The excessive consumption of fossil fuels has precipitated a global energy and environmental crisis， propelling the development of green renewable energy materials into a research hotspot. Wood， owing to its multiscale structural designability and renewability， holds significant application potential across various environmental energy harvesting and conversion domains. This paper systematically integrates the functional development and application progress of wood-based energy materials. By examining the mechanisms， structural regulation strategies， and key performance characteristics for harnessing diverse natural energies—including solar thermal， hydropower， mechanical energy， and thermal radiation—it outlines material design approaches for different application scenarios. Through summarizing multi-energy coupling mechanisms， interfacial regulation pathways， and cross-scale structural construction methods， the paper identifies the inherent advantages of wood-based materials in achieving multi-energy conversion. Building upon this foundation， the paper explores the application potential of wood-based energy materials in distributed energy supply， water resource utilization， environmental thermal management， and electrical signal processing. The review concludes by proposing key future development directions for wood-based energy materials， including structural durability， functional integration， and scalable manufacturing， providing guidance for their further application within green energy systems.
Asphalt pavements often deteriorate under traffic loads and environmental factors， which shortens their service life and jeopardizes road safety. Plant fibers， which are lightweight， high-strength， abundant， and low-cost， serve as sustainable reinforcements in asphalt mixtures. They improve mechanical performance while reducing cracking and aggregate displacement. This paper introduces the classification and physical properties of plant fibers， summarizes surface treatment methods to address their hydrophilicity and improve fiber-asphalt interfacial bonding， and reviews the rheological properties at high and low temperature， fatigue resistance of plant fiber-reinforced asphalt binders， as well as the preparation techniques and pavement performance of asphalt mixtures. Future research should integrate intelligent mix design optimization， multi-scale interfacial mechanism studies， and standardized engineering systems to synergistically advance the high performance， functionalization， and green sustainable development of plant fiber-reinforced asphalt pavement materials.
Based on the measured data of 5 fixed plots， the relationship between plant diversity and stand spatial structure in five forest types of Betula platyphylla forest， Pinus koraiensis-Abies-Picea forest， Pinus koraiensis-broadleaved mixed forest， Hard broad-leaved forest and Picea-Abies forest in Langxiang National Nature Reserve of Xiaoxing'an Mountains was studied. Three indexes of uniform angle index， size ratio index and mingling index were used to describe the stand spatial structure， and three indexes of Simpson diversity index， Shannon-Wiener diversity index and Pielou evenness index were used to describe the plant diversity. On this basis， the correlation analysis was used to explore the influence of different stand spatial structures on plant diversity， and the domain structure factors affecting plant diversity were found out. The results showed that there was no significant difference in the uniform angle index and size ratio index among the five forests. There was a significant difference in the mingling index between Pinus koraiensis-Abies-Picea forest and hard broad-leaved forest （P<0.05）， but the five forests all formed a mixed， aggregated and competitive growth state. The species composition of woody plants in each stand was rich. The tree layer of the Pinus koraiensis-broadleaved mixed forest has the highest Shannon-Wiener index， Simpson index， and Pielou index， while the shrub layer of the Picea-Abies forest has the highest Shannon-Wiener index. and the Pielou index of the shrub layer of Pinus koraiensis-Abies-Picea forest was the highest. The Shannon-Wiener index and Simpson index of the tree layer in the Betula platyphylla forest were significantly negatively correlated with the Pielou index of the shrub layer. The Shannon-Wiener index of the tree layer in Pinus koraiensis-Abies-Picea forest was significantly positively correlated with the Simpson index of the herb layer. The Pielou index of the tree layer in Pinus koraiensis-broadleaved mixed forest， was significantly negatively correlated with the Shannon-Wiener index of the shrub layer. The Simpson index of the tree layer in the hard broad-leaved forest was significantly positively correlated with the Pielou index of the herb layer. There was a significant positive correlation between Shannon-Wiener and Pielou index in shrub layer of Picea-Abies forest. Different stand spatial structure indexes have different effects on plant diversity， and the most important factor is mingling index. The higher the mingling index， the richer the diversity. Through this study， we hope to provide guidance for the diversity protection of protected areas.
