increasing demands of the growing population, it is essential to boost rice production. This not only ensures food security but also helps maintain environmental well-being. To achieve these goals, it is crucial for crop management research to focus on increasing rice yields while minimizing water usage. In Iran, particularly in the Rudbar region, recognizing the significance of rice cultivation in agriculture is of utmost importance. To improve rice field management, various aspects such as water and soil resource management, pest and disease control, nutrition management, sales and marketing strategies, human resources and social capital management, as well as technical and agricultural improvements need to be addressed. Therefore, the aim of the present study was to identify more effective methods for managing the rice fields in Rudbar county, Iran.

Materials and Methods:

 Initially, the researchers conducted a comprehensive analysis of available national and international databases to gather background information for the study. This analysis aimed to establish an initial list of components that could contribute to improving the management of rice fields. The statistical population of the study consisted of all 850 rice farmers in Rudbar City. Using the Karjesi-Morgan table, a statistical sample size of 265 participants was estimated, which corresponded to the size of the population. Eventually, 252 questionnaires were collected after distributing them to the participants, resulting in an 88% response rate. The opinions of faculty members from Tehran University's Department of Agricultural Management and Development were sought to assess the content validity of the questionnaire which was finally confirmed. To assess the reliability or internal consistency of the questionnaire, Cronbach's alpha coefficient was calculated for each of its components. All coefficients were found to be above 0.7, indicating good reliability of the study tool. The data obtained from the questionnaires was subjected to statistical analysis using the LISREL 8.8 software. A confirmatory factor analysis model was applied to examine the data. The reliability of the indicators loaded on each structure was evaluated using the t statistic. Indicators with values exceeding the critical limit of 1.96 were considered to have the required precision for measuring the relevant structure. Additionally, significant factor loadings were determined by extracting values greater than 0.5 from the factor loadings. It is important to note that Cronbach's alpha (with values higher than 0.7) was utilized to assess the reliability of the constructs.

The research findings highlighted several significant factors that have a substantial impact on improving the management of rice farms. These factors encompassed various aspects, including water and soil management, human resources and social capital, nutrition management, pest, disease, and weed management, technical and agricultural management, as well as sales and marketing management. Regarding water and soil management, the study emphasized the importance of optimal application of water resources, consideration of water quality, sediment control, and prevention of toxins and sewage from entering rice fields. Given the submerged nature of some rice stalks and the perpetually swampy conditions of rice fields, it is crucial to ensure the quality of incoming water and prevent the presence of mud and sediments. In terms of nutrition management, the research findings stressed the significance of using fertilizers effectively to enhance rice productivity. This involved post-planting strengthening, adherence to appropriate fertilizer consumption guidelines, and the utilization of plant and animal residues. Nutrition management, along with pest and disease control, played a vital role in successful rice field management. Another factor contributing to effective rice field management was the control of pests, diseases, and weeds. The study highlighted the benefits of employing an integrated approach to manage rice plant diseases and pests, which yielded better outcomes. The research findings also emphasized the role of technical and agricultural management in enhancing rice field operations. This included the use of transplanting machinery and improved seeds, mechanization of cultivation activities, and the application of fertilizer spraying machinery. These measures underscored the need for innovation in rice fields, emphasizing the importance of mechanization and the utilization of modern agricultural instruments. It was recommended that rice producers embrace technological advancements to optimize their technical and agricultural practices. Furthermore, the management of human resources and social capital played a significant role in rice field management. This encompassed fostering the growth of social capital, enhancing knowledge and skills, and utilizing mass media for skill and career development. The findings suggested that increasing cooperation, trust, and organization among rice farmers could be a strategy to revive social capital and enhance management practices. Lastly, the study highlighted important features of rice sales and marketing, such as employing an appropriate distribution system, excluding profit-seekers from the marketing cycle, and establishing regular customer relationships. Overall, the research findings emphasized the importance of addressing various factors, including water and soil management, nutrition management, pest and disease control, technical and agricultural management, human resources and social capital, as well as sales and marketing management, in order to effectively manage rice fields. Implementing these strategies would contribute to improved productivity and sustainable management practices in rice cultivation.

The findings of the study indicated the significance of several measures to improve the management of rice fields. These measures included the utilization of additional fertilizers and adherence to fertilizer usage guidelines, as well as the adoption of mechanized planting and harvesting equipment. It was also recommended to provide skill training programs for rice farmers and introduce online marketing platforms to facilitate the sale of rice. Furthermore, the study highlighted the importance of establishing specialized communication channels and implementing a contract system for rice production and sales through dedicated local organizations. This approach would ensure efficient coordination and enhance the management of rice fields. Additionally, private businesses were recognized for introducing new technologies, while the government played a crucial role in providing the necessary infrastructure and platforms to support rice field management. Improving the skills of rice farmers, especially in terms of market innovations, was identified as a key factor in enhancing the management of rice fields. This aspect should be considered alongside institutional and policy-making advancements to ensure comprehensive improvements in rice field management.