Search Results (150)

Exploring the action mechanisms and enhancement pathways of the resilience of agricultural product green supply chains is conducive to strengthening the system’s risk resistance capacity and providing decision support for achieving the “dual carbon” goals. Based on theories such as dynamic capability theory and complex adaptive systems, this paper constructs a resilience framework covering the three stages of “steady-state maintenance–dynamic adjustment–continuous evolution” from both single and multiple perspectives. Combined with 768 units of multi-agent questionnaire data, it adopts Structural Equation Modeling (SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze the influencing factors of resilience and reveal the nonlinear mechanisms of resilience formation. Secondly, by integrating configurational analysis with machine learning, it innovatively constructs a resilience level prediction model based on fsQCA-XGBoost. The research findings are as follows: (1) fsQCA identifies a total of four high-resilience pathways, verifying the core proposition of “multiple conjunctural causality” in complex adaptive system theory; (2) compared with single algorithms such as Random Forest, Decision Tree, AdaBoost, ExtraTrees, and XGBoost, the fsQCA-XGBoost prediction method proposed in this paper achieves an optimization of 66% and over 150% in recall rate and positive sample identification, respectively. It reduces false negative risk omission by 50% and improves the ability to capture high-risk samples by three times, which verifies the feasibility and applicability of the fsQCA-XGBoost prediction method in the field of resilience prediction for agricultural product green supply chains. This research provides a risk prevention and control paradigm with both theoretical explanatory power and practical operability for agricultural product green supply chains, and promotes collaborative realization of the “carbon reduction–supply stability–efficiency improvement” goals, transforming them from policy vision to operational reality. Full article

The sustainable utilization of forest biomass for bioenergy production is increasingly challenged by the variability and unpredictability of raw material availability. These challenges are particularly critical in regions like Central Portugal, where seasonality, dispersed resources, and wildfire prevention policies disrupt procurement planning. This study investigates two flexibility strategies—dynamic network reconfiguration and operations postponement—as policy relevant tools to enhance resilience in forest-to-bioenergy supply chains. A novel mathematical model, the mobile Facility Location Problem with dynamic Operations Assignment (mFLP-dOA), is proposed and solved using a scalable matheuristic approach. Applying the model to a real case study, we demonstrate that incorporating temporary intermediate nodes and adaptable processing schedules can reduce costs by up to 17% while improving operational responsiveness and reducing non-productive machine time. The findings offer strategic insights for policymakers, biomass operators, and regional planners aiming to design more adaptive and cost-effective biomass supply systems, particularly under environmental risk scenarios such as summer operation bans. This work supports evidence-based planning and investment in flexible logistics infrastructure for cleaner and more resilient bioenergy supply chains. Full article

Heilongjiang Province, as China’s principal gateway for Russian timber imports, faces structural inefficiencies in the localization of wood-processing enterprises—characterized by ecological sensitivity, resource–industry mismatches, and uneven spatial distribution. To address these challenges, this study proposes a two-stage site selection framework that integrates Geographic Information Systems (GIS) with an enhanced Non-dominated Sorting Genetic Algorithm II (NSGA-II). The model aims to reconcile ecological protection with industrial efficiency by identifying optimal facility locations that minimize environmental impact, reduce construction and logistics costs, and enhance service coverage. Using spatially resolved multi-source datasets—including forest resource distribution, transportation networks, ecological redlines, and socioeconomic indicators—the GIS-based suitability analysis (Stage I) identified 16 candidate zones. Subsequently, a multi-objective optimization model (Stage II) was applied to minimize carbon intensity and cost while maximizing service accessibility. The improved NSGA-II algorithm achieved convergence within 700 iterations, generating 124 Pareto-optimal solutions and enabling a 23.7% reduction in transport-related CO₂ emissions. Beyond carbon mitigation, the model spatializes policy constraints and economic trade-offs into actionable infrastructure plans, contributing to regional sustainability goals and transboundary industrial coordination with Russia. It further demonstrates methodological generalizability for siting logistics-intensive and policy-sensitive facilities in other forestry-based economies. While the model does not yet account for temporal dynamics or agent behaviors, it provides a robust foundation for informed planning under China’s dual-carbon strategy and offers replicable insights for the global forest products supply chain. Full article