This study examines how different types of plantations （pure and mixed forests） affect soil hydrological properties and nutrient status in the hilly region of South-central Shandong， located in the lower Yellow River Basin. The goal is to provide a scientific basis for optimizing the management of soil and water conservation forests. Five typical plantation forest types were selected： Quercus acutissima pure forest （ML）， Robinia pseudoacacia pure forest （CH）， Pinus tabuliformis pure forest （YS）， broad-leaved mixed forest （KYH： Q.acutissima × R.pseudoacacia）， and coniferous-broadleaved mixed forest （ZKH： P.tabuliformis × Q.acutissima）. Through field sampling and laboratory analysis， several soil indicators were systematically measured， including bulk density， porosity， water-holding capacity， pH， organic carbon， nitrogen， phosphorus， and potassium. The results indicated that the Robinia pseudoacacia pure forest had the highest soil water-holding capacity （field capacity of 52.6%） and high porosity， but poor soil aeration. In contrast， the Pinus tabuliformis pure forest demonstrated lower levels of aeration and water-holding capacity. Mixed forests showed a more balanced performance between water retention and aeration， with the coniferous-broadleaved mixed forest showing a water-holding capacity close to that of the Robinia pseudoacacia pure forest. In terms of nutrients， the broad-leaved mixed forest significantly outperformed the pure forests， with levels of organic carbon （27.58 g·kg-1）， total nitrogen （4.76 g·kg-1）， and available nutrients. Overall， mixed forests， particularly broad-leaved mixed forest， exhibited superior soil functions regarding the balance between water retention and aeration as well as nutrient supply. Therefore， mixed afforestation models are recommended for ecological restoration in this region to achieve the dual goals of soil and water conservation and the enhancement of soil fertility.
Water is the main limiting factor for plant growth and survival in the southern edge of Horqin Sandy Land. Stem sap flow is an important basis for reflecting the physiological activities of trees and estimating water consumption per plant. This study investigated the sap flow rate of the sand-fixing shrub Lespedeza bicolor and its response mechanisms to environmental factors， aiming to provide a scientific basis and reference for formulating water use strategies and management measures for local Lespedeza bicolor populations. The experimental results showed that the average flow rate of L.bicolor during the observation period was 446.38 g/d. The diurnal variation pattern of sap flow in L.bicolor showed a bimodal "midday depression" phenomenon， with the timing of the midday depression advancing by 1 hour as the months progress from July to October. The average flow velocity at night was 0.045 g/h， and its contribution to the total daily flow was very low， at 0.077%. The flow velocity of the stem sap of L.bicolor was positively correlated with total solar radiation， temperature， wind speed， soil temperature， and vapor pressure deficit， and negatively correlated with relative humidity and precipitation. Among the above environmental factors， the vapor pressure deficit had the greatest impact on the sap flow of L.bicolor， with a contribution rate as high as 89.78%. There was an obvious threshold effect in the relationship between the two. The inflection point of the vapor pressure deficit liquid flow velocity relationship curve was 0.719 kPa， and the upper limit of the liquid flow velocity threshold was 111.85 g/h. Understanding the characteristics of transpiration water consumption and its response mechanisms to environmental factors in sandy-land L.bicolor can facilitate the comprehension of eco-hydrological processes of sandy-land L.bicolor under climate change， and provide a scientific theoretical basis for optimizing stand structure and managing stand resources in the study area.
