Search Results (820)

The Miombo woodlands are declining in both area and value, primarily due to over-harvesting of commonly preferred species. These forests, however, still contain several other species that are potentially of commercial importance. This study aimed to address the need for improved volume and biomass estimates for the sustainable management and utilization of two of the most abundant timber species in Mozambique’s Miombo woodlands: Brachystegia spiciformis (common name: Messassa) and Julbernardia globiflora (common name: red Messassa). Non-linear models were developed to estimate the merchantable wood volume under bark, heartwood volume, and biomass. The volume and biomass models for wood and heartwood volume, which included both diameter at breast height (DBH) and tree height as predictor variables, outperformed single-predictor models. However, the performance of some ratio models using DBH as the only predictor variable surpassed that of models using two predictor variables. The developed models are recommended for adoption by forest companies to increase economic and environmental benefits as they can refine harvest planning by improving the selection of trees for harvesting. Proper tree selection enhances the rate of recovery of high-quality timber from heartwood while observing sustainable forest management practices in Miombo and increasing the proportion of carbon removed from forests, which is subsequently stored in wood products outside the forest. 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

The Brazilian forestry sector comprises 9.94 million hectares of plantations, with eucalyptus dominating 75% of this area for pulp production. Technological advances have enhanced machinery performance, with the cut-to-length system being the primary method for pulpwood production. This study aimed to optimize the operational cycle of the log loader by evaluating productivity, operational cycles, and loading costs. Data were collected in Bahia, northeastern Brazil, from a forestry company operating under varying productivity scenarios and forest rotations. Time and motion studies were conducted to assess the log loader’s cycles, while productivity and cost analyses were performed. The results indicated that predictive models effectively explained productivity variations. The log loader’s productivity increased with the average volume per tree (AVT) and decreased with the number of movements, which consumed 68% of the cycle time due to wood adjustment and stack organization. Stages such as personal breaks, truck movements, crane adjustments, and cleaning of fallen material showed no significant statistical differences. Loading costs rose by up to 154% with increased movements and decreased with a higher AVT. Additionally, loading tri-train trucks significantly influenced transportation efficiency, emphasizing the importance of optimizing the log loader’s cycle to balance costs and enhance transportation operations. Full article

The construction sector’s increasing eco-consciousness is driving the need for higher-performance wood-based engineered products from underutilized timber resources, such as small-diameter trees from hazardous fuel treatments of our forests. Strand-based products, including oriented strand board (OSB) and lumber (OSL), are widely used. However, hot-pressing during their manufacturing generates approximately 10% waste, which includes a substantial amount of resinated strands that are landfilled. The huge potential of using strand-based products has led to many studies and growing interest in strand-based three-dimensional sandwich panels that can be used as wall, floor, or roofing panels. As the market grows, understanding the recyclability of these resinated strands becomes crucial. This study investigates the feasibility of using re-resinated waste strands that were collected during lab-scale production of strand-based panels. Results demonstrate significant improvements in dimensional stability, mechanical properties, and fire resistance. Specifically, recycling increased internal bond strength, flexural strength, time to ignition, time to flameout, mass loss, and time to peak heat release rate by 107%, 44%, 58%, 35%, 51%, and 27%, respectively, and helped decrease water absorption and thickness swell by 51% and 58%, respectively. Full article

Aboveground biomass models are useful for assessing vegetation conditions and providing valuable information on the availability of ecosystem goods and services, including carbon stock and forest/rangeland products. This study aimed to develop aboveground biomass estimation models for the common woody species found in Borana woodland. Multispecies and species-specific models for aboveground biomass were developed using 114 destructively sampled trees representing five species. The dendrometric variables selected as predictors of the trees’ aboveground dry biomass for both multispecies and species-specific models were diameter at breast height, tree height, wood basic density (ρ), crown area (ca) and crown diameter (cd). The distribution of biomass across trees’ aboveground components was estimated using destructively sampled trees. Most tree biomass is allocated to branches, followed by the stems. The tree diameter, wood basic density, and crown diameter were significant predictors in generic and species-specific biomass models across all tree components. Incorporating wood basic density into the model significantly improved prediction accuracy, while tree height had a minimal effect on biomass estimation. The stem and twig biomasses were the highest and least predictable plant parts, respectively. Compared with the existing models, our newly developed models significantly reduced prediction errors, reinforcing the importance of location-specific models for accurate biomass estimation. Hence, this study fills the geographic and ecological gaps by developing models tailored with the unique conditions of the Borana lowland forest. The accuracy of species-specific biomass models varied among tree species, indicating the need for species-specific models that account for variations in growth architecture, ecological factors, and bioclimatic conditions. Full article

