Search Results (155)

To address the growing demand for sustainable materials in advanced manufacturing, the objective of this study was to develop and characterize a novel 3D-printable biocomposite using ruminant-digested corn stover (DCS) as a reinforcement for polylactic acid (PLA). The methodology involved systematically optimizing DCS particle size (80–140 mesh) and loading concentration (5–20 wt.%), followed by fabricating composite filaments via melt extrusion and 3D printing test specimens. The resulting materials were comprehensively characterized for their morphological, physical, and mechanical properties. The optimal formulation, achieved with 120-mesh particles at 15 wt.% loading, exhibited a 15.6% increase in tensile strength to 64.17 MPa and a 21.1% enhancement in flexural modulus to 4.19 GPa compared to neat PLA. In addition to the mechanical improvements, the biocomposite offers an advantageous density reduction, enabling the fabrication of lightweight structures for resource-efficient applications. Comprehensive characterization revealed effective interfacial integration and uniform fiber dispersion, validating biological preprocessing as a viable method for unlocking the reinforcement potential of this abundant biomass. While the composite exhibits characteristic trade-offs, such as reduced impact strength, the overall performance profile makes it a promising candidate for structural applications in sustainable manufacturing. This research establishes a viable pathway for agricultural waste valorization, demonstrating that biological preprocessing can convert agricultural residues into value-added engineering materials for the circular bioeconomy. Full article

The effects of changes in China’s final demand structure on its forestry sector and associated supply chains have not been thoroughly examined. This study aims to provide a detailed analysis of the quantitative relationships and underlying mechanisms between these interactive changes. Using China’s 153-sector input–output tables from the National Bureau of Statistics and applying a Leontief-based input–output model, we conducted scenario simulations through three distinct schemes, generating both quantitative and qualitative results. Our findings indicate that (1) For China’s forestry sector and its entire value chain to thrive, policymakers should boost consumer demand. This can better stimulate the development of forestry and the “agriculture-forestry-animal husbandry-fishery services” sector and related service industries; (2) Increased investment demand effectively stimulates the development of tertiary industries and secondary industries within the forestry supply chain and boosts the demand and production of intermediate products; (3) Changes in net exports have a significant impact on forestry and the forestry industry chain. To reduce dependence on foreign timber resources, China should strategically expand commercial plantation development; (4) Regarding intermediate product production, investment has a more pronounced effect on increasing total volume compared to consumption. Additionally, the Sino–US tariff disputes negatively impact the forestry industries of both countries. China needs to accelerate import substitution strategies for timber products, adjust international trade markets, and expand domestic consumption and investment to ensure the healthy and stable development of its forestry sector. Full article

The agricultural products trade network is essentially a complex adaptive system formed by nonlinear interactions between countries. Based on the complex system theory, this study reveals the dynamic self-organization law of the RCEP regional agricultural products trade network by using the panel data of RCEP agricultural products export trade from 2000 to 2023, combining social network analysis (SNA) and the temporal exponential random graph model (TERGM). The results show the following: (1) The RCEP agricultural products trade network presents a “core-edge” hierarchical structure, with China as the core hub to drive regional resource integration and ASEAN countries developing into secondary core nodes to deepen collaborative dependence. (2) The “China-ASEAN-Japan-Korea “riangle trade structure is formed under the RCEP framework, and the network has the characteristics of a “small world”. The leading mode of South–South trade promotes the regional economic order to shift from the traditional vertical division of labor to multiple coordination. (3) The evolution of trade network system is driven by multiple factors: endogenous reciprocity and network expansion are the core structural driving forces; synergistic optimization of supply and demand matching between economic and financial development to promote system upgrading; geographical proximity and cultural convergence effectively reduce transaction costs and enhance system connectivity, but geographical distance is still the key system constraint that restricts the integration of marginal countries. This study provides a systematic and scientific analytical framework for understanding the resilience mechanism and structural evolution of regional agricultural trade networks under global shocks. Full article

This paper examines how demographic characteristics, institutional structures, and livelihood strategies shape household resilience to climate variability and drought in West Pokot County, one of Kenya’s most climate-vulnerable arid and semi-arid lands (ASALs). Using a mixed-methods approach, it combines household survey data with three statistical techniques: Multinomial Logistic Regression (MLR) assesses the influence of gender, age, and education on livestock ownership and livelihood choices; Multiple Correspondence Analysis (MCA) reveals patterns in institutional access and adaptive practices; and Stepwise Linear Regression (SLR) quantifies the relationship between resilience strategies and agricultural productivity. Findings show that demographic factors, particularly gender and education, along with access to veterinary services, drought-tolerant inputs, and community-based organizations, significantly shape resilience. However, trade-offs exist: strategies improving livestock productivity may reduce crop yields due to resource and labor competition. This study recommends targeted interventions, including gender-responsive extension services, integration of indigenous and scientific knowledge, improved infrastructure, and participatory governance. These measures are vital for strengthening resilience not only in West Pokot but also in other drought-prone ASAL regions across sub-Saharan Africa. Full article