Vegetation ecological quality is a fundamental element characterizing terrestrial vegetation landscapes， and its changes exert a profound impact on the energy flow and material cycle of global and regional ecosystems. This study takes Heilongjiang Province as the research area and estimates the fractional vegetation cover （FVC） and net primary productivity （NPP） based on Landsat series data， meteorological data， and land use data. Subsequently， a vegetation ecological quality index （VEQI） is constructed to analyze the temporal variation characteristics of VEQI from 2000 to 2020. Furthermore， the optimal parameter-based geographical detector model is employed to explore the driving mechanisms of the spatial differentiation of VEQI in relation to topographic， soil， climatic， and anthropogenic factors. The results show that from 2000 to 2020， the annual average vegetation ecological quality index in Heilongjiang Province showed a significant upward trend （with an annual increase of 0.56）； all four categories of factors can effectively explain the spatial differentiation of the vegetation ecological quality index. Soil bulk density， monthly average temperature in the growing season， soil acidity and elevation are the main influencing factors for the spatial differentiation of the vegetation ecological quality index in Heilongjiang Province. The synergistic effect of population density and slope aspect had a strong non-linear impact on the spatial differentiation of vegetation ecological quality index.
In Dehua pear cultivation， manual picking is inefficient， with labor costs exceeding 15% per mu. Traditional mechanical picking， due to the rigidity of its equipment， often results in a fruit breakage rate exceeding 20%， making it difficult to adapt to the thin skin （0.2-0.3 mm） and crispy flesh of the pear. To address this industry pain point， this paper designs an integrated harvesting robot system using a ‘bionic end effector+YOLOv11 visual positioning’ approach. The core of the system consists of a six-degree-of-freedom robotic arm， a binocular depth camera， and an electrically driven， separate end effector. The actuator utilizes a three-finger flexible gripping and shearing mechanism， balancing non-destructive grasping with precise stalk severing. The visual system， based on YOLOv11， introduces the C2PSA attention module to enhance the distinction between fruit and leaf features， and combines it with a binocular camera for three-dimensional positioning. Experiments based on samples from a pear orchard in Dehua， Fujian， show that the recall rate for the ‘pear’ category remained above 0.85 at a confidence level≥0.7， with an optimal F1 value of 0.83 （confidence level 0.565） and a stable mAP50 of 0.87. Field tests also demonstrate that the system achieved four times the efficiency of manual picking， while keeping the fruit breakage rate below 5%. This solution provides technical support for automated Dehua pear harvesting， and its design principles are valuable for the development of harvesting equipment for fragile fruits such as peaches and strawberries.
Aiming at the problems of low harvesting efficiency and high risk of tree damage caused by the fixed excitation force of the traditional walnut harvester's vibration mechanism and its difficulty in adapting to different diameter grades of fruit trees， a vibration mechanism with controllable excitation force was designed. This mechanism adopted two motors to independently drive two sets of fan-shaped eccentric blocks in combination， generating three adjustable theoretical excitation forces. The excitation force was dynamically matched with the tree trunk diameter through real-time detection by a depth camera. A three-dimensional model of the vibration mechanism was established in SolidWorks， and the eccentric blocks were designed through parametric calculation. The performance of the mechanism was verified by finite element analysis and the automatic dynamic analysis of mechanical systems （ADAMS）. The tree trunk diameter was identified by combining the point cloud data of the depth camera with the least squares cylindrical fitting algorithm based on random sample consensus （RANSAC）. The results showed that the actual excitation forces of the three gears obtained by ADAMS software simulation were 12.40， 18.82， and 31.22 kN， with a relative error of no more than 0.80% compared with the theoretical values. ANSYS （analysis system） software analysis of the eccentric blocks showed that the modal frequency range was 755.36 to 3，983.60 Hz， effectively avoiding the working frequency of 16 Hz. The relative error tail mean of the tree trunk diameter identification algorithm verified in the field was 1.63%. The field simulation system realized the closed-loop control of “diameter grade-excitation force-amplitude”. This vibration mechanism can accurately generate three target excitation forces， has a reliable structure， and can adaptively adjust the excitation force through the input of tree trunk diameter， providing a new idea for the intelligent upgrade of forest fruit harvesting equipment.