Softwood bark and twigs represent by-products of forest supply chains rich in extractable bioactive compounds. This study aimed at evaluating the bioactive molecules of hydrodynamic cavitation (HC) based extracts of bark and twigs from different conifer plants and exploring their antioxidant capacity. Samples of Picea abies twigs (RAR) and bark (CAR) and Abies alba twigs (SFT) underwent extraction using a pilot-scale Venturi reactor HC device. The freeze-dried extracts were characterized for the antioxidant capacity, through both in vitro and ex vivo assays, the antimicrobial activity, and the content of phenolics and free amino acids by UHPLC-ESI-MS/MS. HC-based aqueous extracts were obtained quickly and with low energy consumption. We found 10 phenolic acids, nine flavonols, three flavan-3-ols, five flavanones, three procyanidins, two stilbenoids, and 10 other phenolic compounds. Moreover, eight essential and seven dispensable amino acids were found. The principal component analysis showed clear discrimination among the three extracts. The CAR extract showed antimicrobial activity. The SFT extract showed the higher anthocyanins content and antioxidant activity, both through in vitro and ex vivo methods. These preliminary results confirm that by-products of Picea abies and Abies alba are rich in bioactive compounds and antioxidant activities, suggesting potential applications in the nutraceutical and pharmaceutical fields. Full article

The global supply chain of wood products plays a key role in sustainable development and climate resilience, but remains fragmented in the academic and technical literature. This systematic review aims to synthesize research published between 2000 and 2025 on wood products’ production, transformation, trade, governance, and sustainability. A comprehensive search was conducted in multiple databases and repositories, including Scopus, FAOSTAT, ScienceDirect, DOAJ, SciELO, CAPES, EMBRAPA, and AGNIC. A total of 784 records were identified and, after applying eligibility and deduplication criteria, 119 documents were included in the final synthesis. The results reveal key thematic trends, including the dynamics of international timber trade, certification and traceability systems, logistical challenges, digitalization, and integration of forest policies. Key gaps include limited inclusion of smallholders, low technology adoption in the Global South, and fragmented governance mechanisms. The results suggest that improving sustainability in global timber supply chains requires coordinated policy frameworks, technological investment, and inclusive market systems. This review contributes a consolidated overview and offers insights for researchers, policymakers, and practitioners in the forestry sector. Full article

This study examines the establishment of a Hub for Circular Economy and Industrial Symbiosis (HUB-CEIS) centred on a forest biomass waste plant in Fundão, Portugal, presenting an innovative model for rural industrial symbiosis, circular economy governance, and sustainable waste management. Designed as a strategic node within a reverse supply chain, the hub facilitates the conversion of solid waste into renewable energy and high-value co-products, including green hydrogen, tailored for industrial and agricultural applications, with an estimated 120 ktCO₂/year reduction and 60 direct jobs. Aligned with the United Nations (UN) Sustainable Development Goals (SDGs) and the Paris Agreement, this initiative addresses global challenges such as decarbonization, resource efficiency, and the energy transition. Employing a mixed research methodology, this study integrates a comprehensive literature review, in-depth stakeholder interviews, and comparative case study analysis to formulate a governance framework fostering regional partnerships between industry, government, and local communities. The findings highlight Fundão’s potential to become a benchmark for rural industrial symbiosis, offering a replicable model for circularity in non-urban contexts, with a projected investment of USD 60 M. Special emphasis is placed on the green hydrogen value chain, positioning it as a key enabler for regional sustainability. This research underscores the importance of cross-sectoral collaboration in achieving scalable and efficient waste recovery processes. By delivering practical insights and a robust governance structure, the study contributes to the circular economy literature, providing actionable strategies for implementing rural reverse supply chains. Beyond validating waste valorization and renewable energy production, the proposed hub establishes a blueprint for sustainable rural industrial development, promoting long-term industrial symbiosis integration. Full article

