No 1/2023, January

Impact of Rural Out-Migration on Agricultural Technology Adoption of Rural Households in Southern Ethiopia


Using the new economics labor migration theory as a theoretical framework and the multinomial treatment effects negative binomial regression as an analytical model in southern Ethiopia, this study investigated the effects of rural out-migration on the intensity of agricultural technology adoption. In the year 2021, data were collected from 415 sample houses using stratified random sampling. Regression analysis showed that while the influence of migration from rural to urban areas is negligible, participation in international migration greatly increases the likelihood of technology adoption in rural families by 38.9%. The intensity of agricultural technology adoption by rural households is negatively and significantly correlated with male-headed households and household age, while the frequency of extension visits, non-farm participation, saving, membership in cooperatives, sales of livestock, and tropical livestock unit are positively and significantly related to the intensity of agricultural technology adoption. The outcome is consistent with the labor migration theory's risk and credit hypotheses. To encourage the adoption of agricultural technology and stop the recent surge of rural out-migration in southern Ethiopia, policymakers should provide access to capital, public services, and viable off-farm employment in rural areas.

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The Relationship Between Digital Performance and Production of Greenhouse Gas Emissions in EU Countries: Correlation Analysis and ANOVA Method


Agricultural activities produce the significant amounts of greenhouse gas emission. The importance of an ever-changing climate means that digital technologies and their environmental impact are more frequently discussed in the context of the 5th Industrial Revolution. It is important to minimize environmental threats and reduce production waste on the way to a sustainable path. The main scientific aim of the paper is to examine, based on correlation analysis and ANOVA method, the relationship between two variables, digital performance of individual EU countries expressed by the indicator Digital Economy and Society Index and production of Greenhouse Gas Emissions, specifically how digital technologies affect the environment and how to transform digital technologies to supporting the European Green Deal and accelerate sustainable growth. The reasons are that digital technologies can play an important role in reducing greenhouse gas emissions. According to the results, it has been proven that exists a positive correlation between two variables regarding as a weak correlation between DESI and GHG emissions. Analysis of variance indicates the highly significant differences between variables. Countries with the higher DESI index produce more Greenhouse gas emissions as well but in a weak manner.

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The Effect of Foreign Direct Investment and Trade Openness on Economic Growth: Evidence from Five African Countries


Through some empirical studies, the flow of FDI and trade openness have proven to support economic growth in developing countries. This paper examines the significance of FDI and trade openness in five African countries (Ghana, Morocco, Kenya, Uganda, and Zambia). The study employed the panel data analysis method using data from the World Bank for the period 1994-2019 for the five selected countries. The result from the Random effect model indicated that FDI positively supports growth, whereas trade openness harms economic growth in these countries. The outcome further revealed that Uganda enjoys more significance than the other countries using the countries' dummies through the pooled model estimation. We recommend that various governments focus more on exports, reduce imports, attract more FDI through incentives, and create a regulatory environment that is friendly to FDI.

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Development of Organic Production in Ukraine: Potential, Current Threats and Consequences for Global Food Security


The article aims to analyze the potential of organic production in Ukraine in war conditions and determine its consequences for world food security. Methodological approaches based on cluster and rating analysis of regions based on their potential in the field of organic production are proposed and provide an appropriate evaluation algorithm, mathematical tools, and strategic alternatives for all variants of data obtained in the calculation process. With the help of the given methodological approaches, the development of strategies for organic production for the primary clustering of regions, namely in Kyiv, Odesa, and Cherkasy oblasts, is proved. The system of forming a regional model of organically oriented multidisciplinary agriculture is appropriate for these regions. This will create the preconditions for organic food production, organic livestock, and related sectors of environmentally oriented economic activities. The development of an innovative component for implementing SMART-specialization projects is possible. It is substantiated that the most affected regions (Kharkiv, Luhansk, Donetsk, Kherson, Mykolaiv, Zaporizhia) from hostilities and occupation are potential for organic production and have significant areas for agricultural production. It is projected that the other war in Ukraine will reduce the production of farm products, including organic, which will lead to food security in most countries.

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Developing an Efficient System with Mask R-CNN for Agricultural Applications


In order to meet the world's demand for food production, farmers and producers have improved and increased their agricultural production capabilities, leading to a profit acceleration in the field. However, this growth has also caused significant environmental damage due to the widespread use of herbicides. Weeds competing with crops result in lower crop yields and a 30% increase in losses. To rationalize the use of these herbicides, it would be more effective to detect the presence of weeds before application, allowing for the selection of the appropriate herbicide and application only in areas where weeds are present. The focus of this paper is to define a pipeline for detecting weeds in images through the use of a Mask R-CNN-based weed classification and segmentation module. The model was initially trained locally on our machine, but limitations and issues with training time prompted the team to switch to cloud solutions for training.

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Sensor Data Gathering for Innovative Climatic System for Effective Water and Nutrient Management


Climate change is having a major impact on various sectors such as agriculture and water management due to changes in the distribution of rainfall. Mitigation of climate change impacts can be achieved through early detection of these changes by monitoring systems and the adoption of appropriate adaptation measures. One of the main goals is to design and develop a next generation monitoring and alerting system to support the optimization of water and soil nutrient management in agricultural domain. Sensors and sensor data management play an important in this kind of monitoring systems. A complete sensor data chain was developed based on modern wireless sensor networks and IoT technologies that covers the data gathering up to the data publication by interoperable interfaces. The monitoring system was tested on vineyards in pilot localities in Czech Republic and in Argentina.

