Search Results (3,088)

Food security and income generation remain a critical issue for small-scale farming households in Sub-Saharan Africa (SSA) due to population growth, climate change, and market instability. Indigenous leafy vegetables (ILVs) offer high nutritional value and have the capability to mitigate food insecurity but are underutilized due to social stigma. This review aims to systematically analyze the food and income contribution of cultivation and utilization of ILVs by small-scale farming households in Sub-Saharan Africa. This review analyses the literature on the role of ILV cultivation in enhancing food security and household income over the past two decades. A systematic search across five databases was conducted and identified 53 relevant studies. Findings indicate that ILVs contribute significantly to household nutrition and income through consumption and surplus sales. However, ILV cultivation faces barriers such as climate change, pest infestations, land degradation, water scarcity, insecure land tenure, limited agricultural training, poor communication networks, and restricted market access. Policy interventions are necessary to support small-scale farmers in ILV cultivation by providing agricultural extension services, promoting sustainable farming practices, and integrating ILVs into food security strategies. Further research should examine policy frameworks and supply chain mechanisms to enhance farmer participation and economic benefits from ILV production. Full article

Accurate classification of tomato ripening stages and quality estimation is pivotal for optimizing post-harvest management and ensuring market value. This study presents a rigorous comparative analysis of morphological and colorimetric features extracted via two state-of-the-art deep learning-based instance segmentation frameworks—Mask R-CNN and YOLOv8n-seg—and their efficacy in machine learning-driven ripening stage classification and quality prediction. Using 216 fresh-market tomato fruits across four defined ripening stages, we extracted 27 image-derived features per model, alongside 12 laboratory-measured physio-morphological traits. Multivariate analyses revealed that R-CNN features capture nuanced colorimetric and structural variations, while YOLOv8 emphasizes morphological characteristics. Machine learning classifiers trained with stratified 10-fold cross-validation achieved up to 95.3% F1-score when combining both feature sets, with R-CNN and YOLOv8 alone attaining 96.9% and 90.8% accuracy, respectively. These findings highlight a trade-off between the superior precision of R-CNN and the real-time scalability of YOLOv8. Our results demonstrate the potential of integrating complementary segmentation-derived features with laboratory metrics to enable robust, non-destructive phenotyping. This work advances the application of vision-based machine learning in precision agriculture, facilitating automated, scalable, and accurate monitoring of fruit maturity and quality. Full article

Global agricultural value chains (GVCs) face growing structural risks that threaten long-term sustainability, yet traditional methods often miss these systemic risks. Using complex network analysis and OECD data, this study examines the structural risks in China (Mainland China, Hong Kong, and Taiwan)’s agricultural GVC network from 2001 to 2020. By analyzing both supply and demand sides, we reveal a growing asymmetry in network risks and find that risk sources are shifting from direct trading partners to hidden, indirect ones. On the upstream demand side (imports), we observe that risks have turned into a strong reliance on a few core partners, creating a rigid structure that is difficult to change. In contrast, the downstream supply side (exports) exhibits high volatility, involving frequent shifts across uncertain new markets. These results suggest that agricultural security policies should shift from passive crisis response to active structural optimization. This study aims to provide a practical reference for China and other economies seeking to build a safer and more stable agricultural trade system. 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 temperate Himalayan states of Jammu and Kashmir, Himachal Pradesh, Uttarakhand, Ladakh, Sikkim, and Arunachal Pradesh in India face unique agro-ecological challenges across agriculture and allied sectors, including pest and disease pressures, inefficient resource use, post-harvest losses, and fragmented supply chains. This review systematically examines 21 critical problem areas, with three key challenges identified per sector across agriculture, agricultural engineering, fisheries, forestry, horticulture, sericulture, and animal husbandry. Artificial Intelligence (AI) and Machine Learning (ML) interventions, including computer vision, predictive modeling, Internet of Things (IoT)-based monitoring, robotics, and blockchain-enabled traceability, are evaluated for their regional applicability, pilot-level outcomes, and operational limitations under temperate Himalayan conditions. The analysis highlights that AI-enabled solutions demonstrate strong potential for early pest and disease detection, improved resource-use efficiency, ecosystem monitoring, and market integration. However, large-scale adoption remains constrained by limited digital infrastructure, data scarcity, high capital costs, low digital literacy, and fragmented institutional frameworks. The novelty of this review lies in its cross-sectoral synthesis of AI/ML applications tailored to the Himalayan context, combined with a sector-wise revenue-loss assessment to quantify economic impacts and guide prioritization. Based on the identified gaps, the review proposes feasible, context-aware strategies, including lightweight edge-AI models, localized data platforms, capacity-building initiatives, and policy-aligned implementation pathways. Collectively, these recommendations aim to enhance sustainability, resilience, and livelihood security across agriculture and allied sectors in the temperate Himalayan region. Full article