This study explores how integrating design processes into the native timber industry of southern Chile, specifically in the Araucanía and Los Ríos regions, can improve the value chain and promote sustainability. Chile’s native wood sector is constrained by fragmented value chains, underutilised small-diameter logs and limited market confidence. These challenges jeopardise forest sustainability and rural livelihoods, underscoring the imperative to find innovative solutions to reinvigorate the sector. A market gap analysis revealed critical limitations in the current industry, including low supply, limited demand, and weak technological development, especially in producing value-added wood products. The research identified over 417,000 hectares of second-growth roble (Nothofagus obliqua)-raulí (Nothofagus alpina)-coigüe (Nothofagus dombeyi) forests suitable for sustainable management. Interviews with woodworking SMEs showed that 66% already use native timber, yet 46% of the projected volume remains underutilised due to the prevalence of short and thin logs. In response to these challenges, the study developed innovative prototypes such as interior claddings and lattices made from smaller, underutilised logs. These designs were evaluated and validated for use in residential and public buildings, demonstrating their potential to meet new market demands while promoting resource efficiency. The results show that, whilst there is a clear need for better infrastructure, workforce training, and commercial planning to support product adoption, design-driven innovation offers a promising path forward enhancing the industry’s competitiveness. Demonstrating how design-led integration can transform under-used native timber into high-value products, simultaneously driving sustainable forest stewardship and local economic growth. Full article

China is one of the world’s leading producers and exporters of wood-based panels and plays a crucial role in ensuring a stable global supply of wood products. But China’s wood product exports have recently diminished, potentially due to the retraction of foreign investment. This behavior remains unexamined mechanistically in the current literature. This study investigates the impact of FDI on the export performance of China’s wood processing industry and explores the potential for leveraging foreign investment to reverse the downward trend in export growth. Our findings indicate that FDI alleviates export constraints by enhancing wood resource efficiency, which suggests a substantive response to industry challenges rather than a mere strategic adjustment. However, FDI inflows have decreased in recent years, negatively affecting export performance and highlighting the need for policy improvements. We further examine the differential effects of FDI on exports across port and non-port regions, given that the urgency of attracting FDI varies spatially. Our analysis reveals that the export spillover effect of FDI in port areas is approximately 165% higher than in non-port areas, largely due to China’s high dependence on wood product imports. In regions with extensive artificial forests, the impact is lower, possibly due to a stronger focus on domestic markets. In particular, Eastern China, benefiting from early market liberalization and a history of successful foreign collaborations, demonstrates significant improvements in export performance. To mitigate the export pressures on China’s wood processing industry, we recommend targeted industrial policies, particularly for port areas, to attract high-quality FDI that supports global supply chain stability and sustainable development. Full article

Efficient supply chain management (SCM) is essential for enterprises seeking to enhance operational efficiency, reduce costs, and mitigate risks while ensuring product quality and customer satisfaction. Addressing quality concerns within the supply chain proactively helps minimize rework, recalls, and returns, leading to significant cost savings and improved profitability. This study presents a machine learning (ML)-driven predictive analytics framework designed to forecast defect rates and optimize quality control processes. The research leverages a dataset sourced from a real-world fashion and beauty startup, hosted in a public repository. The framework employs advanced ML algorithms, including extreme gradient boosting (XGBoost), support vector machines (SVMs), and random forests (RFs), to accurately predict defect rates and derive actionable insights for supply chain optimization. Results demonstrate the effectiveness of predictive analytics in improving supply chain quality management, enabling enterprises to proactively reduce defect rates, minimize costs, and optimize return on investment (ROI). The proposed framework is designed to be scalable and transferable, ensuring adaptability across various industries, including fashion, e-commerce, and manufacturing. These findings underscore the economic and operational benefits of integrating machine learning into supply chain quality control, offering a data-driven, proactive approach to achieving high-efficiency, high-quality supply chain operations. Full article

