Search Results (1,830)

Bananas underpin Uganda’s food security and rural economy, but productivity is declining due to emerging pests, diseases, and declining soil fertility. To address these challenges, hybrid stress-tolerant banana varieties (HBVs) have been developed and released, but their adoption remains uneven across the country. This study analyzes the spatial distribution and determinants of HBV adoption and intensity in Uganda, providing new insights to inform scaling strategies. A cross-sectional survey of 624 banana-farming households was conducted across 24 districts in both traditional and non-traditional banana-growing regions. Data were analyzed using descriptive statistics and a Tobit regression model to capture both the binary decision to adopt and the intensity of adoption, measured as the number of HBV mats planted. Results showed significant regional variation; adoption was highest in Northern Uganda (73.9%) and lowest in Central and Southwestern regions (≈24%). Education and land size positively influenced adoption, while reliance on planting materials from fellow farmers consistently reduced adoption intensity across all regions. Gender and household structure also shaped adoption patterns, with male and married farmers more likely to plant larger areas of HBVs. The findings highlight the need for regionally tailored interventions, including strengthening formal seed systems, enhancing farmer knowledge, and addressing gender gaps in technology access. Strengthening institutional seed channels and extension support can accelerate HBV scaling and contribute to resilient banana production in Uganda. Full article

Against the backdrop of the “dual carbon” strategy and digital rural development, examining the impact of farmers’ digital literacy on the adoption and efficiency of green agricultural technologies can provide micro-level evidence and actionable policy insights for advancing the green transformation of agriculture. Through a systematic literature review and thematic analysis of 52 eligible studies, this study identifies a significant triple role of digital literacy—as an enabler, a mediating mechanism, and a potential barrier—in the adoption of green agricultural technologies. While digital literacy significantly facilitates technology adoption, its positive effects are constrained by a “capacity gap” arising from limited digital skills, low literacy levels, and inadequate digital infrastructure. Technology adoption demonstrates distinct stratification: digital information and communication technologies (ICTs) exhibit high penetration but superficial utilization; green production technologies are largely limited by capital availability; and precision agriculture, intelligent systems, and blockchain applications remain primarily at the pilot or demonstration stage. Furthermore, the interaction between digital literacy and technology adoption enhances agricultural efficiency by reducing income disparities, fostering rural entrepreneurship, and improving green total factor productivity (GTFP). This review highlights the importance of targeted policies and further research to address the capacity gap, realize sustained efficiency gains, and promote digital empowerment as a pathway to sustainable agricultural transformation. Full article

This article reports on a comparative case study that examined the ground rules used to facilitate a dialogic space in two discrete and diverse research studies: Year 5 & 6 children learning to code with ScratchMaths as part of their mathematics programmes, and crop farmers in rural east Africa developing their practice through various communications. The intention was to see if there were common actions or principles important for the establishment of ground rules in dialogic spaces in general. Understanding the nature of dialogic space has become increasingly important in many areas of education. STEM subjects, particularly when integrated, frequently involve collaborative interaction, and utilise a dialogical approach. Some initial aspects of ground rules were collaboratively identified, with both studies then independently analysed to identify emerging themes related to these ground rules. Several key elements emerged: developing the processes for interaction and communication; developing trust between participants; developing respectful dialogue; teacher roles; and facilitating collaborative work and the co-construction of meaning. The comparative case study suggested that these were important for other education work when establishing dialogic space. Full article

Expanded and intensified agriculture is a major driver of habitat loss for endangered species such as the Oriental White Stork (Ciconia boyciana), making wildlife-friendly farming an increasingly important approach for reconciling biodiversity conservation with agricultural development. Building on a 2018 feasibility study in the Sanjiang Plain, this research employs a choice experiment to examine how preferences for Oriental White Stork-friendly farming have evolved among urban consumers and residents of stork habitats under expanding green consumption and increasing experience with environmentally friendly farming. The results reveal pronounced preference heterogeneity and persistent cognitive separation between wildlife conservation and agricultural production, particularly among urban consumers, despite a stable group being willing to pay a premium for stork-friendly products. Rural residents’ decisions remain largely economically driven, though younger farmers with prior experience in environmentally friendly practices show more positive attitudes. Significant urban–rural differences suggest policy complementarities, whereby price-oriented incentives may encourage price-sensitive farmers to adopt green agriculture, while intrinsically motivated farmers require support through an Oriental White Stork-oriented value chain. Overall, the findings demonstrate that Wildlife-Friendly Farming cannot be effectively promoted through a one-size-fits-all approach; instead, stratified, group-specific policy and market mechanisms are essential for aligning producer incentives with consumer demand and supporting the long-term viability of biodiversity-friendly agricultural systems. Full article