With the growth of international trade, concerns over the safety of imported agricultural products in South Korea have intensified due to factors such as the COVID-19 pandemic, radiation contamination risks, and the prevalence of GMOs. In response, this study develops two composite indices—the Agricultural Product Safety Index (APSI) and the Imported Food Safety Index (IFSI)—to quantitatively assess food safety risks across major exporting countries and apply them to Korea’s import structure. The indices integrate production and distribution risk indicators based on publicly available data and adhere to five key principles, including applicability, reliability, boundedness, independence, and representativeness. Empirical results from 2014 to 2021 indicate that Australia consistently demonstrates the highest food safety level, followed by the United States, Argentina, Ukraine, and Brazil. While the indices provide a structured and transparent framework for monitoring import-related safety, their scope is limited to selected countries and excludes biological hazards due to data limitations. Future research should expand the geographical coverage and incorporate empirical validation techniques. These findings contribute to the development of evidence-based policy instruments aimed at enhancing food safety governance in global supply chains. Full article

Inefficient agricultural water use is a significant factor exacerbating global water scarcity. Water rights trading (WRT) offers a new governance paradigm to address this issue. Initiated by China in 2014, the WRT policy provides a case for researching formal water markets in developing countries. This paper uses a sample of 30 Chinese provinces from 2007 to 2022 and employs the difference-in-differences method to evaluate the impact of WRT on agricultural water use efficiency (AWUE). The findings suggest that AWUE in pilot areas increased by an average of 48.1% compared to non-pilot areas. Heterogeneity analysis reveals a stronger WRT impact on AWUE in regions with developed markets, abundant water, and high agricultural dependence. Subsequent analysis identifies that WRT enhances AWUE mainly by incentivizing water-saving innovation, promoting cross-industry factor mobility, and optimizing crop structures. This study thus offers empirical evidence supporting China’s water marketization reform and explores WRT policy as a pathway to enhance AWUE. Full article

This study presents an integrated approach to sustainable soil and crop management by evaluating the individual and combined effects of cow manure (CM), rice husk biochar (RHB), and potassium humate (KH)—three underutilized, low-cost organic amendments derived from agricultural byproducts. Uniquely, it investigates how these amendments simultaneously affect soil physical and chemical properties, plant growth, and the accumulation of bioactive compounds in sunflower sprouts, thereby linking soil health to crop nutritional quality. The application of 2% w/w KH alone resulted in the greatest increases in macroaggregation (+0.51), soil pH (from 6.8 to 8.6), and electrical conductivity (+298%). The combination of 1% w/w CM and 2% KH led to the highest increases in soil organic carbon (OC, +62.9%) and soil respiration (+56.4%). Nitrate and available phosphorus (P) peaked with 3% w/w RHB + 2% KH (+120%) and 1% w/w CM + 0.5% KH (+35.5%), respectively. For plant traits, 0.5% w/w KH increased the total leaf area by 61.9%, while 1% w/w CM enhanced shoot and root biomass by 60.8% and 79.0%, respectively. In contrast, 2% w/w KH reduced chlorophyll content (−43.6%). Regarding bioactive compounds, the highest total phenolic content (TPC) was observed with 1% w/w KH (+21.9%), while the strongest DPPH antioxidant activity was found under 1% w/w CM + 1% w/w KH (+72.6%). A correlation analysis revealed that biomass production and secondary metabolite accumulation are shaped by trade-offs arising from resource allocation under stress or nutrient limitations. Potassium, P, soil microbial respiration, and OC emerged as key integrators connecting soil structure, fertility, and plant metabolic responses. Overall, the combination of 1% w/w CM with 0.5–1% w/w KH proved to be the most effective strategy under the tested conditions. Full article

Background: The Port of Santa Marta, located on Colombia’s northern Caribbean coast, plays a vital role in the country’s maritime trade, particularly in the export of agricultural and perishable goods. This raises the question: how competitive is Santa Marta’s container terminal compared to national and regional ports, and what strategic factors shape its performance within the Colombia and Latin American maritime logistics system? Methods: This study evaluates the port’s competitiveness by applying Porter’s Extended Diamond Model. A mixed-methods ap-proach was employed, combining structured surveys and interviews with port stakeholders and operational data analysis. A competitiveness matrix was developed and examined using standardized residuals and L1 regression to identify critical performance gaps and strengths. Results: The analysis reveals several competitive advantages, including the port’s strategic location, natural deep-water access, and advanced infrastructure for refrigerated cargo. It also benefits from skilled labour and proximity to global shipping routes, such as the Panama Canal. Nonetheless, challenges remain in storage capacity, limited road connectivity, and insufficient public investment in hinterland infrastructure. Conclusions: While the Port of Santa Marta shows strong maritime capabilities and spe-cialized services, addressing its land-side and institutional constraints is essential for positioning it as a resilient, competitive logistics hub in the Latin American and Caribbean region. Full article

