Iranian Agriculture Research Articles

Sectoral impacts of climate change in Iran: A dynamic analysis with emphasis on agriculture

Iranian agriculture, the largest consumer of water, is highly vulnerable to sever climate change-induced droughts. This study aimed to analyze the impact of climate change on various sectors, with a focus on agricultural output and gross domestic product (GDP). To achieve this, a dynamic Computable General Equilibrium (CGE) model incorporating a climate damage function was utilized to project the consequences of climate change on various sectors of Iran's economy. The damage function is based on the temperature anomaly. This study simulated the impact of shocks caused by climate scenarios by 2060. The modified Social Accounting Matrix served as the primary dataset for CGE modeling. By simulating climate scenarios up to 2060, the findings indicated that certain agricultural products, such as cereals and livestock, have the potential for an annual output expansion of 2–3.5 % under the most severe climatic scenarios. This expansion is attributed to their lower reliance on capital inputs and their increased final demand for agricultural commodities. Conversely, the growth rates of output expansion and final demand for services products are lower than those for agricultural products. With climate change options, there may be a shift in output composition, favoring crops, agricultural industries, and energy products, while the growth of services output remains comparatively lower. The GDP growth path also deviates from the current path of 1.8 %, reaching rates of 1.5–1.7 %. In the most restrictive scenario, the GDP is projected to decline in the mid-2050s. Similarly, the range for consumption growth is estimated to be 1.8–2.1 %. Climate change does not significantly alter the income distribution within rural and urban income groups. However, it exacerbates rural-urban inequality by favoring urban households with higher consumption levels. The current state of the Iranian economy, especially the agricultural sector, faces increased vulnerability due to climate change. Nevertheless, certain agricultural activities may experience a relatively greater increase in output because of the growing demand for these products.

Investigating the Nexus Between GHG Emissions and AFOLU Activities: New Insights from C-Vine Copula Approach

The greenhouse gas (GHG) emissions from agriculture, forestry, and other land use (AFOLU) account for more than 10% of the total GHG emissions in Iran. To reduce the environmental impact, assessments of Iran’s GHG emissions status are critical for identifying the national policies to achieve Sustainable Development Goals (SDGs) in the bio-based industry. However, there is no study exploring the dependency between AFOLU and GHG emissions in Iran by using the Vine Copula approach. Hence, the study aims to examine the causality direction and correlation structure among selected horticulture, farming crops, livestock, and poultry products and carbon dioxide (CO2), nitrogen dioxide (N2O), and methane emissions (CH4) in the Iranian agriculture sector over the period 1961–2019, to determine which crops or products are more responsible to deteriorate the environment. The empirical strategy used a C-Vine Copula model to measure the correlations together with the Granger causality (GC) test to analyze the causality links. According to the empirical findings, several crops and products are the sources of emissions. Rice and vegetable cultivations, as well as meat and milk products (Kendall’s τ values of 0.37, 0.33, 0.31, and 0.31, respectively), are the leading sources of CH4 emissions. Legumes, eggs, maize, rice, and milk enhance N2O emissions, while CO2 emissions are caused by apple, potato, and apricot crops (Kendall’s τ values of 0.22, 0.18, and 0.16, respectively). Finally, based on the findings, policy implications are offered.

The effects of policy fluctuations on energy indices in Iran's agriculture sector

The effects of policy fluctuations on energy indices in Iran's agriculture sector