The increasing momentum of agricultural digital transformation and green development necessitates investigations into how farmers’ digital literacy influences their engagement in green production behaviours, which is critical for achieving the high-quality development of modern agriculture. Utilising primary survey data collected from farmers in rural areas of Guizhou Province, China, this study investigated how digital literacy affects farmers’ green production behaviours. The findings are as follows: (1) Digital literacy exerts a significant positive impact on farmers’ adoption of green production behaviours. Regarding the hierarchical effect, the order of influence is as follows: digital security awareness > basic digital skills > digital application and innovation. (2) The facilitating effect of digital literacy is primarily achieved through two pathways: the peer effect and the guidance effect. (3) Farmers with higher education levels are more impacted by digital literacy than farmers with lower education levels. (4) The impact of digital literacy is more positively significant for young and older farmers than for middle-aged groups. Based on these research findings, it is recommended that future policy formulation and technology extension efforts should prioritise support for specific regions and groups, such as mountainous areas, small-scale operations, low-education backgrounds, and the elderly. Such targeted approaches are crucial for encouraging wider adoption of green production behaviours among farmers. Full article

This study aimed to develop a credit risk index to classify coffee producers according to socioeconomic, agronomic, and financial performance variables, with the purpose of strengthening financial inclusion. We combined qualitative and quantitative methods to understand credit risk factors among smallholder coffee producers. The study followed a descriptive-analytical approach structured in consecutive methodological phases. The systematic review, conducted following the Kitchenham protocol, identified theoretical factors associated with credit risk, while fieldwork with 300 producers provided the socioeconomic and productive contexts of coffee-growing households. Producer income, cost of living, and farm management expenses were modeled using regression, statistical, and machine learning methods. Subsequently, these variables were integrated to construct a financial risk index, which was normalized using expert scoring. The index was validated using data from 100 additional producers, for whom annual repayment capacity and maximum loan amounts were estimated according to their risk level. The results indicated that incorporating municipal-level economic variables, such as estimated average prices, income, and expenses, enhanced predictive accuracy and improved the rational allocation of loan amounts. The study concludes that credit risk analysis based on variables related to human, productive, and economic capital constitutes an effective strategy for improving access to finance in rural areas. Full article

Promoting social participation is a core objective of digital inclusive development. Drawing on rural household survey data from five provinces in China and the Digital Governance Index developed by Peking University, this study systematically examines the impact of digital governance on rural households’ social participation deprivation. The benchmark regression results show that the effect of digital governance on rural households’ social participation deprivation follows an inverted U-shape, characterized by an initial increase followed by a subsequent decline. A series of robustness and endogeneity tests confirms the stability of these findings. Further heterogeneity analyses reveal pronounced regional differences. In the western region, the impact of digital governance on farmers’ social participation deprivation follows a U-shaped pattern, with deprivation initially decreasing and then increasing as digital governance deepens. By contrast, in the central and eastern regions, the inflection point of the inverted U-shaped relationship shifts further to the right relative to the full sample. Furthermore, digital governance exerts a significantly stronger mitigating effect on social participation deprivation among households experiencing higher levels of deprivation. Mechanism analysis shows that digital governance reduces farmers’ social participation deprivation by enhancing their perceived access to public services and improving their psychological well-being. However, moderation analysis shows that household-level digital exclusion and relative poverty significantly weaken these beneficial effects. Full article

