Search Results (962)

With the rapid expansion of the global timber trade, accurate wood identification has become essential for regulating ecosystems and combating illegal logging. Traditional methods, largely reliant on manual analysis, are inadequate for large-scale, high-precision demands. A multi-architecture fusion network model that combines generative adversarial networks and one-dimensional convolutional neural networks aims to solve the problems in data quality and the challenges in classification accuracy existing in the classification process of pine tree species. The generative adversarial network is used to improve the data, which effectively expands the scale of the training set. Moreover, the one-dimensional convolutional neural network is utilized to extract local and global features from the spectral data, which improves the classification accuracy of the model and also makes the model more stable. The results obtained from the experiment show that MAFNet can achieve an accuracy rate of 99.63% in the classification of pine species. The model performed best on cross-sectional data. The research finds that MAFNet, relying on the strategy of integrating data enhancement and deep feature extraction, provides strong technical support for the rapid, accurate and non-destructive identification of pine species. Full article

Studies of microbial degradation of historic woods are essential to help protect and preserve these important cultural properties. The USS Cairo is a historic Civil War gunboat and one of the first steam-powered and ironclad ships used in the American Civil War. Built in 1861, the ship sank in the Yazoo River of Mississippi in 1862 after a mine detonated and tore a hole in the port bow. The ship remained on the river bottom and was gradually buried with sediments for over 98 years. After recovery of the ship, it remained exposed to the environment before the first roofed structure was completed in 1980, and it has been displayed under a tensile fabric canopy with open sides at the Vicksburg National Military Park in Vicksburg, Mississippi. Concerns over the long-term preservation of the ship initiated this investigation to document the current condition of the wooden timbers, identify the fungi that may be present, and determine the elemental composition resulting from past wood-preservative treatments. Micromorphological characteristics observed using scanning electron microscopy showed that many of the timbers were in advanced stages of degradation. Eroded secondary cell walls leaving a weak framework of middle lamella were commonly observed. Soft rot attack was prevalent, and evidence of white and brown rot degradation was found in some wood. DNA extraction and sequencing of the ITS region led to the identification of a large group of diverse fungi that were isolated from ship timbers. Soft rot fungi, including Alternaria, Chaetomium, Cladosporium, Curvularia, Xylaria and others, and white rot fungi, including Bjerkandera, Odontoefibula, Phanerodontia, Phlebiopsis, Trametes and others, were found. No brown rot fungi were isolated. Elemental analyses using induced coupled plasma spectroscopy revealed elevated levels of all elements as compared to sound modern types of wood. High concentrations of boron, copper, iron, lead, zinc and other elements were found, and viable fungi were isolated from this wood. Biodegradation issues are discussed to help long-term conservation efforts to preserve the historic ship for future generations. Full article

The effects of thermal treatment on the changes in the chemical composition and higher heating values (HHV) of tropical hardwood meranti were investigated in a study. The samples of light red meranti wood (Shorea spp.) with dimensions of 20 mm × 100 mm × 700 mm were conditioned at 20 °C (control samples) and thermally treated at 160, 180, 200, and 220 °C. The chemical composition and HHV of control samples and thermally treated samples were evaluated. The chemical composition was measured using the procedures of Seifert, Wise, and ASTM. After thermal treatment, a significant reduction in holocellulose and hemicellulose content and an increase in extractives and lignin were observed. Consequently, we observed a rise in HHVs. HHV of thermally treated wood was strongly positively linearly correlated with lignin content (Pearson r = 0.9850, p < 0.001, R² = 0.9702, n = 15). Regression analysis showed that the model HHV = 0.1443(lig) + 16.012 is suitable for predicting the HHV of thermally treated wood, if the lignin content is known. Full article