Estimating Yield Response Functions to Nitrogen for Annual Crops in Iran

Nitrate is a crucial element for crop growth, and its optimal application is essential for maximizing agricultural yield. In Iranian agriculture, there is a substantial gap between recommended nitrate usage and what farmers actually apply. In this study, our primary objective is to determine the most effective utilization of nitrate for crop cultivation. Simultaneously, we aim to analyze the factors that contribute to the disparity between optimal and current nitrate application practices. Furthermore, our research explores the impact of these differences on regional variations in crop yields. This is achieved using a quadratic yield response function model based on unbalanced panel data spanning the years 2000 to 2016, which includes a total of 14 crop activities and encompasses 31 administrative regions. The results show that rice exhibits the highest nitrogen usage, while rain-fed wheat demonstrates the lowest utilization at the optimal point. Depending on whether random- or fixed-effects estimation is found to be the most suitable specification, average yields corresponding to the optimal level of nitrogen use are calculated by region, or the average across all regions. In Iran, the top-performing regions for cereals like rain-fed wheat and irrigated barley can achieve yields of 1.33 and 3 t/ha, respectively. These yields represent a 31% and a 9% increase from the levels observed in 2016. The outcomes derived from the estimated yield response function will be integrated into comprehensive agricultural, economic, and environmental optimization models. These integrated models will facilitate the assessment of various fertilizer policies on fertilizer use, land allocation, farm-household incomes, and environmental externalities, such as nitrate leaching and nitrate balance. This study holds substantial scientific promise, given its exploration of the policy implications surrounding fertilizer usage, making it crucial not only for Iran, but also for many developing nations grappling with inefficient and unsustainable agricultural practices. It represents the first of its kind in the literature, providing estimations of optimal nitrogen use and crop yield points across all regions in Iran. This is achieved through advanced visualization using GIS maps.

Application of Index Insurance in Iran's Agriculture: case of wheat growers.

Drought-induced risk endangers farmers in arid and semi-arid regions. Insurance is recognized as an appropriate policy alternative to support farmers facing with financial losses associated with production reduction. In this context, present study developed an ex ante index-based insurance program to deal with drought-induced risk of production losses. We applied this model to wheat growers in Iran. After the calibration of the contract parameters, an insurance scheme was optimized and tested. We showed that optimal insurance contracts generate low gain of certain equivalent income, high compensation, and a high basis risk. The best contract was not proportional to the complexity of the proposed index. The insurance program studied is recommended as a proper alternative for currently applying yield insurance.

Strategic analysis of startup ecosystem in Iran’s agricultural sector

This study aimed to analyze the strengths, weaknesses, opportunities, and threats (SWOT) encountered by the Iranian agriculture startups ecosystem. The study was performed in two steps. In the first step, a list of SWOT of the agricultural startups ecosystem was identified via interviews with 15 key experts. In the second step, each of the points was ranked in the form of a structured questionnaire through a 5-point Likert scale by 50 agricultural startups actors. The findings showed that the position of the Iranian agricultural startup ecosystem is in the defensive zone. Five key strategies were identified and prioritized using the QSPM method to exit this area and improve the ecosystem situation. The proposed action plans related to the five strategies can be used as a practical guide for policy makers in agricultural startups to improve the existing ecosystem. The results could cover the lack of a comprehensive scientific and empirical study of startup ecosystem analysis, with a focus on the agricultural context, and provide a basis for further studies in this area.

IMPACT OF AGRICULTURAL TRAINING COURSES ON APPLYING MODERN AND EFFICIENT IRRIGATION METHODS AMONG FARMERS IN TABRIZ, IRAN (TREATMENT EFFECT APPROACH)

Purpose: Many experts believe that the lack of an efficient water management system in agriculture has made it essential to redesign new irrigation models adopted in many successful countries across the world. Improving water productivity in the agriculture sector is undoubtedly one of the crucial measures taken to improve water resource management. Water productivity in Iran's agriculture is about one-fifth of the global standard. Many assume that accurate training courses for farmers or granting production facilities and loans for agriculturists are beneficial steps to use efficient and effective irrigation methods and a subsequent considerable saving in water consumption.
 Design/methodology/approach: This study aims to apply the Treatment Effect Approach to examine the impact of academic or promotional training courses for irrigation efficiency on the application of modern and efficient irrigation methods, by farmers. To do this, 132 trained farmers were assigned to the treatment or test groups, and 212 untrained farmers in Tabriz were assigned to the control group in the crop year 2020. 
 Findings: Results indicated a positive and significant impact of agriculture education and training courses on the probability of using efficient irrigation techniques. In other words, agriculture knowledge increases the probability of using modern irrigation methods up to 344.25. 
 Originality: It is suggested that agricultural policies must grant loans and facilities to agriculturists or those farmers who have received purposeful training courses about the application of efficient irrigation methods.