Pear cultivation in Greece, with an annual production of approximately 81,000 tonnes, constitutes a significant segment of the national fruit industry, particularly in Northern regions such as Macedonia and Thessaly. Despite ranking 8th in the EU in terms of pear production, Greece’s cultivated area is slightly declining, and adoption of smart agriculture technologies (SAT) remains limited. In this context, the present study investigates the preferences, patterns, and barriers of SAT adoption within the Greek pear sector, aiming to lay the groundwork for more effective digital transformation in the agri-food domain. Using a structured interview-based survey, data were collected from 30 pear growers, revealing critical insights into the technological landscape of the sector. A central challenge that emerged was the insufficient internet connectivity in rural farming areas, highlighting the urgent need for improved digital infrastructure to support SAT deployment. Furthermore, the study emphasizes the importance of targeted education and awareness programs to bridge the digital knowledge gap among pear farmers. An especially notable finding concerns the role of the chosen tree training system in influencing SAT uptake: more than 50% of adopters utilize the palmette training system, suggesting a strong correlation between orchard design and technological readiness. Among the SAT categories, Data Analytics and Farm Management Software were the most widely adopted, a trend partly driven by attractive governmental subsidies of €30 per hectare. Importantly, all respondents who had implemented SAT (100%) reported a measurable increase in farm income, reinforcing the technologies’ impact on productivity and profitability. Foremost among the challenges encountered is the deficit in technical knowledge and training. In conclusion, this study offers a comprehensive overview of Greek pear producers’ perceptions, challenges, and emerging opportunities related to smart agriculture. Full article

Carbon farming represents a strategic approach to enhancing agricultural sustainability while reducing greenhouse gas (GHG) emissions. In Türkiye, agriculture accounted for approximately 14.9% of national GHG emissions in 2023, dominated by methane (CH₄) and nitrous oxide (N₂O). By increasing carbon storage in soils and vegetation, carbon farming can improve soil health, water retention, and climate resilience, thereby contributing to mitigation efforts and sustainable rural development. This study reviews and synthesizes international and national evidence on carbon farming mechanisms, practices, payment models, and adoption enablers and barriers, situating these insights within Türkiye’s agroecological and institutional context. The analysis draws on a systematic review of peer-reviewed literature, institutional reports, and policy documents published between 2015 and 2025. The findings indicate substantial mitigation potential from soil-based practices and livestock- and manure-related measures, yet limited uptake due to low awareness, capacity constraints, financial and administrative barriers, and regulatory gaps, highlighting the need for region-specific approaches. To support implementation and scaling, the study proposes a policy-oriented, regionally differentiated and digitally enabled MRV framework and an associated implementation pathway designed to reduce transaction costs, enhance farmer participation, and enable integration with emerging carbon market mechanisms. Full article

Amid escalating ecological degradation, social fragmentation, and rising mental health challenges—especially in rural and agricultural communities—there is an urgent need to reimagine systems that support both planetary and human flourishing. This viewpoint examines an emerging paradigm in agriculture that emphasizes the role of farmers’ inner development in fostering practices that enhance ecological health, community well-being, and a resilient food system. A key goal is to draw more academic attention to growing community calls for more holistic, relational, and spiritually grounded approaches to food systems as an important focus for ongoing research. Drawing on diverse case studies from Japan, India, and Europe, we examine how small-scale and natural farming initiatives are integrating inner development, universal human values, and ecological consciousness. These case studies were developed and/or refined through a program led by the Conscious Food Systems Alliance (CoFSA), an initiative of the United Nations Development Programme (UNDP) that seeks to integrate inner transformation with sustainable food systems change. The initiatives are intended as illustrative examples of how agriculture can transcend its conventional, anthropocentric role as a food production system to become a site for cultivating deeper self-awareness, spiritual connection, and regenerative relationships with nature. Participants in these cases reported significant shifts in mindset—from materialistic and extractive worldviews to more relational and value-driven orientations rooted in care, cooperation, and sustainability. Core practices such as mindfulness, experiential learning, and spiritual ecology helped reframe farming as a holistic process that nurtures both land and life. These exploratory case studies suggest that when farmers are supported in aligning with inner values and natural systems, they become empowered as agents of systemic change. By linking personal growth with planetary stewardship, these models offer pathways toward more integrated, life-affirming approaches to agriculture and future academic research. Full article