Currently, the customs inspection of wood-boring pests in timber still primarily relies on manual visual inspection, which involves observing insect holes on the timber surface and splitting the timber for confirmation. However, this method has significant drawbacks such as long detection time, high labor cost, and accuracy relying on human experience, making it difficult to meet the practical needs of efficient and intelligent customs quarantine. To address this issue, this paper develops a rapid identification system based on the peristaltic signals of wood-boring pests through the PyQt framework. The system employs a deep learning model with multi-attention mechanisms, namely the Residual Denoising Vision Network (RDVNet). Firstly, a LabVIEW-based hardware–software system is used to collect pest peristaltic signals in an environment free of vibration interference. Subsequently, the original signals are clipped, converted to audio format, and mixed with external noise. Then signal features are extracted through three cepstral feature extraction methods Mel-Frequency Cepstral Coefficients (MFCC), Power-Normalized Cepstral Coefficients (PNCC), and RelAtive SpecTrAl-Perceptual Linear Prediction (RASTA-PLP) and input into the model. In the experimental stage, this paper compares the denoising module of RDVNet (de-RDVNet) with four classic denoising models under five noise intensity conditions. Finally, it evaluates the performance of RDVNet and four other noise reduction classification models in classification tasks. The results show that PNCC has the most comprehensive feature extraction capability. When PNCC is used as the model input, de-RDVNet achieves an average peak signal-to-noise ratio (PSNR) of 29.8 and a Structural Similarity Index Measure (SSIM) of 0.820 in denoising experiments, both being the best among the comparative models. In classification experiments, RDVNet has an average F1 score of 0.878 and an accuracy of 92.8%, demonstrating the most excellent performance. Overall, the application of this system in customs timber quarantine can effectively improve detection efficiency and reduce labor costs and has significant practical value and promotion prospects. Full article

Wood is a renewable, carbon-sequestering, and structurally versatile material that has supported human civilization for millennia and continues to play a central role in advancing sustainable development. Although its low density, high specific strength, and esthetic appeal make it highly attractive, its intrinsic flammability presents significant challenges for safety-critical uses. This review offers a comprehensive analysis that uniquely integrates three key domains, covering advanced processing technologies, flame-retardant functionalization strategies, and multifunctional applications. Clear connections are drawn between processing approaches such as delignification, densification, and nanocellulose extraction and their substantial influence on improving flame-retardant performance. The review systematically explores how these engineered wood substrates enable more effective fire-resistant systems, including eco-friendly impregnation methods, surface engineering techniques, and bio-based hybrid systems. It further illustrates how combining processing and functionalization strategies allows for multifunctional applications in architecture, transportation, electronics, and energy devices where safety, durability, and sustainability are essential. Future research directions are identified with a focus on creating scalable, cost-effective, and environmentally compatible wood-based materials, positioning engineered wood as a next-generation high-performance material that successfully balances structural functionality, fire safety, and multifunctionality. Full article

This study investigated the distribution of pine wood nematodes (PWNs, Bursaphelenchus xylophilus) and their co-occurrence with B. mucronatus in recently dead pine trees across coastal and inland regions while monitoring the seasonal emergence patterns of Monochamus alternatus from 2021 to 2023. Nematodes were extracted from felled trees and beetle bodies using the Baermann funnel method. Aggregation pheromone traps were used to monitor vector activity and to assess temperature-dependent emergence. The results showed a negative correlation between PWN and B. mucronatus density (r = −0.73, p < 0.01), which prompted tests on interspecific interactions. M. alternatus emergence was positively associated with average temperature (r = 0.74–0.78), supporting the temperature-informed surveillance timing in this dataset. These findings highlight the role of climate-driven dynamics in shaping vector behavior and nematode population structures. This study supports the development of sustainable temperature-responsive management strategies for controlling pine wilt disease. These strategies provide a foundation for climate-resilient forest health and long-term ecosystem sustainability. Full article