This study aims to assess the environmental impact of using wood-based biomass as a high-efficiency fuel alternative to fossil fuels for heat production. To achieve this, the life cycle of biomass transformation, utilization, and disposal was analyzed using the life cycle assessment (LCA) methodology with SimaPro 9.5.0.2 PhD software. The system boundaries included extraction, processing, transportation, combustion, and waste management, following a cradle-to-gate approach. A comparative analysis was conducted between natural gas, the most widely used conventional heating fuel, and two biomass-based fuels: wood pellets and wood chips. The results indicate that biomass utilization reduces greenhouse gas emissions (−19%) and fossil resource depletion (−16%) while providing environmental benefits across all assessed impact categories analyzed, except for land use (+96%). Biomass is also to be preferred for forest waste management, ease of supply, and energy independence. However, critical life cycle phases, such as raw material processing and transportation, were found to contribute significantly to human health and ecosystem well-being. To mitigate these effects, optimizing combustion efficiency, improving supply chain logistics, and promoting sustainable forestry practices are recommended. These findings highlight the potential of biomass as a viable renewable energy source and provide insights into strategies for minimizing its environmental footprint. Full article

The term “added value” is frequently used by stakeholders in the forest wood sector. However, beyond its intuitive meaning, what does “added value” mean in economics, and what are the main ways of adding value to wood-based products? To answer these questions, a theoretical framework of the concept of “added value” and an overview of its main applications within wood supply chains are provided. Subsequently, the results of a systematic literature review are reported. A total of 1974 primary research articles published in English in the last decade were collected from the Scopus and Web of Science databases. The main objectives were to understand how the “added value” concept is addressed, determine which wood-based products are studied, identify how value is added, and ascertain the main consequences. The analysis of the 111 selected articles showed that the term “added value” is often used as a label rather than a clearly defined concept. Improved production processes and the valorisation of raw materials were found to be the main methods of adding value to wood-based products, while environmental benefits emerged as the most frequent objective. The findings may serve several purposes, such as identifying research needs, guiding industrial innovation, and informing policy makers, helping to implement measures that really benefit wood supply chains. Building on this study, future research could explore how added value is perceived and implemented by forest enterprises, wood industries, policymakers, and other stakeholders. This would provide a broader reference framework for applying the concept of added value. Full article

With the intensification of global resource competition, the issue of timber supply has escalated from an economic concern to a significant strategic challenge. This study focuses on the evolution of disruption resilience in the global trade network for wood forest products, aiming to reveal the patterns of resilience dynamics under disruption risks by simulating underload cascading failure phenomena. The study provides theoretical support for enhancing the security and stability of the global wood forest product supply chain. Utilizing global trade data from the UN Comtrade Database 2023, a directed weighted complex network model was constructed, spanning upstream, midstream, and downstream sectors, with trade intensity distances serving as edge weights. By developing an underload cascading failure model, the evolution of disruption resilience was simulated under various disruption scenarios from 2002 to 2023, and the long-term impacts of critical node failures on network performance were analyzed. The results demonstrate significant spatiotemporal heterogeneity in the disruption resilience of the global wood forest product trade network. The upstream network exhibits improved resilience in total node strength but reduced global efficiency. The midstream network shows marked volatility in resilience due to external shocks, such as the global financial crisis, while the downstream network remains relatively stable. Simulations reveal that failures in core nodes (e.g., China, the United States, and Germany) disproportionately degrade global efficiency and node strength, with node centrality metrics positively correlated with network performance loss. This study elucidates the evolutionary mechanisms of disruption resilience in the wood forest product trade network under risk propagation, offering actionable insights for optimizing network robustness and supply chain stability. It is recommended that policymakers promote green supply chain initiatives, accelerate afforestation projects, and enhance domestic timber self-sufficiency to reduce reliance on imported timber, thereby strengthening node resilience and fostering sustainable forest resource utilization for economic and environmental benefits. Full article