Barriers of environmentally-friendly entrepreneurship development in Iran's agriculture

Environmental-friendly entrepreneurship as an approach for improving quantity and quality of agricultural products, while preserving environment, has been considered in the recent years. However, various obstacles have prevented development of this type of entrepreneurship in developing countries. For exploring these barriers in the agricultural sector of western Iran, 186 agricultural experts were interviewed using a questionnaire in a survey study. Exploratory factor analysis indicated that environmentally-friendly entrepreneurship barriers can be summarized in a five-factor structure including educational-extension, economic, supportive, technical-managerial and infrastructural barriers. This five-factor structure, which was confirmed through confirmatory factor analysis, was able to explain 68.29 percent of the variance related to the barriers of environmentally-friendly entrepreneurship development in the agricultural sector. Findings of this study, while adding new knowledge to the existing knowledge in the field of research issue, can be useful in planning and policy-making for developing this type of entrepreneurship and production of green products.

Production of Rice-By Product Protein Isolate Using the Subcritical Water Extraction Method

Background: Subcritical water extraction (SWE) is a friendly technique applied to produce rice by-product extract. The aim of this study is using SWE as a new friendly extraction method for producing protein isolates (PI) of rice bran and rice combination as a byproduct of Iranian agriculture product. Methods: D-optimal combined design was used to optimize bran rice ratio, solid/water ratio, extraction time, and particle size to obtain maximum protein. Bran (8-12%) and rice ratio (88-92%) solid water (0.04 -0.12%), time (15-45 min), and particle sizes (420 µm and 710 µm) were selected as independent variables, and protein as dependent variable. After optimization, the effects of extraction parameters on functional properties were investigated. Results: Increasing bran/rice ratio has a significant effect on the protein extraction. In this study, the optimum SWE conditions were solid water (0.12), bran rice ratio (8:92), time (45 min), particle size (420 µm), and the optimum SWE temperature was obtained at 120 Cº. SWE also could significantly enhance functional properties, such as the solubility, emulsifying activity index (EAI), and degree of hydrolysis of by-product of rice milling (BRM) PI. Conclusion: According to the positive impact of SWE on protein extraction and the functional properties of BRM PI, this method could be applied as a novel extraction technique to modify the properties of rice protein isolate for functional purposes in the future. However, more investigation is required to study the quantity and quality of the extracted valuable materials to scale it up for industrial means.

The Role of Transformational Leadership in Developing Innovative Work Behaviors: The Mediating Role of Employees’ Psychological Capital

Despite growing research on the significance of transformational leadership as a key contextual factor that determines innovative behavior, recent studies have not investigated the psychological mechanisms that link transformational leadership to employees’ innovative behavior thoroughly. Thus, the main purpose of this study was to examine the mediating role the four dimensions of psychological capital—self-efficacy, hope, resilience, and optimism—play in the relationship between transformational leadership and employees’ innovative work behavior. Data from 178 Iranian agriculture experts were collected and analyzed using structural equation modeling. The results indicated that transformational leadership was related to employees’ innovative work behavior directly and positively. Furthermore, the results showed that hope and self-efficacy partially mediated the relationship. This study fills a gap in the literature by clarifying the way the dimensions of psychological capital influence transformational leadership’s positive relationship to employees’ innovative work behavior in the public sector of developing countries. The results imply that to be innovatively effective, organizations need to manage both employees’ contextual (transformational leadership) and psychological (psychological capital) resources to enhance their innovative work behavior. The theoretical and practical implications were further discussed.

The effect of climate change on agricultural production in Iran.