Persistent scatterer (PS) pixel selection is crucial in the PS-InSAR technique, ensuring the quality and quantity of PS pixels for accurate deformation measurements. However, traditional methods like the amplitude dispersion index (ADI)-based method struggle to balance the quality and quantity of PS pixels. To adequately select high-quality PS pixels, and thus improve the deformation measurement performance of PS-InSAR, the multi-temporal feature extraction network (MFN) is constructed in this paper. The MFN combines the 3D U-Net and the convolutional long short-term memory (CLSTM) to achieve time-series analysis. Compared with traditional methods, the proposed MFN can fully extract the spatiotemporal characteristics of complex SAR images to improve PS pixel selection performance. The MFN was trained with datasets constructed by reliable PS pixels estimated by the ADI-based method with a low threshold using ∼350 time-series Sentinel-1A SAR images, which contain man-made objects, farmland, parkland, wood, desert, and waterbody areas. To test the validity of the MFN, a deformation measurement experiment was designed for Tongzhou District, Beijing, China with 38 SAR images obtained by Sentinel-1A. Moreover, the similar time-series interferometric pixel (STIP) index was introduced to evaluate the phase stability of selected PS pixels. The experimental results indicate a significant improvement in both the quality and quantity of selected PS pixels, as well as a higher deformation measurement accuracy, compared to the traditional ADI-based method. Full article

The aim of this study was to investigate the potential of dyer’s woad (Isatis tinctoria L.) as a sustainable, plant-based colouring agent for enhancing the visual properties of wood surfaces. Veneers of oak (Quercus sp.) and poplar (Populus sp.) were used as materials and dyed with aqueous extracts derived from fresh and dried woad leaves. To facilitate dye uptake, the veneer surfaces were pretreated with various mordants: alum, citric acid, acetic acid, and distilled water (as a control). The aim was to assess the impact of both the form of the plant material and the type of mordant on the resulting colour change. Colour modifications were measured using spectrophotometry and subjected to statistical analysis. The results revealed distinct differences between untreated and dyed veneers, as well as among samples treated with different mordants. Furthermore, the effectiveness of the dye varied depending on whether fresh or dried leaves were used. These findings confirm the feasibility of employing Isatis tinctoria L. as a natural wood dye and highlight its potential as an eco-friendly alternative to synthetic surface treatments in decorative wood applications. Full article

The antifungal effect of catechin and extractives from Prosopis juliflora was studied against one white rot fungus, Trametes versicolor (TV), and one brown rot fungus, Poria placenta (PP). The mentioned extractives from Prosopis julilfora were crude mesquitol and pure mesquitol. Tebuconazole was used in this study as a known fungicide against the two named fungi. Wood preservation using the current synthetic fungicides can be harmful to the environment and toxic to animals and plants. To help solve these problems, fungicides can be mixed with natural extractives to act synergistically as wood preservatives. Most of these natural extractives contain polyphenols, which are secondary metabolites, having good antioxidant properties, which may inhibit radical species involved in wood cell polymer defects. In this study, 1000 ppm and 5000 ppm of crude mesquitol, pure mesquitol and catechin had a very good growth inhibition against TV and PP. Thus, the concentrations were used to assess their synergistic response when mixed with lower inhibitory concentration of tebuconazole. The results showed that there was an additive effect in a combination of 0.1 ppm tebuconazole with 1000 ppm pure mesquitol for PP, 0.5 ppm Tebuconazole with 1000 ppm crude mesquitol and pure mesquitol for PP and 0.5 ppm tebuconazole with 1000 ppm pure mesquitol for TV. The other remaining combinations of 1000 ppm/5000 ppm of the samples with 0.1 ppm/0.5 ppm tebuconazole all had synergistic effect. This data suggests that a combination of polyphenols (catechin and extractives) with tebuconazoles can be useful sources for preparation of fungicides and wood preservatives for agricultural use and wood durability, respectively. Full article