This study explores the application of Fourier transform infrared (FTIR) spectroscopy combined with chemometric and machine learning techniques for authenticating sheep’s milk and distinguishing it from cow’s milk. The demand for accurate authentication methods is driven by the high production costs of sheep’s milk and the prevalent issue of adulteration with cow’s milk, which can have economic, health, and ethical implications. Our research utilizes exploratory analysis, regression, and classification tasks on spectral data to identify characteristic spectral signatures and physicochemical parameters for sheep’s milk. Key methods included the application of decision trees, random forests, and k-nearest neighbors (KNN), with the random forest model showing the highest predictive accuracy (R² of 0.9801). Principal Component Analysis (PCA) and analysis of variance (ANOVA) revealed significant spectral and compositional differences, particularly in fat content and wavelengths responsible for amide I and II bands (1454 nm and 1550 nm) correlated with the conformational characteristics of the proteins, with sheep’s milk exhibiting higher values than cow’s milk. These findings indicate the potential of FTIR spectroscopy as a reliable tool for milk authentication. Currently, digitalization within the milk production chain is limited, particularly in the case of regional dairy products. The introduction of integrated photonics, machine learning, and, in the future, telemetry systems would enable dairy farmers to optimize their operations and ensure the origin and quality of the milk supplied to milk producers. Full article

Among the land use–land cover products, tree cover maps are essential tools for assessing forest functionality and ecosystem services, and implementing sustainable forest management. By combining open-source and ancillary high-resolution cartographic datasets, this study aims to map trees and forests in the Latium region in central Italy, highlighting their spatial configuration, function, and forest typology. The main findings show that trees cover 44.2% of the regional land area. Forests cover 508,056 ha, forming the core matrix of the Latium mountain landscape, providing significant ecological and socio-economic value for forest management and the regional wood supply chain. Although trees outside the forest represent only 3.1% of regional tree cover, they play a crucial role in enhancing ecological connectivity and landscape resilience. Approximately 2% of the tree and forest cover occurs in urban areas, contributing significantly to climate regulation and air quality in densely populated environments. The dominant forest types in Lazio include Turkey oak, temperate broadleaf, beech, downy oak, and Holm oak, which together account for 58.6% of the total tree cover. The accuracy tests confirm the feasibility of using open-source data for reliable, cost-effective forest mapping. Regular updates of these maps can support continuous monitoring and promote sustainable forest management practices. Full article

Background: The forest products industry plays a significant role in global carbon emissions, highlighting the need for sustainable practices to address the climate crisis. Reverse logistics (RL), focusing on the return, reuse, and recycling of materials, offers a promising approach to decarbonizing supply chains. However, its application within forest products supply chains remains underexplored. Methods: This study conducts a review of the literature on RL, its environmental implications, and its potential to reduce carbon emissions in forest products supply chains. Key areas examined include greenhouse gas reduction, waste management, and the promotion of circular economy principles. Additionally, the study evaluates case studies and models that integrate RL practices into forest-based industries. Results: The findings reveal that RL can significantly reduce greenhouse gas emissions by optimizing transportation routes, minimizing waste, and extending product life cycles. Incorporating these practices into forestry operations reduces the environmental impact and aligns with sustainable forestry goals. The study identifies gaps in current research, particularly regarding empirical data and the scalability of RL solutions. Conclusions: RL represents a critical strategy for decarbonizing forest products supply chains and advancing sustainable development. Future research should focus on developing standardized methodologies, enhancing technological integration, and fostering policy support to maximize its impact. These steps are essential to fully leverage RL as a tool for mitigating climate change and promoting a circular economy. Full article