International Journal of Agricultural Management and Development
Volume:13 Issue: 2, Jun 2023

Precision agriculture holds significant potential for increasing crop yield, reducing costs, and ensuring environmental protection. However, the adoption of these technologies is impeded by certain barriers that need to be acknowledged. This survey aimed to investigate the perceptions of agricultural experts (n=142) regarding the barriers to adopting precision agriculture in Ardabil province, Iran. Data were collected through a questionnaire administered to the participants. The research tool was validated by a group of university staff, and its reliability was confirmed through a pilot study involving 30 experts, which yielded a high alpha value. Due to the prevailing COVID-19 situation, data collection was conducted virtually. The findings indicated that the surveyed experts possessed a relatively good understanding of precision agriculture. Five factors, namely lack of knowledge, economic constraints, inadequate extension-farmer interactions, data security concerns, and limited accessibility, collectively accounted for 73.34 percent of the total variance in barriers to adopting precision agricultural technologies. Due to the lack of knowledge and poor farmer-extension interaction, extension courses are needed to improve farmers' knowledge and awareness of precision agriculture. Regarding the economic barriers, allocating the facilities and credits for developing and applying these technologies is necessary. Concerning the barriers to data security and lack of access, the government and related organizations should support farmers in solving internet access problems. Also, training and necessary facilities to maintain data security should be provided. Considering the effect of perception of usefulness on attitude, it is necessary to provide in-service training to improve experts' knowledge and perceptions about these technologies' usefulness. Precision agriculture demonstration farms in research stations or farmers' farms with the interaction of experts can be effective.

In recent years, global rice consumption has seen a substantial increase, and consumption is expected to continue rising due to its significance in household diets worldwide. However, successful rice processing requires specific operations. This study assessed the effectiveness of Japan International Cooperation Agency (JICA) Rice Processing Technologies Utilization among rice processors in Kogi State, Nigeria. A three-stage sampling technique was employed to select one hundred and eighty (180) rice processors for the study. Data collection utilized a questionnaire complemented with an interview schedule, and the analysis employed descriptive statistics (frequency counts, percentages, and mean). Results revealed that the majority (91.1%) of the respondents were female with a mean age of 47.6 years. Additionally, 86.7% were married, and 56.7% had primary education. It was also found that extension agents (72.2%) were the main sources of information on JICA rice processing technologies in the study area. Furthermore, the study found that all JICA initiatives were effective. However, the false bottom at parboiling for quality paddy rice (X̅ = 3.99) and the Ajifa mill for milling clean rice grains with a good appearance (X̅ = 3.98) were rated as the most effective JICA initiatives by the respondents. Consequently, the study recommends that the government should encourage and organize free adult literacy classes to increase processors' knowledge and orientation toward processing activities.

This study aims to assess the inequality in consumption among rural households in Iran and identify the contributing factors. Initially, we gauge consumption inequality using household income and expenditure statistics published by the Statistics Center of Iran in 2019. Subsequently, we analyze the impact of significant demographic factors within households, including gender, education, and the generational status of household heads, on consumption inequality. We accomplish this through Gini coefficient analysis and quantile regression. The analysis of the Gini coefficient reveals that age groups and the generational status of household heads provide a more effective representation of the observed inequality within the studied households compared to other demographic features. Employing quantile regression to investigate the asymmetric effects of the mentioned demographic factors on the distribution of households' per capita consumption indicates that various segments of consumption expenditure distribution exhibit asymmetric responses to these factors. Household income has a positive influence on the distribution of household consumption expenditures. However, its impact is 60% greater on the right side of the distribution than on the left side. In cases where the household head is female, per capita expenditures are reduced by one million and three hundred thousand Tomans. Notably, the sign of this coefficient consistently remains negative across different quantiles, albeit with varying magnitudes. Ultimately, households with higher education levels or belonging to older age categories demonstrate greater average per capita expenditures compared to households with lower education levels or younger household heads.

The present study aimed to design a model for developing entrepreneurial behavior in agricultural cooperatives in Kermanshah province, employing an exploratory mixed-method approach. In the qualitative phase of the study, the participant team included all key individuals well-informed about entrepreneurship within the cooperatives of Kermanshah province. Thirty participants were selected using a snowball purposive sampling method. The statistical population for the quantitative phase included 530 managers and members of active agricultural cooperatives in Kermanshah province. Among them, 223 were selected using the stratified sampling method and Krejcie and Morgan's table. Data collected during the qualitative phase were analyzed using Nvivo8 software, resulting in the development of a grounded theory in the form of a conceptual model. During model analysis, research hypotheses were initially compiled and then assessed using the path analysis method in SPSS 23 and SmartPLS3 software. The findings from the qualitative phase, based on the grounded theory model, were categorized into six groups: Causative conditions (e.g., economic profits, personal incentives, etc.)Contextual conditions (e.g., cultural factors, diverse working areas, etc.)Intervening conditions (e.g., sanctions, market fluctuations, etc.)Phenomena (e.g., entrepreneurial behavior such as innovation, initiative in job tasks, etc.)Strategies (e.g., educational-promotional activities, keeping cooperatives up to date, etc.)Consequences (e.g., self-sufficiency in production, preventing cooperatives from depression, etc.).In the quantitative phase, the model emerging from the qualitative part was tested and ultimately approved. Based on the results, it is recommended that to foster entrepreneurial behavior in agricultural cooperatives, the research model be presented to cooperative members through training classes.

The aim of this study was to feasibility study of tourism entrepreneurship development in rural areas of Darreh-Shahr County in order to provide appropriate strategies for its development. The present study was conducted on a mixed (qualitative + quantitative) approach of a sequential exploratory type. Using purposeful and network sampling, 15 key informants in entrepreneurship and tourism participated in deep interview until saturation was reached. Qualitative data was analyzed using SWOT analysis and quantitative data was analyzed using Analytical Hierarchy Process (AHP). Results revealed that conservative and aggressive strategies are needed to develop tourism entrepreneurship in rural areas of Darreh-Shahr County. The AHP analysis revealed that aggressive strategy such as “exhibitions, and local markets for rural and nomads production” and conservative strategies such as “providing long term low interest loans for the development of infrastructural facilities for rural entrepreneurial tourism along” and “attracting local investors for establishing recreational facilities such as parks” is needed for the development of tourism entrepreneurship in rural areas of Darreh-Shahr county.

Imports and exports in all countries play an important role in economic growth. Therefore, choosing the right products will increase the country's competitiveness in world trade. Saffron is one of the most important and distinctive non-oil products of Iran for export. The purpose of this study is to predict the export of saffron through three machine learning algorithms and select a proper algorithm for predicting. The sample period of the forecasting models includes the data of Iran Saffron export from 2012 to 2019 which have been collected from the Iran Saffron Association. After performing the data preparation steps, the saffron export prediction was performed using three data mining algorithms including artificial neural network, deep learning, and gradient boost tree. To choose a better forecasting model, the validity of the model plays an essential role. Predictive validity of three designed models, using Absolute Error (Artificial neural network = 0.036, Network deep learning = 0.031, Gradiant boost tree = 0.047), R-squared (Artificial neural network = 0.045, Network deep learning = 0.044, Gradiant boost tree = 0.073) and Correlation (Artificial neural network = 0.95, Network deep learning = 0.98, Gradiant boost tree = 0.97) were measured. Based on the findings, all of these three designed models are accurate and their prediction error is very low and close to each other. However, with insignificant differences, the deep learning network has less error. The results could be useful for more accurate planning of saffron exports.