The issue of climate change caused by global warming has become a major concern and challenge around the world, requiring comprehensive countermeasures. Agriculture is the most affected part of climate change and Iran's agriculture economy is at risk because of hot and dry and damages due global climate changes. This study investigates the effects of climatic variables temperature, such as precipitation, carbon and dioxide emission on total crop production in Iran from 1971 to 2020 using a fully modified conventional least squares econometric model (FMOLS). Chemical fertilizer and crop area variables, as well as fixed capital in agricultural have machinery, also been used as indicators of technology. The results showed that all variables had a significant effect on production. The average annual temperature and total annual rainfall its had an inverse U-shaped relationship with production, and were significant. Fertilizer and crop area variables had a positive effect, while CO2 had a negative relationship on total crop production in Iran. The findings of this study can be used to provide strategic plans for policymakers in the face of climate change. It is suggested that the government invest more in the mechanization of the agricultural sector and provide facilities and credits with priority given to farmers' education and the use of temperature-resistant varieties, and also act regionally against climate change.

The role of skill development in improving the performance of agricultural extension agents in Iran using structural equation modeling and grounded theory.

Performance improvement is the main concept of development policy. Belief in strengthening and improving the performance of individuals and institutions in developing countries for success in development policy has gradually formed among development agents. Performance improvement at the individual level pays attention to individual needs in order to enhance performance. Development requires developed and trained people. Therefore, the better the human resources as wealth and national capital are cultivated, the smoother the development path will be. The dimensions of improving performance at the individual level include things such as abilities, needs, attitudes, psychology, motivations, talents and skills, which also raises the need for skill development. In this regard, the current research seeks to investigate the relationship between skill development and performance improvement in extension in Iranian agriculture. The statistical population includes agricultural jihad centers in five regions of the country (the division of the country's provinces according to the Ministry of Agricultural Jihad, where each region includes 6 provinces) which is 8142 people, and accordingly, Cochran's formula was used to determine the sample size and the number of sample size 366 people were obtained. A structured questionnaire was developed to collect data. Structural equation modeling was used to examine the skill development measurement model, the performance improvement measurement model, and the skill development model. The research results show the significant relationship of all the indicators extracted from the interview in the structural equations.

Challenges Of Precision Agriculture Application In Pistachio Orchards: Factor Analysis From Iranian Agricultural Experts' Perspective

Iran's agriculture is globally well-known for its pistachio product. However, traditional management approaches and poor application of proper new technologies have brought reduced productivity and environmental hazards. In the information age, in order to transition from traditional to modern horticultural model, the application of precision agriculture model is appropriate. Therefore the purpose of the present study is to determine the challenges of precision agriculture application in pistachio orchards in Semnan province. The research method was survey. The statistical population were 187 horticultural experts of Semnan and counties' agricultural research center. By of Cochran formulae, 124 people were selected as sample. It was used a stratified random sampling method. In field study step, it was used the questionnaire as the main research tool. It was confirmed the face and content validity and reliability of research tool. The results of prioritizing the challenges of application of PA in pistachio orchards showed that the respondents’ point view, the lack of economic justification for PA from the point of view of gardeners in the area, fragmentation of lands and lack of integrated land management, lack of the technical infrastructure required for PA in orchards had the highest priority. Also, shortage of PA researches and the gap between research and extension, poor management of gardeners in the use of precision agricultural technologies, lack of providing consulting services to gardeners were identified as the least priority. Exploratory factor analysis results have demonstrated the exploitation of four factors, including investment and supportive, structural, human resource development and supply, finally organizational and program challenges.

Evaluation of Isfahan City Subsidence Rate Using InSAR and Artificial Intelligence

Iranian agriculture has not made significant progress in recent decades, and crops are grown using methods such as flood irrigation. Consumption of more than 90% of Iran's water is related to the agricultural sector, most of which is extracted from groundwater, which causes land subsidence (LS). In this study, Isfahan LS has been measured with 30 Sentinel-1 radar images by the Interferometric synthetic aperture radar (InSAR) method from 2020 to 2021. Convolutional neural network (CNN), whale optimization algorithm (WOA) and grey wolf optimization (GWO) are used for phase unwrapping. 3 leveling points in two months of 2020 have been measured to determine and validate the root-mean-square error (RMSE) of the proposed methods. As a result of applying the three phase unwrapping algorithms in the InSAR technique, it showed CNN has best accuracy, RMSE and worst time and GWO has best time. The maximum subsidence reaches more than 170 mm/year. The average of the whole study area of Isfahan has subsidence of 110.9 mm/year. Correlation of 3 piezometric well with subsidence of Isfahan city has more than 0.9.

