To explore the differences of community characteristics， species diversity and their coupling relationship with environment in different cold temperate coniferous forests in Daxing'an Mountains， and to provide theoretical basis and data support for the scientific management and biodiversity protection of cold temperate coniferous forests in this area. Taking the typical Larix gmelinii forest， Pinus sylvestris var. mongolica forest， Picea jezoensis forest， Picea koraiensis forest， and Pinus pumila var. pumila forest in Daxing'an Mountains as the research objects， the characteristics of tree layer， shrub layer and herb layer were investigated respectively， and the diversity index， evenness index and richness index were calculated. Redundancy analysis （RDA） was used to explore the coupling relationship between community characteristics and species diversity of five populations. The results showed that the plant species in the cold temperate coniferous forest were poor. The overall tree layer tree species type was single. The average DBH and average tree height of Pinus sylvestris var. mongolica were the highest in the five coniferous forest associations. Vaccinium vitis-idaea was the main species in the shrub layer of five coniferous forests. Deyeuxia purpurea， Pyrola asarifolia subsp. incarnata and Maianthemum bifolium were the main species in the herb layer. These five populations had significantly different diversity characteristics and had significant differences in coupling relationships. The diversity index was relatively concentrated on the left side of the second axis， and was positively correlated with tree height， DBH and number of species in each layer， but negatively correlated with altitude， canopy density， shrub layer coverage and herb layer height. Five typical cold temperate coniferous forests in the Daxing 'an Mountains have significantly different community structure and species diversity characteristics.
In order to explore the suitable ultra-dry storage conditions for the dormancy-released seeds of Fraxinus mandshurica， the dormancy-released seeds of Fraxinus mandshurica were dried to different water （4%， 3%， 2%） content at different drying rates （fast （the mass ratio of silicone to seed was 6∶1）， medium（3∶1） and slow（1∶1）， respectively）， and stored at room temperature for different times （0， 30， 90， 180， 270， 360 d）. The germination performance and physiological changes of Fraxinus mandshurica seeds after ultra-dry storage were studied using seeds stored at 5 ℃ with 7% water content as a control. The results showed that the seed germination rate of all ultra-dry storage treatments could reach more than 50% within 180 days. After ultra-dry storage for 180 days， the germination ability of the fast drying seeds was strong， and the germination rate of the seeds with high water content （4%） was the highest （72%）； the germination ability of slow drying seeds was low， and the germination rate of seeds with low water content （2%） was the lowest （50%）. After 270 days of ultra-dry storage， the seed germination rate decreased significantly， and the seed germination rate of each ultra-dry storage treatment was significantly lower than that of the control. The relative conductivity of seeds was significantly lower than that of 0 d after ultra-dry storage for 30 d and 90 d， and higher than that of 0 d after ultra-dry storage for 360 d. The MDA content of seeds with 3% and 4% water content after fast drying was lower than that of the control at 0， 90 and 270 days of storage. The ultra-dry storage of dormancy-released Fraxinus mandshurica seeds is feasible， and the treatment effect of fast drying to higher water content （4%） is better， but the ultra-dry storage time is appropriate within 180 days. After storage time of more than 270 days， the seed conductivity increases significantly， and the seed germination ability decreases significantly. Therefore， if Fraxinus mandshurica seeds are sown and used in a short term （half a year） after dormancy is released， ultra-dry storage can be used. If it is planned to be sown and used in a long term （more than one year）， it is better to store the seeds at 5 ℃ with 7% water content.