In the current study, lavender plant (Lavandula angustifolia Mill.) waste, as obtained after the essential oils steam distillation process as well as lignocellulose biomass of two of the most common pine species (Pinus nigra L., Pinus brutia L.), was characterized in terms of chemical composition, moisture, ash content, and calorific value, in order of its potential to be used as feedstock material in pellets production to be assessed, studying different materials ratios. The lavender material was introduced at low percentages (0, 5, 10 and 15% w/w) in the feedstock of pellets, in order to maintain the total ash content of the mixed feedstock as adequately low-lying, ensuring the classification of pellets in qualitative categories of A1, A2 and B (residential uses, ENplus). The resultant lavender–pine mixed syntheses were densified in a multi-mold pelletizing machine and the pellets were characterized with regard to physical, morphological, mechanical, hygroscopic, and thermal characteristics, based on the limits set by the respective ENplus standards as benchmarks. The results demonstrated that although lavender waste has a high content of ash and extractives compared to wood, it can be used in a mixture (<15% lavender percentage) with pure wood material to produce pellets of adequate quality for residential use. The lavender waste presence favored pellets’ mechanical strength, dimensions, hydrophobicity, dimensional stability, bulk density (marginally) and resultant quality of the pellets. Lavender slightly decreased the calorific value of pellets, though without recording a significant adverse impact. The lavender material mixed with black pinewood (at 15%) revealed the best pellets’ feedstock performance. The findings exhibited that lavender lignocellulosic residues are suitable for producing high-performance residential pellets, provided that the lavender content does not exceed 15% of the feedstock. Full article

This study examines the impact of recent climatic trends on the preservation of submerged wooden structures at the Gran Carro archaeological site in Lake Bolsena, Italy. Climatic data from the Bolsena Meteorological Station were analysed alongside in situ water quality measurements collected near the archaeological remains at a depth of 4 m. The key parameters included water temperature (Tw), redox potential (Eh), dissolved oxygen (DO), and total dissolved solids (TDS). Trend analyses using the Mann–Kendall test and Sen’s slope revealed significant increases in air and water temperatures, which were strongly correlated. Although precipitation exhibited an upward trend, its negative correlation with temperature suggests greater variability rather than a stable water supply. Despite increased rainfall, lake levels showed a significant decline, likely due to intensified evaporation and water extraction for irrigation. UAV surveys confirmed recent lowering of the lake’s water surface during drought periods. Among the limnological parameters, dissolved oxygen saturation declined significantly, while redox potential increased, indicating shifts toward more anaerobic conditions. These environmental changes could promote the activity of erosive bacteria that degrade submerged wood. Conversely, increased evaporation might also enhance oxygen penetration at depth, potentially activating decay agents such as soft rot fungi and wood-boring bacteria. Overall, the findings suggest that ongoing climatic changes are adversely affecting the preservation of submerged wooden structures, highlighting the need for adaptive management strategies to protect both the lake ecosystem and its archaeological heritage. Full article

Petroleum hydrocarbon pollution is a serious environmental and human health problem. In recent decades, the impact of this substance has been profound and persistent, affecting the balance of aquatic and terrestrial ecosystems and leading to significant physical and psychosocial effects among the population. Natural sources (crude oil, natural gas, forest fires, and volcanic eruptions) and anthropogenic (road traffic, smoking, pesticide use, oil drilling, underground water leaks, improper oil spills, industrial and mining waste water washing, etc.), the molar weight of the hydrocarbon, and the physicochemical properties are important factors in determining the degree of pollution. The effects of pollution on the environment consist of altering the fundamental structures for sustaining life (infertile lands, climate change, and loss of biodiversity). In terms of human health, diseases of the following systems occur: respiratory (asthma, bronchitis), cardiovascular (stroke, heart attack), pulmonary (infections, cancer), and premature death. To reduce contamination, sustainable intervention must be carried out in the early stages of the pollution-control process. These include physical techniques (isolation, soil vapor extraction, solvent extraction, soil washing), chemical techniques (dispersants–surfactants, chemical oxidation, solidification/stabilization, thermal desorption), biological techniques (bioremediation, phytoremediation), and indigenous absorbents (peat, straw, wood sawdust, natural zeolites, clays, hemp fibers, granular slag, Adabline II OS). Due to the significant environmental consequences, decisions regarding the treatment of contaminated sites should be made by environmental experts, who must consider factors such as treatment costs, environmental protection regulations, resource recovery, and social implications. Public awareness is also crucial, as citizens need to understand the severity of the issue. They must address the sources of pollution to develop sustainable solutions for ecosystem decontamination. By protecting the environment, we are also safeguarding human nature. Full article