Agricultural marketing increasingly integrates Agriculture 4.0 technologies—Blockchain, AI/ML, IoT, and recommendation systems—yet systematic evaluations of computational maturity and deployment readiness remain limited. This Systematic Literature Review (SLR) examined 99 peer-reviewed studies (2019–2025) from Scopus, Web of Science, and IEEE Xplore following PRISMA protocols to assess algorithmic performance, evaluation methods, and Technology Readiness Levels (TRLs) for agricultural marketing applications. Hybrid recommendation systems dominate current research (28.3%), achieving accuracies of 80–92%, while blockchain implementations (15.2%) show fast transaction times (<2 s) but limited real-world adoption. Machine learning models using Random Forest, Gradient Boosting, and CNNs reach 85–95% predictive accuracy, and IoT systems report >95% data transmission reliability. However, 77.8% of technologies remain at validation stages (TRL ≤ 5), and only 3% demonstrate operational deployment beyond one year. The findings reveal an “efficiency paradox”: strong technical performance (75–97/100) contrasts with weak economic validation (≤20% include cost–benefit analysis). Most studies overlook temporal, geographic, and economic generalization, prioritizing computational metrics over implementation viability. This review highlights the persistent validation–deployment gap in digital agriculture, urging a shift toward multi-tier evaluation frameworks that include contextual, adoption, and impact validation under real deployment conditions. Full article

Bio-based fertilisers (BBFs) derived from waste streams represent a transformative approach to sustainable agriculture, addressing the dual challenges of waste management and food security. This comprehensive review examines recent advances in BBF production technologies, nutrient recovery mechanisms, soil health impacts, and the benefits of a circular economy. This review, based on an analysis of peer-reviewed studies, demonstrates that BBFs consistently improve the physical, chemical, and biological properties of soil while reducing environmental impacts by 15–45% compared to synthetic alternatives. Advanced biological treatment technologies, including anaerobic digestion, vermicomposting, and biochar production, achieve nutrient recovery efficiencies of 60–95% in diverse waste streams. Market analysis reveals a rapidly expanding sector projected to grow from $2.53 billion (2024) to $6.3 billion by 2032, driven by regulatory support and circular economy policies. Critical research gaps remain in standardisation, long-term performance evaluation, and integration with precision agriculture systems. Future developments should focus on AI-driven optimisation, climate-adaptive formulations, and nanobioconjugate technologies. Full article

This study analyzes the competitive asymmetries and trade effects of the proposed EU–Mercosur Trade Agreement on the European Union’s (EU) and Polish agri-food sectors. The comparative analysis reveals that Mercosur holds a significant structural advantage driven by substantially lower labor costs, cheaper agricultural land, and a climate permitting multiple harvests. This cost advantage is further compounded by weaker regulatory standards (e.g., on pesticides and antibiotics). This structural edge is most pronounced in high-volume commodities, leading to Mercosur trade surpluses in products such as soybeans, sugar cane, and wheat, which pose the primary competitive threats to the EU market. Conversely, the EU maintains an intensive advantage through superior yields in intensive farming (e.g., maize) and specialization in high-value, processed products. This creates quantifiable export opportunities for EU/Polish producers in sectors where Mercosur is a consistent net importer, notably other frozen vegetables, preserved tomatoes, and apples. The findings confirm an asymmetric effect of liberalization, which necessitates a dual strategy of internal structural reform (e.g., the EU Protein Strategy) and the implementation of external protective mechanisms, including strategic Common Agricultural Policy (CAP) adaptations and safeguard clauses, to maintain the long-term competitiveness and Supply Chain Resilience of European 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

Functional food plays an increasingly important role in shaping healthy dietary habits by integrating health-promoting components into consumers’ everyday diets and helping reduce food waste. Products developed using by-products and raw material streams from food processing can support the principles of the circular economy (CE) by improving resource efficiency and lowering the environmental footprint of the food system. In Poland, as in many countries worldwide, functional food is a rapidly growing category that can contribute to public health and serve as a driver of economic development. However, the excessive and scientifically unsupported use of the term “functional food” for marketing purposes may mislead consumers and weaken trust in this product group. From a CE perspective, transparent communication and informed consumer choices are essential, as they promote environmentally responsible behaviors and support sustainable production models. The aim of this study was to assess the level of knowledge about functional food among residents of Eastern Poland, which is a less industrialized and predominantly agricultural region. The analysis focused on awareness of health benefits, consumption frequency, consumer attitudes, and interest in educational initiatives promoting functional food within CE principles. The study also examined whether consumers associate functional food with sustainability-oriented practices. The findings offer insights for educational and marketing strategies grounded in scientific evidence and highlight the potential of functional food in building a sustainable, resource-efficient food system. Full article