The forest canopy fixes carbon dioxide in the atmosphere through photosynthesis， and the tree trunk uses the organic matter generated by the canopy for cambium splitting and thickening. Whether the assimilation of tree canopy and the radial growth of tree trunk changed synchronously in the process of climate change is controversial， and whether the synchronous or differential changes are related to the response characteristics of these two processes to climate factors is also a hot topic of attention. In particular， the same tree species in different climatic background is still to be studied. Larix gmelinii as the main coniferous forest species in cold temperate zone of China， is sensitive to climate change. Therefore， this paper selected Greater Hinggan Mountains from south to north in the Arshan （AES）， Kudur （KDE） and Daebaeksan （DBS） as the research objects. Normalized difference vegetation index （NDVI） and ring width index （RWI） were used to represent the growth of tree canopy and trunk， respectively. Segmentation function and correlation analysis were used. The relationship between tree canopy and trunk growth and the differences in driving factors under different climate backgrounds were investigated. The main results were as follows： the rapid warming period significantly promoted the growth of tree canopy， mainly reflected in the early growing season （EGS） and the late growing season （LGS）. However， organic matter produced by photosynthesis may be more used for canopy respiration， thus inhibiting the radial growth of trees， resulting in an insignificant relationship between tree trunk and canopy growth during this period. With the slowing down of the temperature rise rate， the growth of tree canopy was mainly reflected in the middle of the growing season （MGS） and the end of the growing season （LGS）， and the relationship between tree trunk and canopy growth showed significant correlation（P<0.05）. The global temperature rise rate leads to the difference in response of forest trunk and canopy growth to climate factors， which may be the root cause of the inconsistent relationship between tree trunk and canopy growth. The acceleration of global temperature rise increases the difference between trunk and canopy growth in response to climate， and on the contrary， greatly reduces the difference between the two.
As the global climate warms， the frequency of extreme events increases， resulting in the decline and even death of some of the world's forests， and in some places the impact is more pronounced on large trees. The climate in Northeast China is gradually becoming warmer and drier， and Pinus koraiensis， as the main precious tree species in Northeast China， has already experienced a decline in the study area. However， the differences in the effects of temperature rise and extreme events on the growth of Pinus koraiensis of different diameter classes have not been studied in detail. The response of different diameter classes of Pinus koraiensis to climate change and the adaptability characteristics （resistance， resilience， restoring elasticity and relative resilience to extreme drought were analyzed and compared by dendrochronology in the natural forest area of southern Xiaoxing'anling. The results showed as follows： 1） There was a negative correlation between large diameter and the maximum temperature at the beginning of the growing season， and a positive correlation between large diameter and the precipitation in June of the same year； the minor grade was negatively correlated with the precipitation at the end of the growing season in the current year and the previous year. 2） The growth trend of large diameter class and small diameter class was basically the same， in which the response stability of large diameter class to the maximum temperature of the growing season was lower than that of small diameter class， and the growth of small diameter class was mainly affected by the decrease of precipitation. 3） With the warming of climate， the resistance and relative resilience of different diameter classes to extreme drought showed a downward trend， and the adaptability of large diameter class to drought was slightly lower than that of small diameter class， but the difference was not obvious. The difference of response to climate and the stability of response of different diameter classes of Pinus koraiensis mainly appeared in the early growing season of rapid growth， reflecting the different demand of different diameter classes for hydrothermal conditions. With the warming of climate， the adaptability of radial growth of different diameter classes of Pinus koraiensis to extreme drought events decreased， and it could not recover to the pre-drought level in the short term. It is predicted that the future climate will continue to rise， and the adaptability of large diameter class Pinus koraiensis may weaken. Further analysis should be carried out based on the frequency and time of drought， and the research scope should be expanded to deal with the adverse effects of warming on Pinus koraiensis forest， which will play an important role in forest management.
Hemicellulose acid hydrolysates contain diverse sugars， yet existing separation and purification processes remain complex. This study presents a simplified and efficient method for isolating and extracting crystalline xylose from hemicellulose hydrolysates. By leveraging the preferential selectivity of phenylboronic acid toward xylose， a xylose-boronate ester XDE intermediate was formed. Subsequent transesterification with propylene glycol in ethyl acetate enabled the precipitation of high-purity crystalline xylose. The process achieved an average xylose yield of 75% and purity up to 99.8% over five operational cycles. Notably， this green solvent-based tandem system operated at ambient temperature， eliminating industrial-scale procedures including decolorization， desalination， and recrystallization. The developed methodology demonstrates efficient xylose extraction with minimized energy consumption and environmental impact.