Background/Objectives: Birth preparedness and complication readiness (BPCR) is a cornerstone of maternal health strategies designed to minimize the “three delays” in seeking, reaching, and receiving skilled care. In Ethiopia, uptake of BPCR remains insufficient, and little evidence exists on how individual- and community-level factors interact to shape preparedness. This study assessed the determinants of BPCR among women of reproductive age in Hawela Lida district, Sidama Region. Methods: A community-based cross-sectional study was conducted among 3540 women using a multistage sampling technique. Data were analyzed with multilevel mixed-effect negative binomial regression to account for clustering at the community level. Adjusted prevalence ratios (APRs) with 95% confidence intervals (CIs) were reported to identify determinants of BPCR. Model fitness was assessed using Akaike’s Information Criterion (AIC), the Bayesian Information Criterion (BIC), and log-likelihood statistics. Results: At the individual level, women employed in government positions had over three times higher expected BPCR scores compared with farmers (AIRR = 3.11; 95% CI: 1.89–5.77). Women with planned pregnancies demonstrated higher BPCR preparedness (AIRR = 1.66; 95% CI: 1.15–3.22), as did those who participated in model family training (AIRR = 2.53; 95% CI: 1.76–4.99) and women exercising decision-making autonomy (AIRR = 2.34; 95% CI: 1.97–5.93). At the community level, residing in urban areas (AIRR = 2.78; 95% CI: 1.81–4.77) and in communities with higher women’s literacy (AIRR = 4.92; 95% CI: 2.32–8.48) was associated with higher expected BPCR scores. These findings indicate that both personal empowerment and supportive community contexts play pivotal roles in enhancing maternal birth preparedness and readiness for potential complications. Random-effects analysis showed that 19.4% of the variance in BPCR was attributable to kebele-level clustering (ICC = 0.194). The final multilevel model demonstrated superior fit (AIC = 2915.15, BIC = 3003.33, log-likelihood = −1402.44). Conclusions: Both individual- and community-level factors strongly influence BPCR practice in southern Ethiopia. Interventions should prioritize women’s empowerment and pregnancy planning, scale-up of model family training, and address structural barriers such as rural access and community literacy gaps. Targeted, multilevel strategies are essential to accelerate progress toward improving maternal preparedness and reducing maternal morbidity and mortality. Full article

As global agriculture seeks to reconcile the dual imperatives of food security and environmental sustainability, this study examines the role of Internet access in promoting green agricultural production, specifically by reducing fertilizer and pesticide use. Using a panel dataset from 16 rural fixed observation points in Henan Province from 2009 to 2022, we find that Internet access significantly lowers per-unit farmland expenditures on fertilizers and pesticides by 6.0% and 7.3%, respectively. Mechanism analysis reveals that these positive effects operate through three main channels: improved information accessibility delivers timely agricultural data and guides input decisions; enhanced technical learning efficiency reduces barriers to adopting green technologies; and stronger market connectivity via e-commerce platforms shortens supply chains and provides price incentives. Heterogeneity analysis further identifies more pronounced effects among farmers with higher human capital (higher education, better health, younger age), higher production capital (greater mechanization, larger farmland, stronger decision-making capacity), lower livelihood capital (lower income, lower consumption, less communication expenditure), and higher spatial capital (residing in urban suburbs, poverty registration villages, and traditional villages). This study provides micro evidence for digital technology to empower sustainable agricultural development and provides policy implications for building a sustainable agri-food system. Full article