High-quality development of agricultural enterprises is essential for China’s rural revitalization, yet the institutional conditions that support it remain poorly understood. Drawing on institutional logics and configuration theory, this study adopts a holistic systems perspective to examine how government, market, and social institutions interact to shape enterprise performance. Using provincial data (2013–2023) matched with firm-level data for 119 listed agricultural enterprises, we estimate total factor productivity as the core outcome and apply dynamic fuzzy-set Qualitative Comparative Analysis (dynamic fsQCA) to identify equifinal institutional pathways. The results reveal that high-quality development is an emergent property of complex institutional systems; instead, high-quality development emerges from several distinct configurations combining policy support, marketization, financial development, Agricultural Infrastructure Index, market stability, and urban–rural integration. Two contrasting configurations are associated with non-high-quality development, characterized by financial scarcity and infrastructure deficits or by fragmented policy support under weak regulation. Dynamic analysis further reveals clear temporal and spatial heterogeneity: some market–finance driven paths lose robustness over time, while policy–urbanization and regulation–infrastructure based configurations become increasingly stable. These findings extend institutional configuration research to the agricultural sector, demonstrate the value of dynamic fsQCA for capturing temporal effects, and offer differentiated policy implications for optimizing institutional environments to foster the high-quality development of agricultural enterprises. Full article

High-quality agricultural products from the Lambayeque region have contributed to the growth of Peru’s agro-export sector and increased international trade. However, the need for agricultural exports to be more resilient and sustainable is demonstrated by the fact that markets are still concentrated, logistical costs are high, and global demand is constantly shifting. The purpose of this study is to use a gravity-based trade model and market intelligence techniques to analyse the agricultural exports from the Lambayeque region between 2015 and 2024. Using official data from the World Bank, AZATRADE, CEPII, and MINCETUR, we employed a quantitative explanatory approach. The results show that the concentration of businesses has significantly decreased while the value of exports has increased steadily. The Herfindahl–Hirschman Index increased from 6209 in 2015 to 1349 in 2024, and export destinations have become slightly more diverse. Exports are negatively impacted by geographic distance, but free trade agreements greatly benefit them. There is a lot of export potential in markets like Finland, Indonesia, Austria, Bolivia, and Vietnam. However, Israel and Hong Kong appear to be full. Overall, the findings indicate that Lambayeque’s export performance has improved, but it still runs the risk of becoming overly focused on a single sector. Long-term sustainability of the region’s agricultural exports depends on enhancing logistical infrastructure, bolstering market intelligence, and promoting regional diversity. Full article

Financialisation has an increasing influence on the functioning of non-financial enterprises. It is therefore important to examine whether and to what extent food sector enterprises are subject to the process of financialisation. The research objective was to determine the level of financialisation of food industry enterprises in Poland in relation to the whole industry sector. To achieve this objective, the following research hypothesis was formulated: the process of financialisation of food industry enterprises proceeds similarly to the analogous process undergoing in industrial enterprises but varies across different sectors of the food industry. The research was conducted on the basis of statistical data from Statistics Poland (SP) published in various statistical studies. Financial data from 2010 to 2023 were analysed. For this purpose, research tools used in the paper are referred to in the literature as measures of the level of financialisation, so-called balance sheet indicators. The main limitation of the research is that the results can only be applied to countries with similar economic conditions, especially post-communist countries, and that balance sheet indicators are used to measure financialisation, which, although widely used, are limited in their effectiveness because they focus only on balance sheet data. The results support the research hypothesis. The companies in the analysed industries are characterised by a low level of financialisation. The process of financialisation of food industry companies is similar to the one in industrial companies and is more intense in beverage production than in other food industry sectors. There is room for a sustainable financing policy. The results indicate that there is room for higher financing of food industry enterprises in Poland, but excessive financing may lead to excessive concentration and monopolisation of enterprises and even to speculation on agricultural markets. To maintain financial stability, it will be important to pursue a stable monetary policy, limit the risk of food price volatility, improve communication and coordination in international monetary policy, and increase national food self-sufficiency. This study fills a research gap in understanding the process of financialisation, assessing its degree of advancement and diversity in the main sectors of food processing enterprises. Full article

This study investigates the weak-form efficiency of South Africa’s summer grain spot markets, focusing on white maize, yellow maize, sunflower, and soybean. Using daily log return data from 2007 to 2025, we apply autocorrelation, Portmanteau (Q), and heteroskedasticity-robust Lo–MacKinlay variance ratio tests, along with Bai–Perron structural break analysis, Pesaran–Timmermann directional accuracy tests, and mean return per trade calculations. Results reveal significant short-term serial dependence and mean-reverting behaviour across all commodities, indicating partial predictability and deviations from weak-form efficiency. Structural break analysis identifies multiple regimes within the price series, showing that market dynamics are not constant over time. Directional accuracy and MRP results indicate that while some predictability exists, the economic gains from exploiting past prices are small and likely insufficient to overcome trading frictions. These findings suggest that price adjustments are gradual rather than instantaneous, reflecting structural and operational market frictions such as limited liquidity, low adoption of electronic trading, and constrained transparency. Enhancing digital trading platforms, improving real-time price reporting, and investing in storage and logistics could strengthen price discovery and reduce transaction costs. The study provides insights into emerging agricultural markets and highlights the importance of considering market structure when evaluating efficiency. 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