To enhance the weathering resistance of wood， anatase titanium dioxide was encapsulated with silica to form silica-coated anatase-type titanium dioxide （A-TiO2@SiO2）， which was then modified with a silane coupling agent to produce the modifier （KH560-TiO2@SiO2）. KH560 referred to γ-glycidoxypropyltrimethoxysilane. Fast-growing poplar wood was treated with this modifier via vacuum impregnation， and the effects of KH560-TiO2@SiO2 on the ultraviolet resistance of poplar wood were systematically evaluated. The results indicated that Ti and Si elements were introduced into the surface of the modified wood， with a significant amount of particulate matter being loaded. The treated wood exhibited a higher contact angle compared to the untreated wood， which helped to reduce the degradation caused by water in outdoor applications. The ability of the modified wood to excite hydroxyl radicals， superoxide anions， and phenoxyl radicals was reduced， while its absorbance in the UV region increased. Untreated poplar wood experienced rapid lignin degradation after UV aging， leading to photodegradation and structural deterioration. The photocatalytic properties of anatase titanium dioxide （A-TiO2） promoted the degradation of cellulose in poplar wood. However， the KH560-TiO2@SiO2 modification delayed lignin degradation while maintaining the stability of cellulose. In summary， the encapsulation treatment reduced the photocatalytic activity of A-TiO2， and the modifier acted as a UV shield while decreasing the wettability of the wood， thereby enhancing the weathering resistance of poplar wood. Fast-growing poplar wood treated with KH560-TiO2@SiO2 has the potential for outdoor applications.
Salix integra is an valuable raw material in the wickerwork industry with high economic value. However， when Salix integra is stored for extended periods， it often experiences splitting during weaving， which negatively affects production efficiency and resource utilization. In this study， polyethylene glycol （PEG） with molecular weights ranging from 600 to 6000 were used as modifiers to soften Salix integra through a vacuum impregnation process at a concentration of 20%. The effects of different PEG molecular weights on the physical and mechanical properties， chemical structure， micro morphology， and thermal stability of Salix integra were analyzed. The results demonstrated that vacuum impregnation PEG modification significantly improved the bending properties of Salix integra， with the most notable effect observed for the lower molecular weight PEG. After treatment with PEG600， the weight percentage rate and density of the Salix integra increased substantially， while its rigidity decreased and flexibility was markedly enhanced. Notably， the material exhibited exceptional resistance to splitting， as no breakage occurred even when the bending strain exceeded three times that of untreated Salix integra. This improved performance was attributed to the more effective penetration of lower molecular weight PEG into the Salix integra， which formed additional hydrogen bonds with the hydroxyl groups in cellulose fibers， thereby enhancing the bending properties of Salix integra. Furthermore， PEG modification also enhanced the thermal stability of Salix integra. In conclusion， PEG600 was the most effective modifier for softening Salix integra. This method can provide superior performance support for the utilization of Salix integra in wickerwork and other applications.
This study investigated the pore fractal characteristics of medium density fiberboard （MDF） of different thicknesses. By combining high-pressure mercury intrusion porosimetry （MIP） and nitrogen （N2） adsorption experiments， the pore structure parameters such as pore volume， pore size， and pore size distribution were quantified. Utilizing the FHH （Frenkel-Halsey-Hill） and MIP fractal theoretical models in conjunction with experimental results， the fractal dimensions of pores at different scales were calculated. The complexity of the pore structure was quantified through fractal models， revealing significant differences in the pore fractal characteristics of MDF of different thicknesses. The fractal dimensions calculated using the fractal models indicated that both the macro-pore fractal dimension （2.957-2.988） and the mesopore fractal dimension （2.602-2.851） increased significantly with increasing thickness （R 2>0.90）， suggesting that the pore structure complexity of thicker boards was higher. The influence of density （0.722-0.777 g/cm³） on the fractal dimension was relatively weak. Moreover， there was a close relationship between the fractal dimension and pore structure parameters. The macro-pore fractal dimension was positively correlated with the average pore size and porosity of the material， while the mesopore fractal dimension was negatively correlated with the average pore size and positively correlated with the specific surface area. This study reveals the pore fractal patterns dominated by thickness， providing a theoretical basis for optimizing the environmental performance of MDF through process improvement.