To enhancethe efficiency of classification， stacking and packaging of customized door and window materials， the mechanism trajectory and motion characteristics of double-beam stacker are designed and analyzed. Aiming at the dynamic interference problem of motion trajectory generated by the double-beam stacker during the stacking process， this paper proposes a discriminant analysis method based on the optimal feasibility of relative positions. On this basis， different motion strategies are formulated for different motion characteristics， and a collaborative planning model of the double-beam stacker is constructed. The trajectory motion characteristics are analyzed through standardized kinematic modeling to complete the optimization of the feasibility planning model. A kinematic model is established by combining ADAMS with Matlab Simulink， and the simulation verification of the manipulator's planning model is carried out. Numerical analysis and verification of the solution set of the motion model using the system simulation technology of ADAMS and Simulink show that the displacement trajectories of the two manipulators along the x-axis have no overlapping regions， which effectively avoids the risk of interference and collision. The velocity curve is continuous without abrupt changes， and the acceleration is concentrated in the range of 2-4 m/s²， which confirms the effectiveness of the established motion model. The dual-manipulator motion planning model established in this study can effectively enhance the efficiency of the classification and stacking process of door and window materials， and has high reliability. The model is of great significance for promoting the intelligent classification， stacking and packaging of customized door and window materials.
Mine ecological restoration faces challenges such as complex terrain， poor soil quality， low efficiency， and a lack of specialized equipment. This study aims to develop a new， efficient， low-cost， and mechanization-friendly vegetation restoration method for mines to overcome the limitations of traditional techniques. An innovative vegetation restoration strategy for mining areas is proposed. The device of this strategy consists of two modules： a breeding rope and a laying device. The breeding rope can be pre-produced standardized in factories and then deployed at vegetation restoration sites using the laying device. The effectiveness of afforestation restoration is compared in terms of efficiency and economic benefits. The study demonstrates that the new method achieves a planting efficiency of 200-260 m²/h， with a comprehensive cost of approximately RMB 50 per square meter. In mine restoration， the new method requires less time compared to techniques such as spray seeding with mesh reinforcement， with its advantages becoming more pronounced on steeper slopes. Kinetic simulations verifies the reliability of the core components of the equipment： the working torque of the drive shaft is less than 12.2 kN·m， meeting strength design requirements， and the maximum load of the hydraulic system is less than 25 kN with sufficient margin. The breeding rope technology and its supporting equipment provide a quantifiable and scalable efficient solution for mine ecological restoration. This approach significantly enhances afforestation efficiency and economic benefits， playing a crucial role in advancing the transformation of mine greening from manual methods to mechanized and large-scale operations.
The aim of this research was to address the issues of poor terrain adaptability and low cutting efficiency of the Acanthopanax senticosu brush cutting equipment. Design an in-forest circular saw type Acanthopanax senticosu brush cutter mounted on the front of a tractor. Through structural design， it was clarified that the entire machine consisted of four core mechanisms： support adjustment， transmission，brush cutting and feeding. The support adjustment mechanism and feeding mechanism were developed， and the motion trajectory and cutting force of the circular saw blade in the cutting mechanism were analyzed to validate that its power met the requirements. Field experiments were conducted with the rotational speed of the circular saw， traveling speed， and cutting height as influencing factors， and the experimental data were processed using data processing software. The results indicated that traveling speed had the greatest impact on the cutting efficiency of the brush cutter， followed by the rotational speed of the circular saw， while cutting height had the least effect. Using Design-Expert13 software， a regression model for cut rate was constructed and parameters were optimized. It was obtained that the influence degrees of each factor on the cut rate from large to small were the traveling speed， the rotational speed of the circular saw， and the cutting height. When the rotational speed of the circular saw was 1 925 r/min， the traveling speed was 4.2 km/h， and the cutting height was 39.6 cm， the cut rate reached 99.4%， resulting in the best cutting performance. This equipment can meet the efficient brush cutting needs of Acanthopanax senticosus in complex forest terrain， providing technical support for mechanized pruning in large-scale Acanthopanax senticosus planting.