Where do new scientific agricultural trends stand An investigation into the perceived educational needs of Iranian agriculture students

Where do new scientific agricultural trends stand An investigation into the perceived educational needs of Iranian agriculture students

Where do new scientific agricultural trends stand An investigation into the perceived educational needs of Iranian agriculture students

Where do new scientific agricultural trends stand An investigation into the perceived educational needs of Iranian agriculture students

The relationship between proactive personality and employees’ creativity: the mediating role of intrinsic motivation and creative self-efficacy

Employees’ creativity is one of the most important factors in the success of organizations which has attracted the attention of researchers in recent years. Recent research has suggested that proactive personality fosters creativity. However, there is a lack of research into the mechanisms that make this link possible. The main purpose of this study was to examine the relationship between proactive personality and employee creativity by focusing on the mediating roles of intrinsic motivation and creative self-efficacy. Data from 178 Iranian agriculture experts were collected and analyzed by conducting structural equation modeling. The results indicated that proactive personality was directly and positively related to employees’ creativity. Additionally, the results showed that intrinsic motivation and creative self-efficacy partially mediated the relationship between proactive personality and employees’ creativity. The findings not only shed light on mechanisms that underlie in the proactive personality -creativity linkage but they also highlight the importance of intrinsic motivation and creative self-efficacy in the linkage. Together, the study extends the effect of proactive personality on creativity and the mediation mechanisms underlying this relationship. The theoretical and practical implications, limitations, and future research directions are discussed.

The Effect of Yield Fluctuations and Production Risk on Pistachio Commercial Cultivars in Kerman Province

The required capital and liquidity for agricultural production are always a limiting factor in Iranian agriculture. Since, income is a combination of production and product price, one of the major problems of the country's pistachio industry is the high yield fluctuations and high price fluctuations. In the present study, the mean and yield fluctuations of four pistachio commercial cultivars (Kaleh-Ghoochi, Ahmad-Aghaei, Akbari, and Owhadi) were evaluated in the Anar and Rafsanjan orchards in Kerman province. The information used in this study was collected through a questionnaire from farmers. The orchards were selected by multi-stage random method. From the total number of villages in the two regions, some sites were selected based on random. Then, some farmers were selected randomly. By referring to the selected farmers, an orchard was selected from each cultivar. The number of studied orchards was 100 forms in each cultivar. To measure the yield per hectare, the amount of actual product that had achieved in the last six years. Finally, the mean and yield fluctuations of 4 pistachio commercial cultivars were analyzed. The results showed that the studied cultivars had a significant difference in the yield, profit net and coefficient variation at a probability level of 5%. The results indicated that the Ahmad-Aghaei cultivar was the best in average yield (1758.7 kg ha-1) and net profit per hectare (292530201 Rials ha-1) and then Akbari cultivar. However, performance fluctuations in the Owhadi cultivar (53.06%) was lower than the other three cultivars. Base on the results, the Kaleh-Ghoochi cultivar was minimum in average yield (1073.6 kg ha-1) and production fluctuations (73.14%) than the others. Therefore, if the aim is to minimize the income fluctuations of pistachio farmers, depending on the region, one of Ahmad-Aghaei or Akbari cultivars should be planted. It can be concluded that among commercial cultivars, prioritization and justification for planting and propagation were Ahmad-Aghaei, Akbari, Owhadi and Kaleh-Ghoochi, respectively.

Entrepreneurial opportunity recognition: an empirical study in Iranian agriculture sector

Entrepreneurial opportunity recognition: an empirical study in Iranian agriculture sector

Entrepreneurial opportunity recognition: an empirical study in Iranian agriculture sector

Entrepreneurial opportunity recognition: an empirical study in Iranian agriculture sector