The macro structure， micro structure and cell morphology of the Dalbergia cultrata wood were measured and analyzed by using zoom stereromicroscope， digital microscope and image measuring analysis system， and the wood density was determined at the same time. The results showed that the wood color of the D. cultrata wood was purple red； the growth rings were obvious； the wood was scattered with holes， and the combination type of the wood vessels was mainly single vessels， a few were radial multiple vessels， and the shape of the vessel cells was mainly drum-shaped； the wood fiber cells were superimposed， with small cavity and thick， and the cell length-width ratio and wall cavity ratio were 48.84 and 0.81， respectively. The xylem rays were fine， imposed， and homomorphic 2-3 columns， with a height of 5-9 cells and a length-width ratio of 5.17. The axial parenchyma was superimposed， abundant， wing-shaped or concentric paratracheal belt-shaped； the cell length-width ratio was 6.36. Crystalline cells were mostly divided into compartments containing crystals， with as many as 17 crystalline particles.The wave pattern was slightly visible under the eye； the wood grain was straight and the structure was fine. The wood fiber and crystal cells accounted for the largest and smallest proportion of the wood tissue percentages， respectively； the wood tissue percentages could deeply understand the growth of trees and the properties of wood. The wood density was large， and the density， air-dried density and oven-dried density of the wood were 0.85， 1.04， 0.94 g/cm3， respectively. The above analysis perfected the theory of wood anatomical structure and provided theoretical basis for wood identification and appraisal.
To solve the problem that the target detection algorithm is prone to leakage and lacks detection accuracy in detecting wood surface defects， this paper proposes an improved YOLOv8 model （YOLOv8-CBW， C， B and W are abbreviations for CondSiLU， BiFPN and Wise-IoU） and constructs a self-made dataset containing various wood defects. By optimizing the original YOLOv8 algorithm and combining CondConv （conditional convolution） with SiLU （sigmoid-weighted linear unit） to form the CondSiLU module instead of the traditional convolution module， the flexibility of feature extraction is improved； the bidirectional feature pyramid network （BiFPN） is introduced to enhance the multi-scale feature fusion capability； and the Wise-IoU （weighted intersection over union） loss function replaces the CIoU （complete intersection over union） to improve the adaptability and generalization performance of the model to low-quality samples. The experimental results show that the improved YOLOv8-CBW model improves the mAP50 （mean average precision at IoU threshold 0.50） and mAP50-95（mean average precision over IoU thresholds from 0.50 to 0.95） by 3.7% and 3.9%， respectively， compared with the YOLOv8 model， and it shows higher precision and stability in complex wood defect detection tasks. The research in this paper provides new ideas for wood defect detection tasks and has good practical application prospects.
Aiming at the bottleneck problem of insufficient adaptability of traditional defect detection methods in automated wood processing industry， research on intelligent detection technology based on deep learning is carried out， and a dataset covering multi-species wood characteristics and typical defect types is proposed. Applying object detection technology to defect detection， using dilation wise residual （DWR） module to optimize C2f module， and proposing task aligned dynamic detection head （TADDH） and feature focusing spread pyramid network （FSPN） to impove YOLOv8 algorithm （DFT-YOLO）. The experimental results showed that a significant improvement in accuracy， reaching 96.8%， which was 7.9 higher than the original model. On the average accuracy of the key evaluation indicators mAP50 and mAP50-95， the impoved model reached 93.8% and 75.2%， respectively， increasing by 6.8% and 17.5%， respectively. While improving the detection accuracy， the number of parameters of the model had decreased by approximately 1/6 （16.2%）. The impoved model can provide a lightweight detection method for wood defects.