In order to solve the problems of low excavation rate， large soil reflux and complicated manual secondary soil clearing work in the working process of Camellia oleifera digging machine， according to the structure of the existing Camellia oleifera digging machine， EDEM simulation and experimental research were used to optimize the parameters of the machine and improve the excavation rate of the pit. Taking the large-diameter pit drilling bit suitable for the complex site environment of hilly and mountainous areas as the research object， the large-diameter drilling technology scheme of Camellia oleifera was proposed， and a large-diameter drilling bit with high excavation rate was designed. The main components of the digging bit were modeled， and the soil was modeled by combining EDEM2023 software， and the working process of the pit digging was simulated. Taking the excavation rate of the drilling device as the evaluation index， and the diameter of the drill rod， the spiral rising angle and the static friction factor of the soil-fin as the test factors， the single factor test was carried out to determine the value range of the three parameters. On this basis， multi-factor orthogonal experiments were carried out to determine the optimal combination of parameters for the excavation rate. The results of single factor test showed that the diameter of the drill rod of the drilling device increased from 80mm to 120 mm， and the excavation rate showed a downward trend. The spiral rise angle of the fin increased from 15° to 23°， and the excavation rate showed a downward trend. The static friction coefficient between the soil and the fin increased from 0.50 to 0.60， and the excavation rate showed a trend of first increasing and then decreasing. Among the three， the spiral angle had the greatest influence on the excavation rate， and the diameter of the drill rod had the least influence on the excavation rate. The results of the quadratic regression orthogonal rotation combination test showed that the influence order of the three factors on the excavation rate of the digging machine was the spiral rising angle>the static friction coefficient > the diameter of the drill rod， the diameter of the drill rod was 82 mm， the spiral rise angle was 23°， and the static friction factor was 0.56， and the excavation rate was 92.73% under the combination of this parameter.
Aiming at the problem of insufficient image segmentation accuracy caused by fuzzy edge and texture interference of surface defects in automatic production of wood processing， an improved ivy algorithm （IIVY） is proposed for multi-threshold segmentation of wood defect images. Firstly， the population diversity is enhanced by the wind direction growth mechanism， and a nonlinear dynamic balance factor is designed to dynamically coordinate the global exploration and local development capabilities. Secondly， the elite-oriented regeneration strategy is introduced to improve the ability of the algorithm to jump out of the local optimum. Then， the fitness function is designed based on symmetric cross entropy， and the wood defect image is segmented by IIVY. Compared with four classical algorithms （grey wolf optimizer （GWO）， whale optimization algorithm （WOA）， sparrow search algorithm （SSA） and sand cat swarm optimization （SCSO）， the evaluation indexes include optimal fitness value， peak signal-to-noise ratio， feature similarity and subjective visual evaluation. The results show that the IIVY fitness convergence curve is significantly better than the comparison algorithm； in terms of peak signal-to-noise ratio and feature similarity index， the number of test groups in which IIVY achieved the optimal value accounted for 83.33% and 91.67% of the total number of test groups， respectively. IIVY is more accurate in the segmentation of the edge of the defect area， and the segmentation results completely retain the wood texture details. The IIVY algorithm can accurately segment the wood surface defects， retain the texture features of the wood surface， and provide reliable technical support for wood defect detection.