The present study investigates Vietnam’s economic structural transformation from 2007 to 2023, identifying key sectors contributing to output growth and poverty reduction. The study is situated within the broader context of industrialization and sustainable development in emerging economies. It employs structural decomposition analysis using Vietnam’s national input–output tables for the years 2007, 2011, 2015, 2019, and 2023. The analysis decomposes changes in total output into technical effects and final demand effects, allowing for an evaluation of the relative contributions of sectoral productivity and demand side factors. The findings of the study indicate that the manufacturing and services sectors have been the primary drivers of economic growth, with the electrical and optical equipment, food, beverages and tobacco, and basic metals sectors demonstrating particularly strong performance. The factor of final demand, which is derived from consumption, investment, and exports, has played a dominant role in driving output. Notably, export-led manufacturing has experienced significant benefits due to Vietnam’s engagement in free trade agreements. It is noteworthy that the agriculture sector demonstrated a period of recovery between 2019 and 2023, driven by an increase in final demand. This study underscores the pivotal function of sectoral adaptability, trade openness, and strategic policy in maintaining inclusive economic development. It is evident that the phenomenon under scrutiny is not only indicative of vulnerabilities and opportunities but also shaped by global shocks, for example, the coronavirus pandemic. Full article

In this study, the relationship between economic growth and carbon emissions for the period 1968–2022 in Turkey was evaluated within the framework of the EKC (Environmental Kuznets Curve) hypothesis. In addition, the impacts of renewable energy consumption and agricultural value added on carbon emissions were analyzed using the ARDL bounds testing approach. The validity of the results was also tested using the FMOLS and DOLS methods. The findings confirmed the existence of a cointegration relationship between carbon emissions and per capita income, renewable energy consumption, and agricultural value added. Long-term analyses indicate that renewable energy consumption reduces carbon emissions, whereas growth in agricultural value added leads to an increase in emissions. In addition, it has been determined that the EKC hypothesis is valid in both the long and short terms and that increases in per capita income raise emissions up to a certain threshold and have a mitigating effect when this threshold is exceeded. The results of the short-term analysis showed that the effects of renewable energy consumption vary across periods, and that agricultural value added increases emissions in the short term. This study provides empirical evidence for Turkey by incorporating sectoral variables within the EKC framework and offers meaningful insights for policymakers regarding the environmental impacts of agricultural value added and renewable energy use in the context of a developing country. Accordingly, fiscal policy instruments such as green taxation, carbon credit trading mechanisms, and financial and agricultural subsidies should be more effectively utilized in Turkey to support structural transformation in agriculture and promote the use of clean energy, in line with the findings that suggest the need for targeted agricultural and energy policies aligned with Turkey’s SDG commitments. Full article

This study conducts a macro-level comparative analysis of the eco-efficiency in the agricultural sectors of the European Union (EU) member states and Türkiye from 2003 to 2022. By treating countries as decision-making units, this research offers a holistic overview of how national-level inputs and outputs shape the aggregate performance, focusing on the trade-offs between economic value generation and environmental pressures. An input-oriented Data Envelopment Analysis (DEA) model, based on Variable Returns to Scale (VRS), was employed. The model employs three inputs—compensation of employees (COE), energy consumption (EC), and gross fixed capital formation (GFC)—and two outputs—agricultural gross domestic product (GDP) and GHG emissions (GGEs). All variables were normalized by agricultural land area per country to account for scale differences. The findings reveal significant disparities in the eco-efficiency across countries and over time. Notably, Türkiye consistently demonstrated a high performance, frequently serving as a benchmark. In contrast, several Eastern European countries exhibited lower scores, suggesting significant room for structural improvement at the national level. The results point to the considerable potential for reducing energy and labor inputs in many countries. Instead of offering specific policy prescriptions, this study provides a diagnostic tool that identifies national-level performance gaps, informs policy discussions on resource allocation, and highlights priority areas for more detailed investigation. Full article

Concentration within the food industry is a desirable process in the context of improving economic efficiency, which is the basis for building sustainable competitive advantages in internationalisation and globalisation. Excessive concentration of market structures can generate negative externalities that threaten sustainability in the long term. Maintaining a balance between the freedom of economic activities and the protection of consumers and environmental interests is fundamental to the stability of the entire economy and its position in the international market, which is a priority of the EU-MERCOSUR trade agreement. The aim of this article was to assess the process of concentration of the Polish food industry and its impact on factor efficiency in the context of changing external conditions. In order to do so, the Cobb–Douglas production function was used. The research results showed that there is a progressive concentration in the food industry. Changes in the entity structure are taking place in an evolutionary way, as illustrated by the still high fragmentation of companies. Large companies make good use of economies of scale, which is mirrored in their high efficiency. The structure of the Polish food industry makes it possible to realise the objectives of agricultural policy, including in terms of sustainable development and improvement of competitiveness on the global market. Taking into account the current entity structure of the Polish food industry, it will be crucial for the long-term sustainability to take into account contemporary economic, environmental and social issues in the EU-MERCOSUR trade agreement. Full article