In response to the complex diversity of surface defects in plywood veneers and the difficulties in feature extraction， as well as the large number of parameters and computational costs of deep learning-based defect detection algorithms， which makes effective application on devices with lower computing power challenging， a detection model for surface defects （live knots， dead knots， holes， cracks， and notches） in veneers based on an improved YOLOv8n is constructed. To enhance the detection accuracy and lightweight performance of the model， improvements are made to the plywood veneer surface defect detection model. First， a new efficient attention mechanism （coordinate attention， CA） is adopted， which can enhance the accuracy of feature extraction and the network's spatial information perception ability while avoiding excessive computational burden； secondly， a novel structure based on partial convolution （PConv） is proposed——CSPPC （CSP（coross stage partial） pyramid convolution）， it to improve computational efficiency and the fusion capability of multi-scale features； finally， an improved weighted intersection over union loss function——WIoUv3， it is introduced， which enhances the model's localization accuracy and robustness. Experimental results show that the improved YOLOv8 model （CP-YOLOv8） performs excellently in the task of detecting surface defects in plywood veneers， achieving an average precision mean （mAP） of 93.8%， an increase of 0.9% over the original model， while reducing the model's floating-point operations （GFLOPs） and parameter count to 7.2 G and 2.58 M， respectively， a reduction of 0.9 G and 0.42 M， which can fully meet practical application needs and provide an efficient， accurate， and lightweight solution for quality inspection of plywood veneers.
Aiming at the acoustic emission （acoustic emission，AE） signals emitted from wood damage and fracture process， multifractal detrended fluctuation analysis （multifractal detrended fluctuation analysis， MF-DFA） was used to extract the characteristic parameters of the AE signals， and then to study the fractal characteristics of the micro- and macro-damage behaviors of wood. First， the AE signals generated during the three-point bending test of Zelkova schneideriana specimen were collected. Then， the AE signal were intercepted by a sliding time window and treated as a sequence of time periods. The generalized Hurst index， spectral width ， singularity index and were calculated according to the MF-DFA method to describe the long-range correlation and time-varying multifractal characteristics of the AE signal. Finally， the whole process was categorized into elastic， elastoplastic and plastic stages based on the trend of .The results showed that the AE signal released by the fracture process had long-range correlation and its fluctuation was a multifractal process. And the value of in the elastic stage was greatly reduced， which meant the multi-source characteristics in the early stage of failure； the change of elastic-plastic stage in a small range showed that the specimen had a certain stiffness； the macroscopic fracture behavior can be predicted by the time when the plastic stage dropped suddenly.
Using rubberwood as raw material， orthogonal experimental design was used to explore the influence of silver-loaded nano titanium dioxide impregnated heat treatment on the mold and corrosion resistance of rubberwood， and compared the mold and corrosion resistance， dry shrinkage and wet swelling properties of the control timber， heat-treated timber， silver-loaded nano titanium dioxide impregnated timber and silver-loaded nano titanium dioxide impregnated heat-treated timber， and the influence mechanism of different modification treatments on the physicochemical properties of the timber was revealed through the means of electron microscopy， XRD（X-ray diffraction）. The results showed that the optimal process of silver-loaded nano titanium dioxide impregnated heat treatment was 160 ℃， 2.5 h， 1.5% silver loading， 1.5 mg/mL modifier concentration， 60 min vacuum impregnation time， at this time， the modified timber had the greatest efficacy in the prevention of Aspergillus niger and Penicillium citrinum， both of them were 100%， and the modified timber had the smallest rate of quality loss under the influence of white-rot fungus and brown-rot fungus， which were 2.36% and 1.9%， respectively. Compared with the control timber， heat-treated timber and silver-loaded nano titanium dioxide impregnated timber， silver-loaded nano titanium dioxide impregnated heat-treated timber had the lowest wet swelling and dry shrinkage， the radial， tangential and volumetric water-absorbing wet swelling rate was reduced by 31.34%-36.36% compared with that of the control timber， the radial， tangential and volumetric moisture-absorbing wet swelling rate was reduced by 41.06%-61.7% compared with that of the control timber， the radial， tangential and volumetric air-drying dry shrinkage rate was reduced by up to 23.28%-32.24% compared with that of the control timber. The silver-loaded nano titanium dioxide impregnated heat treatment can realize the uniform loading of silver-loaded nano titanium dioxide particles in wood， which can comprehensively improve the mold and corrosion resistance and dimensional stability of wood， and realize the excellent wood modification effect.