Aiming at the problems of multi-scale defects， complex background interference and small target leakage in wood surface defect detection， a multiscale feature aggregation wood defect detection algorithm PADDL-YOLO is proposed based on YOLOV11n （PADDL is a multiscale feature aggregation algorithm consisting of PMSFA （partial multi-scale feature aggregation）， ADown （average pooling down sampling）， DySample （dynamic upsampler）， DPB （dynamic position bias） and LSDECD （lightweight shared detail-enhanced convolutional detection））. First， a partial multi-scale feature aggregation （PMSFA） module is designed to enhance multiscale defect feature extraction. Second， the use of average pooling down sampling （ADown） with a dynamic upsampler （DySample） reduces information loss while reducing computational complexity and improves the model's ability to detect small targets. Then， the dynamic position bias （DPB） module is introduced into the attention mechanism to enhance the C2PSA module， strengthening spatial position awareness and significantly improving defect localization accuracy. Additionally， a lightweight shared detail-enhanced convolutional detection （LSDECD） is designed， employing detail-enhanced convolution to reinforce edge feature capture. Experiments demonstrate that PADDL-YOLO achieves outstanding performance in wood defect detection， with a precision of 91.5%， recall of 91.4%， and mAP@0.5 of 95.0%， representing improvements of 5.2%， 4.9%， and 3.8%， respectively， over the baseline model YOLOV11n. Meanwhile， the model's parameter count is reduced by 25.6%， and computational efficiency is significantly enhanced， providing an effective solution for high-precision real-time detection.
To address the low detection accuracy of existing methods under complex wood texture conditions， this paper proposes an improved YOLOv8s-based approach for wood defect detection. First， an efficient multi-scale attention （EMA） mechanism is embedded into the backbone network to enhance the model’s contextual perception capability in complex texture scenarios. Second， the neck network is redesigned as a re-parameterized generalized feature pyramid network （RepGFPN） to strengthen cross-scale feature fusion. Third， the loss function is replaced with SCYLLA-IoU （SIoU） to improve bounding box regression precision. Finally， the inverted residual mobile block （iRMB） is integrated into the C2f module， improving the model’s ability to capture fine-grained defects. Experimental results demonstrate that the proposed method outperforms the baseline by 5.09% in precision， 3.13% in recall， 3.72% in mAP@0.5， and 2.63% in mAP@0.5：0.95， while achieving a real-time inference speed of 120 frames per second. These findings indicate that the proposed enhancements significantly improve the model’s robustness and generalization capability， leading to superior and more stable performance in complex wood defect detection tasks.
In this study， the mechanism of vegetation on slope scouring protection was explored by combining numerical simulation and macroscopic experiments. Firstly， an artificial test bench was built to conduct practical tests on the slope with or without vegetation cover. Subsequently， numerical simulations were used to simulate the slope scouring process under different vegetation conditions. The experiment results showed that the vegetation could effectively protect the slope， reduce the scouring rate， and the protection effect had strong adaptability， and the simulation results were consistent with the change law and trend of the experimental results， which verified the reliability of the numerical simulation results. The results further showed that vegetation had an important impact on slope stability under different scouring durations. It was verified that the vegetation can improve the stability of the slope through the synergistic effect of leaves， stems and roots through numerical simulation and experimental analysis. Vegetation plays an important role in slope scouring protection
Forest roads are prone to developing defects such as cracks and potholes due to their natural environmental conditions and the heavy vehicle loads they carry， resulting in poor road conditions and high maintenance costs. To address the challenges of inaccurate target detection bounding boxes， significant scale variations of pavement distresses under UAV perspectives， and insufficient lighting conditions， a bimodal asphalt pavement distress detection method （bimodal integrated road getection YOLOv8， BIRD-YOLOv8） was proposed. It employed an intermediate fusion strategy combining visible and infrared images. The DynaSpectra fusion module （DSFM）， constructed by serially connecting adaptive fine-grained channel attention （FCAttention） and linear deformable convolution （LDConv）， replaced the C2f structure in BIRD-YOLOv8's backbone network， enhancing feature extraction capability for distress areas. Normalized Wasserstein distance loss （NWDLoss） was introduced to replace CIoU， strengthening the model's detection ability for small-scale distresses. Experimental results showed that the improved algorithm achieved an mAP of 83.3%， with AP values for transverse cracks， longitudinal cracks， alligator cracks， and potholes reaching 88%， 91.3%， 90.5%， and 63.5%， respectively， laying a foundation for the identification and maintenance of pavement distresses in forest roads.