Rural areas are currently facing a deepening “social-ecological divide,” where the fragmentation of natural, economic, and cultural data—often trapped in “data silos”—hinders effective systemic governance. To bridge this gap, in this study, the Rural Landscape Information Model (RLIM), an integrative framework designed to reconfigure rural connections through data fusion, process coordination, and performance feedback, is proposed. We validate the framework’s effectiveness through a comparative analysis of two distinct rural archetypes in China: the innovation-driven Yu Village and the heritage-conservation-oriented Hani Terraces. Our results reveal that digital technologies drive distinct empowerment pathways moderated by regional contexts: (1) In the data domain, heterogeneous resources were successfully integrated into the framework in both cases (achieving a Monitoring Coverage > 80%), yet served divergent strategic ends—comprehensive territorial management in Yu Village versus precision heritage monitoring in the Hani Terraces. (2) In the process domain, digital platforms restructured social interactions differently. Yu Village achieved high individual participation (Participation Rate ≈ 0.85) via mobile governance apps, whereas the Hani Terraces relied on cooperative-mediated engagement to bridge the digital divide for elderly farmers. (3) In the performance domain, the interventions yielded contrasting but positive economic-ecological outcomes. Yu Village realized a 25% growth in tourism revenue through “industrial transformation” (Ecology+), while the Hani Terraces achieved a 12% value enhancement by stabilizing traditional agricultural ecosystems (Culture+). This study contributes a verifiable theoretical model and a set of operational tools, demonstrating that digital technologies are not merely instrumental add-ons but catalysts for fostering resilient, collaborative, and context-specific rural socio-ecological systems, ultimately offering scalable governance strategies for sustainable rural revitalization in the digital era. Full article

The establishment of a young farmer in the rural economy is a key stage in the process of farm succession in the rural development environment. In this matter, Pillar II of the Common Agricultural Policy (CAP) has a distinct approach related to financing the initiatives of this establishment. A young farmer can obtain funds for their agricultural activity by submitting a funding project proposal to the national agency. The success of a funding project proposal depends on various factors. In this paper, a model of prediction and classification using supervised learning algorithms, primarily Random Forest (RF) and Logistic Regression (LR), was developed to predict project selection outcomes and identify the key determinants of success. This was developed in relation to proposals submitted in the period 2014–2021 through Sub-Measure 6.1 and through the intervention for the young farmer installation intervention under the 2023–2027 CAP Strategic Plan (DR-30 (2023–2027)—Young Farmer Installation, indicated in this paper as DR 30) for the period of 2023–2027. Using the historical data related to this proposal, several models that use automated learning were developed in order to predict the success of a proposal based on specific determinants. In addition, a classification model was used to determine patterns in the proposal data, obtaining several project proposal clusters with common characteristics. The variables and selection criteria with the greatest impact on the final score and probability of acceptance were identified, highlighting the differences between sub-measures and the implications for generational renewal policies in rural areas. The novelty of this study lies in the integration of predictive modeling, classification, and clustering within a unified, policy-oriented analytical framework applied to real administrative data. The results reveal that project selection outcomes are driven primarily by formal scoring components, while structural characteristics such as farm economic size and planned investment play a secondary but consistent role across programming periods. These findings provide actionable insights for refining selection criteria and advisory mechanisms under the Common Agricultural Policy. Full article

Digital twin technology is widely promoted as a transformative step for precision livestock farming, yet no fully realized, engineering-grade digital twins are deployed in commercial dairy or poultry systems today. This work establishes the current state of knowledge on dairy and poultry digital twins by synthesizing evidence through systematic database searches, thematic evidence mapping and critical analysis of validation gaps, carbon accounting and adoption barriers. Existing platforms are better described as near-digital-twin systems with partial sensing and modelling, digital-twin-inspired prototypes, simulation frameworks or decision-support tools that are often labelled as twins despite lacking continuous synchronization and closed-loop control. This distinction matters because the empirical foundation supporting many claims remains limited. Three critical gaps emerge: life-cycle carbon impacts of digital infrastructures are rarely quantified even as sustainability benefits are frequently asserted; field-validated improvements in feed efficiency, particularly in poultry feed conversion ratios, are scarce and inconsistent; and systematic reporting of failure rates, downtime and technology abandonment is almost absent, leaving uncertainties about long-term reliability. Adoption barriers persist across technical, economic and social dimensions, including rural connectivity limitations, sensor durability challenges, capital and operating costs, and farmer concerns regarding data rights, transparency and trust. Progress for cows and chickens will require rigorous validation in commercial environments, integration of mechanistic and statistical modelling, open and modular architectures and governance structures that support biological, economic and environmental accountability whilst ensuring that system intelligence is worth its material and energy cost. Full article