The selection of tree species for afforestation in Mediterranean environments involves challenges related to adaptability, impact on soil properties, and overall environmental quality. Cupressus lusitanica has been recognized for its rapid growth, environmental resilience, and versatile applications, positioning it as a promising candidate for these regions. Although it has been used for afforestation in Northeast Portugal since the 1990s, no comprehensive studies have evaluated its performance under local conditions. To address this knowledge gap, this study assessed a 14-year-old C. lusitanica stand in Northeast Portugal. The wood’s anatomical, physical, chemical, and mechanical properties, as well as biomass production, were evaluated. The species showed superior radial growth and adaptability compared with other species under similar environmental conditions. Despite exhibiting lower fiber length (1.6 mm) and basic wood density (404 kg/m³), shrinkage values fell within the typical range for softwoods. Nevertheless, a marked tendency for warping was observed. The extractive content was relatively high (5.1%), with the ethanol-soluble fraction being predominant (3.6%). Mechanical tests revealed low values for both Modulus of Elasticity (MOE) (3592.5–3617.1 MPa) and Modulus of Rupture (MOR) (57.7–68.9 MPa), with both properties significantly influenced by knot presence. Given the results obtained, the species C. lusitanica, despite its low wood density and potential limitations in use, exhibits remarkable growth and adaptability, which confer a high potential for biomass production and carbon sequestration, as well as potential applications of its wood in reconstituted panels and fiber- or particle-based boards. Full article

Walnuts (Juglans regia L.) are recognized for their rich nutritional profile and health-promoting properties. This study investigates the impact of biostimulation, via wood distillate application, on the chemical composition and therapeutic potential of walnut kernels, focusing on their wound healing activity. Biostimulated walnuts showed enhanced levels of phenolic compounds including antioxidants, sugars, and amino acids compared to untreated or agrochemically treated controls. Phytocomplexes extracted from walnut kernels using green methodologies were tested on human keratinocytes (HaCaT), revealing pro-migratory effect, boosted by biostimulation. Molecular analyses demonstrated the activation of epithelial–mesenchymal transition (EMT) pathways, marked by downregulation of epithelial markers and upregulation of mesenchymal genes such as MMP3, MMP9, vimentin, and SMAD3. Furthermore, a synergistic effect was observed between extracts derived from biostimulated kernels and manuka honey in promoting wound closure. These findings suggest that kernels from biostimulated walnuts may serve as functional foods, paving the way for their use in regenerative medicine. Full article

This study proposes an Automatic Branch Modeling (ABM) framework that combines AdTree and AdQSM algorithms to reconstruct individual tree models and estimate timber volume from fused Hand-held Laser Scanners (HLS) and Unmanned Aerial Vehicle Laser Scanners (UAV-LS) point cloud data. The research focuses on two 50 × 50 m primary tropical rainforest plots in Hainan Island, China, characterized by dense and vertically stratified vegetation. Key steps include multi-source point cloud registration and noise removal, individual tree segmentation using the Comparative Shortest Path (CSP) algorithm, extraction of diameter at breast height (DBH) and tree height, and 3D reconstruction and volume estimation via cylindrical fitting and convex polyhedron decomposition. Results demonstrate high accuracy in parameter extraction, with DBH estimation achieving R² = 0.89–0.90, RMSE = 2.93–3.95 cm and RMSE% = 13.95–14.75%, while tree height estimation yielded R² = 0.89–0.94, RMSE = 1.26–1.81 m and RMSE% = 9.41–13.2%. Timber volume estimates showed strong agreement with binary volume models (R² = 0.90–0.94, RMSE = 0.10–0.18 m³, RMSE% = 32.33–34.65%), validated by concordance correlation coefficients (CCC) of 0.95–0.97. The fusion of HLS (ground-level trunk details) and UAV-LS (canopy structure) data significantly improved structural completeness, overcoming occlusion challenges in dense forests. This study highlights the efficacy of multi-source LiDAR fusion and 3D modeling for precise forest inventory in complex ecosystems. The ABM framework provides a scalable, non-destructive alternative to traditional methods, supporting carbon stock assessment and sustainable forest management in tropical rainforests. Future work should refine individual tree segmentation and wood-leaf separation to further enhance accuracy in heterogeneous environments. Full article