This paper examines how best to use forest wood for energy application, considering that it is a limited natural resource. Eight systems are considered, including wood stoves, steam systems (boiler, power plant, and combined heat and power (CHP)), and gasification combined systems (gas turbine and combined cycle power plant, CHP, and Fischer–Tropsch). The methodology uses energy analysis and modelling and environmental/sustainability considerations to compare the energy systems. In terms of energy conversion efficiency, steam boilers and high-efficiency wood stoves for heating applications provide the highest efficiencies (~80 to 90%) and should be considered. Steam CHP systems provide lower overall energy conversion efficiencies (~75 to 80%) but do provide some electrical energy, and thus should be considered. The use of wood for the production of electricity on its own should not be considered due to low efficiencies (~20 to 30%). Particulate emissions hinder the application of high-efficiency stoves, especially in urban areas, whereas for industrial-scale steam boilers and CHP systems, particle separators can negate this problem. Gasification/Fischer–Tropsch systems have a lower energy efficiency (~30 to 50%); however, a sustainability argument could be made for liquid fuels that have few sustainable alternatives. Full article

The main objective of energy balance analysis is to guide farmers in making informed decisions that promote the efficient management of natural resources, optimise the use of agricultural inputs, and improve the overall economic performance of their farms. In addition, it supports the adoption of sustainable agricultural practices, such as crop diversification, the use of renewable energy sources, and the recycling of agricultural by-products and residues into natural energy sources or fertilisers. This paper analyses the variation in energy efficiency between 2019 and 2022 of the main crops in Angola: maize, soybean, and rice, and the forest production of eucalyptus biomass in agroforestry farms. The research was based on the responses to interviews conducted with the managers of the farms regarding the machinery used, fuels and lubricants, labour, seeds, phytopharmaceuticals, and fertilisers. The quantities are gathered by converting data into Megajoules (MJ). The results show variations in efficiency and energy balance. In corn, efficiency fluctuated between 1.32 MJ in 2019 and 1.41 MJ in 2020, falling to 0.94 MJ in 2021 due to the COVID-19 pandemic before rising to 1.31 MJ in 2022. For soybeans, the energy balance went from a deficit of −8223.48 MJ in 2019 to a positive 11,974.62 MJ in 2022, indicating better use of resources. Rice stood out for its high efficiency, reaching 81,541.33 MJ in 2021, while wood production showed negative balances, evidencing the need for more effective strategies. This research concludes that understanding the energy balance of agricultural operations in Angola is essential not only to achieve greater sustainability and profitability but also to strengthen the resilience of agricultural systems against external factors such as climate change, fluctuations in input prices, and economic crises. A comprehensive understanding of the energy balance allows farmers to assess the true cost-effectiveness of their operations, identify energy inefficiencies, and implement more effective strategies to maximise productivity while minimising environmental impacts. Full article

In Europe, long-distance transport of wood from landings to consumers is most often carried out by trucks and trucks with trailers. In forests located mainly in mountainous areas with rugged terrain and frequent curves, the construction of forest roads is complicated and often access for trucks with trailers is difficult or there is not enough space on the landing for maneuvers. In these cases, the truck leaves the trailer next to the public road and without it moves to the landing and loads the wood with Palafinger hydraulic crane model Epsilon Kran GmbH mounted on it, which it transfers to the trailer on the way back. Then, the truck moves to the landing to load itself, returns, hooks up the trailer and transports the wood to the customer. This study, conducted in a coniferous stand in Bulgaria, aimed to determine and develop models for the productivity and costs associated with transporting a truck with a trailer and to evaluate the suitability of this method. To study this very common method of long-distance transport, observations were made of 185 turns of a truck with a trailer operating with coniferous wood in Rila-Rhodope Mountain Massif, Southern Bulgaria. It was found that the duration of the working cycle is affected by the total mileage (average 65.41 km), the volume of the load and the number of logs. The productivity with and without delays, 7.80 and 7.30 m³/h, respectively, is affected by the mileage and the volume of the wood, while the corresponding transportation productivity (177.46 and 167.24 m³ km/h) is affected by the transport distance loaded and the volume of the load. To increase efficiency and reduce the cost of transporting wood over long distances, investments are needed to improve forest roads to eliminate the need to uncouple the trailer. Full article