The increasing need for scalable and efficient crop monitoring systems in industrial plant factories calls for image-based deep learning models that are both accurate and robust to domain variability. This study investigates the feasibility of CNN-based growth stage classification of butterhead lettuce (Lactuca sativa L.) using two data types: raw images and images processed through GrabCut–Watershed segmentation. A ResNet50-based transfer learning model was trained and evaluated on each dataset, and cross-domain performance was assessed to understand generalization capability. Models trained and tested within the same domain achieved high accuracy (Model 1: 99.65%; Model 2: 97.75%). However, cross-domain evaluations revealed asymmetric performance degradation—Model 1-CDE (trained on raw images, tested on preprocessed images) achieved 82.77% accuracy, while Model 2-CDE (trained on preprocessed images, tested on raw images) dropped to 34.15%. Although GrabCut–Watershed offered clearer visual inputs, it limited the model’s ability to generalize due to reduced contextual richness and oversimplification. In terms of inference efficiency, Model 2 recorded the fastest model-only inference time (0.037 s/image), but this excluded the segmentation step. In contrast, Model 1 achieved 0.055 s/image without any additional preprocessing, making it more viable for real-time deployment. Notably, Model 1-CDE combined the fastest inference speed (0.040 s/image) with stable cross-domain performance, while Model 2-CDE was both the slowest (0.053 s/image) and least accurate. Grad-CAM visualizations further confirmed that raw image-trained models consistently attended to meaningful plant structures, whereas segmentation-trained models often failed to localize correctly in cross-domain tests. These findings demonstrate that training with raw images yields more robust, generalizable, and deployable models. The study highlights the importance of domain consistency and preprocessing trade-offs in vision-based agricultural systems and lays the groundwork for lightweight, real-time AI applications in smart farming. Full article

The Malabo Declaration commits African Union member states to eliminating hunger by 2025. Progress toward this target has been uneven and poorly understood. While some countries have recorded gains in non-hunger thematic areas such as finance, trade, resilience to climate variability, and governance and accountability mechanisms, the extent to which these improvements contribute to hunger reduction remains unclear. This study investigates whether performance in non-hunger areas, as measured through the Comprehensive Africa Agriculture Development Programme Biennial Review C-scores, is statistically associated with outcomes under Commitment 3, which focuses on hunger reduction. We used random effects panel regression model covering 55 African countries from 2017 to 2023, the analysis identifies five significant predictors: agricultural GDP and poverty reduction (PC 4.1), foreign private investment (PC 2.3), multi stakeholder coordination (PC 1.2), inclusive public–private partnerships (PC 4.2), and trade policies (PC 5.2). Investment in resilience (PC 6.2) and capacity for planning and monitoring (PC 7.1) showed marginal associations. Our findings suggest that institutional presence alone does not drive hunger outcomes. We reflect that what matters is the structure, inclusiveness, and functionality of these mechanisms, including whether investments reach food-insecure populations, coordination platforms influence decisions, and policies adapt to local conditions. This study concludes that some high-performing categories fail to deliver tangible hunger reduction benefits when implementation is fragmented or disconnected from context. These findings challenge how progress is currently measured and interpreted at the regional level. Finally, we reiterate that as the region prepares for the post-2025 agenda, future strategies must directly link agricultural transformation to hunger reduction through targeted interventions and accountable institutions. Full article

Controlling agricultural carbon emissions is crucial for addressing global environmental challenges. As a major player in agricultural trade, China needs to explore a specific pathway to reduce its agricultural carbon emissions. This study delves into the impact of China’s agricultural trade on agricultural carbon emissions: (1) The research demonstrates that agricultural trade (AT) significantly reduces China’s agricultural carbon emissions (ACEs), with robustness and endogeneity tests supporting these findings. (2) In the process of lowering agricultural carbon emissions, AT exerts both direct and indirect effects. The direct effect stems from the import substitution effect of agricultural trade, while the indirect effects include agricultural technological innovation (ATI) and the agricultural carbon emission intensity (ECI). (3) The reduction in ACEs is more pronounced in eastern regions, coastal areas, and non-major grain-producing regions. This study reveals the underlying mechanisms between AT and ACEs, suggesting that China has the potential to achieve mutual benefits in international trade and environmental protection. It also provides a trade-oriented perspective for formulating agricultural emission reduction policies. Full article