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What is Inside the Bottle? - Factors Influencing Pálinka Consumption


Pálinka is the national spirit of Hungary and is in possession of the geographical indication of the European Union, but it used to be listed as a poor-quality product for a long time. The turnaround in this field began in the early 2000s. The aim of this study is to analyse the behaviour and attitudes regarding the purchase and consumption of pálinka and, to assess the product-related awareness of Hungarian consumers who like this particular spirit. Based on the literature, the knowledge of Hungarian consumers about pálinka is rather low, which is confirmed by the results of our questionnaire survey of 1,000 people. Furthermore, based on the results obtained, participants in the pálinka sector are more likely to understand how important certain product attributes that are perceived by consumers when purchasing pálinka. In order to increase the awareness of the spirit, it is essential to get to know the consumers, which can be followed by a well-positioned marketing strategy from both the government and corporate side.

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The Context Relevance of ICT, Freshwater Management Activity and Sustainability Goal: A Proposed Encapsulated Conceptual Framework


This study proposes an Encapsulated Conceptual Framework (ECF) for understanding the links between Information and Communication Technologies (ICTs), water resource management activities, and Sustainable Development Goals (SDGs). The study aims to contribute to national, regional, and global debates on the potential of ICTs in achieving sustainability goals. A combination of two socio-technical theories - Relevance Theory (RT) and Technology Acceptance Model (TAM) was adopted to inform the study. The literature review further informed the construction of the ECF. The framework testing involved sampling participants and collecting and analyzing the data. A sample of 251 (n = 251) individuals from formal and informal water user groups on the Tanzanian side of the Lake Victoria Basin participated in testing the framework. The study adopted the cross-sectional design to a mixed research approach. Furthermore, it used three quantitative and qualitative data collection techniques: Focus Group Discussions (FGDs), Key Informant Interviews (KIIs), and Questionnaire Administration (QA). Each FGDs session accommodated a group of participants with 9 – 12 members across the selected sites. KIIs targeted groups network leaders, water resource managers at various levels, and other individuals with potential information. Gathered dataset was cleaned, summarized, and analyzed using descriptive, correlation, and content analytical methods. The study capitalized on the strength of Tableau and R statistics to produce the visualizations that support the descriptive analysis of the data. Furthermore, the study used R and MS Excel software to establish the relationships among the variables. Results indicated the prominent use of mobile as ICTs for freshwater management activities. Furthermore, mobile-based tools such as SMS, voice call, image and video supported these activities to attain some indicators of SDGs related to water resource management. The study concludes that the framework contributes to understanding the contextual issues on ICT, freshwater management and SDGs.

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Factors Influencing the Prices of Rice, Maize and Wheat Prices in Nigeria


This study examines the impact of agricultural Gross Domestic Product (GDP) and imports on Nigeria’s food commodity prices using annual data from 1981 to 2018. Data obtained were analysed using the unit root test, cointegration test and Autoregressive Distributed Lag (ARDL) model to evaluate the long-run and short-run effects of the hypothesized variables on the food commodity prices. The results reveal that maize import value and exchange rate significantly affect the price of maize in the short-run. In contrast, the lagged price of maize, maize output and the past value of maize imports are the factors that influenced the current price of maize within the review period. Also, the lagged price of rice, rice output and the lagged value of rice imported in the immediate year exerted significant influences on the price of rice in Nigeria. Furthermore, the study indicates that the lagged price of wheat, the import value of wheat and the lagged wheat import value were statistically significant in influencing wheat price in Nigeria. Hence, policies for flexibility in the harmonization of exchange rate movements strengthen domestic agricultural performance.

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Consumers’ Preference and Future Consideration Toward Organic Instant Noodles: Evidence from Indonesia


The consumption of instant noodles in Indonesia is the second highest globally. However, people are now more aware of sustainable lifestyles and the health risks of consuming food additives, so some opt for more organic choices, including instant noodles. Research on customers’ preferences in this area remains lacking, so the current study aims to fill the gap. This study also analyses the relationship between the choices and consumers’ future considerations. Discrete Choice Experiment (DCE) method was used to reveal the perception of sustainable attributes in organic instant noodles. The future considerations were measured using the Future Consequences Consideration (FCC) scale. As many as 592 respondents participated in the study, selected using the convenience sampling method. Data were analyzed using conditional logit via package support.CEs on R software. The findings show that Indonesian consumers’ preferences are primarily based on the extrinsic attributes: organic labels and packaging materials, but they also consider the health claims. They will likely prefer instant noodles with organic characteristics for future considerations. The results of this study have implications for instant noodle product development. Young consumers take up a large portion of the market, and they are now more aware of sustainability and health. The current study can inform the product development and the approach to the targeted market. To the best of the authors’ knowledge, this is the first study on consumer perception on sustainability attributes in organic instant noodles.

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