The use of non-wood forest products plays a significant role in sustainable development, especially in the context of regional development. One of the most important and promising raw materials is birch sap, which in European conditions is obtained mainly from silver birch (Betula pendula Roth). Research on the utility value of birch sap and the influence of a number of factors on its efficiency and quality has been carried out in many research centers, but so far, there are not many studies on the variability of such parameters as a function of time, taking into account the entire period of sap leakage. This research was carried out in birch stands of approximately 80 years in three forest site types: mixed coniferous forest, mixed broadleaved forest, and broadleaved forest. In each site, nine sample trees were selected using Hartig’s method. The daily and all-season sap yield obtained from individual trees was statistically characterized. The relationship between birch sap yield and select quantitative (tree height, absolute and relative crown length, and slenderness) and qualitative (forest site type, tree thickness class, and sap harvesting period) variables was examined. For the first time in the literature on the subject, there is a proposal to distinguish the phases of obtaining birch sap, which may bring new knowledge, both in relation to daily productivity and the quality of the sap. As a result, the smallest amount of sap was found in the initial leak phase, a slightly higher amount was found in the final phase, and the largest amount was found in the main phase. Regarding the forest site type and the interaction between the collection phase and forest site type, no statistically significant relationship with the average amount of obtained sap was found. Full article

Mangrove forests are among the most productive vascular plants on Earth. The gross (GPP) and aboveground forest net primary production (ANPP) correlate positively with precipitation. ANPP also correlates inversely with porewater salinity. The main drivers of the forest primary production are the porewater salinity, rainfall, tidal inundation frequency, light intensity, humidity, species age and composition, temperature, nutrient availability, disturbance history, and geomorphological setting. Wood production correlates positively with temperature and rainfall, with rates comparable to tropical humid forests. Litterfall accounts for 55% of the NPP which is greater than previous estimates. The fine root production is highest in deltas and estuaries and lowest in carbonate and open-ocean settings. The GPP and NPP exhibit large methodological and regional differences, but mangroves are several times more productive than other coastal blue carbon habitats, excluding macroalgal beds. Mangroves contribute 4 to 28% of coastal blue carbon fluxes. The mean and median canopy respiration equate to 1.7 and 2.7 g C m⁻² d⁻¹, respectively, which is higher than previous estimates. Mangrove ecosystem carbon fluxes are currently in balance. However, the global mangrove GPP has increased from 2001 to 2020 and is forecast to continue increasing to at least 2100 due to the strong fertilization effect of rising atmospheric CO₂ concentrations. 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

The plywood industry is one of the most significant sub-sectors of the forestry industry and serves as a cornerstone of sustainable construction within a bioeconomy framework. Plywood is a panel composed of multiple layers of wood sheets bonded together. While automation and process monitoring have played a crucial role in improving efficiency, data-driven decision-making remains underutilized in the industrial sector. Many industrial processes continue to rely heavily on the expertise of operators rather than on data analytics. However, advancements in data storage capabilities and the availability of high-speed computing have paved the way for data-driven algorithms that can support real-time decision-making. Due to the biological nature of wood and the numerous variables involved, managing manufacturing operations is inherently complex. The multitude of process variables, and the presence of non-linear physical phenomena make it challenging to develop accurate and robust analytical predictive models. As a result, data-driven approaches—particularly Artificial Intelligence (AI)—have emerged as highly promising modeling techniques. Leveraging industrial data and exploring the application of AI algorithms, particularly Machine Learning (ML), to predict key performance indicators (KPIs) in process plants represent a novel and expansive field of study. The processing of industrial data and the evaluation of AI algorithms best suited for plywood manufacturing remain key areas of research. This study explores the application of supervised Machine Learning (ML) algorithms in monitoring key process variables to enhance quality control in veneers and plywood production. The analysis included Random Forest, XGBoost, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Lasso, and Logistic Regression. An initial dataset comprising 49 variables related to the maceration, peeling, and drying processes was refined to 30 variables using correlation analysis and Lasso variable selection. The final dataset, encompassing 13,690 records, categorized into 9520 low-quality labels and 4170 high-quality labels. The evaluation of classification algorithms revealed significant performance differences; Random Forest reached the highest accuracy of 0.76, closely followed by XGBoost. K-Nearest Neighbors (KNN) demonstrated notable precision, while Support Vector Machine (SVM) exhibited high precision but low recall. Lasso and Logistic Regression showed comparatively lower performance metrics. These results highlight the importance of selecting algorithms tailored to the specific characteristics of the dataset to optimize model effectiveness. The study highlights the critical role of AI-driven insights in improving operational efficiency and product quality in veneer and plywood manufacturing, paving the way for enhanced industrial competitiveness. Full article

Particleboard is an important forest product that can be reprocessed using wood processing by-products. This approach has the potential to achieve significant conservation of forest resources and contribute to the protection of forest ecology. Most current detection models require a significant number of tagged samples for training. However, with the advancement of industrial technology, the prevalence of surface defects in particleboard is decreasing, making the acquisition of sample data difficult and significantly limiting the effectiveness of model training. Deep reinforcement learning-based detection methods have been shown to exhibit strong generalization ability and sample utilization efficiency when the number of samples is limited. This paper focuses on the potential application of deep reinforcement learning in particleboard defect detection and proposes a novel detection method, PPOBoardNet, for the identification of five typical defects: dust spot, glue spot, scratch, sand leak and indentation. The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. The method integrates the variable action space and the composite reward function and achieves the balanced optimization of different types of defect detection performance by adjusting the scaling and translation amplitude of the detection region. In addition, this paper proposes a state characterization strategy of multi-scale feature fusion, which integrates global features, local features and historical action sequences of the defect image and provides reliable guidance for action selection. On the particleboard defect dataset with limited images, PPOBoardNet achieves a mean average precision (mAP) of 79.0%, representing a 5.3% performance improvement over the YOLO series of optimal detection models. This result provides a novel technical approach to the challenge of defect detection with limited samples in the particleboard domain, with significant practical application value. Full article

Global cacao production, primarily led by African countries, is facing a crisis, which presents growth potential for South American countries like Colombia, Peru, and Ecuador. However, a significant challenge for these countries is cadmium (Cd) contamination in cacao beans. Agroforestry systems with cacao (CAFSs) improve soil health and can remediate Cd through tree phytoextraction. Effective phytoremediation requires Cd-tolerant, high-biomass species and preferential Cd allocation to stems. This study evaluated the phytoremediation potential of four forest species (Cariniana pyriformis Miers, Terminalia superba Engl. and Diels, Swietenia macrophylla King, and Cedrela odorata L.) under cadmium (Cd) exposure. C. pyriformis exhibited hypertolerance, showing minimal biomass reduction (less than 15%, changing from 1.619 to 1.343 g plant⁻¹) under excess Cd conditions, compared to Cedrela odorata and T. superba, which showed significant biomass reductions. C. pyriformis and T. superba showed notable Cd accumulation in stems (652.99 and 635.39 mg Cd kg⁻¹), an essential feature for wood tree-mediated phytoextraction, while C. odorata allocated more Cd to leaves (35.35 mg Cd kg⁻¹). C. pyriformis maintained high photosynthesis (12.8 μmol CO₂ m⁻² s⁻¹), light use efficiency (0.086 mol CO₂ mol photons⁻¹), and an increased relative growth rate (0.575 g g⁻¹ day⁻¹) under Cd exposure. Overall, C. pyriformis demonstrated significant potential for use in phytoremediation due to its high Cd tolerance (84%), efficient allocation to stems (17%), and sustained physiological performance under Cd exposure. Conversely, C. odorata allocates Cd to leaves (16%), which can reintroduce Cd into the soil, and exhibits a low tolerance index (54%) under higher cadmium contamination. Further studies are still needed to understand the specific mechanisms of Cd accumulation in stems of promising species like C. pyriformis and T. superba. 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