Traditional methods for harvesting pinecone species face challenges such as low efficiency， high risks， and uncontrollable costs. To address real-time recognition and localization in automated pinecone harvesting， we proposed an improved YOLOv5s-7.0 （you only look once） object detection model and construct a binocular depth camera-based detection and localization network. To improve the accuracy and efficiency of object detection， the YOLOv5s model was improved by embedding partial convolutions （PConv） into the neck module's multi-branch stacked structure to enhance sparse feature processing capability， improve robustness， and reduce feature redundancy in complex scenarios of pinecones. Additionally， the simple attention mechanism （SimAM） was integrated at deep backbone layers and backbone-neck connections to optimize the model’s feature extraction ability and information transmission efficiency in complex backgrounds without significant parameter increases. To meet the requirements of efficient detection and localization， a target detection and real-time localization code was developed using binocular vision principles and the improved YOLOv5s model， and a pinecone detection and localization system was constructed through depth matching. Based on the constructed dataset of Pinus sylvestris var. mongolica cones from the Greater Khingan Mountains and Pinus koraiensis cones from the Lesser Khingan Mountains， the improved YOLOv5s model achieved a precision of 96.8%， a recall of 94.0%， and an average precision （AP） of 96.3% in target detection tasks. The proposed pinecone detection and localization system demonstrated mean absolute errors of 0.644 cm， 0.620 cm， and 0.740 cm along the x-， y-， and z-axes， respectively. Under front， side， and backlighting conditions， the localization success rate reached 93.3%， while in low-light environments， it maintained a success rate of 83.3%. Other performance indicators， including field of view， meet the operational requirements for pinecone harvesting. The proposed pinecone detection and localization system provides a reliable solution for real-time target detection and localization problems in mechanized pinecone harvesting.
In order to explore the influence of slab density and moisture content of medium density fiberboard（MDF） on the spacing error of hot pressing plate in the entrance section of continuous press， the related experiments of slab density and moisture content of 7.7 mm（thin plate） and 16 mm（thick plate） MDF on the spacing error of hot pressing plate at four hot pressing positions in the entrance section were carried out. Combined with the actual production situation of two kinds of fiberboard slabs at the first hot pressing position， the prediction models of the influence of slab density and moisture content on the spacing error of hot pressing plate were established respectively. The experimental results showed that the hot pressing plate spacing error was positively correlated with the density of the two kinds of slabs and negatively correlated with the moisture content. The relative error of the predicted value of the 2 models was within 5 %， and the prediction effect was good. It can effectively predict the spacing error of hot pressing plate caused by different slab density and moisture content. The research results provide some reference and reference for the precise control of slab thickness in hot pressing process.
In recent years， biomass pyrolysis equipment has emerged as a focal point of research in the global energy sector. To tackle challenges such as uneven material heating and accumulation at the tail section commonly observed in fixed-bed pyrolysis systems， this study focuses on optimizing and analyzing the performance of spiral combined flights， a key component in fixed-bed reactors. A novel variable-pitch combined flights structure was designed， and its critical parameters were systematically determined. Using Altair EDEM simulations， the effects of rotational speed and equipment inclination angle on the discharge rate were evaluated， and the simulation outcomes were validated through experiments. Simulation results demonstrated that the variable-pitch combined flights structure effectively lifted materials and redirected tail-end accumulation towards the discharge outlet， enabling uniform heating and resolving the issue of particle buildup at the tail. Meanwhile， the inclination angle exerted a significantly stronger influence on the discharge rate， with a between-group to within-group mean square ratio of 240.00， far surpassing the ratio of 25.60 observed for rotational speed. Experimental results aligned closely with the simulations， yielding a correlation coefficient of 0.998 7.
The amplification circuit represents a pivotal component within the domain of forestry intelligent equipment， with its functionality exerting a direct influence on the efficacy with which weak signals are monitored within forestry monitoring applications. High-performance discrete amplification circuits are complex in structure， and the traditional manual selection of discrete component parameters in analogue circuits is inefficient and difficult to meet the requirements of low noise and high stability in fields such as forest fire monitoring and wood defect detection. The purpose of this paper is to propose an automatic parameter optimization method for discrete components in circuits based on the nondominated sorting genetic algorithm Ⅱ （NSGA-Ⅱ）. Firstly， a parameter optimization model of the amplifier circuit is established， and design indicators are proposed in accordance with the requirements. Next， NSGA-Ⅱ is used to solve the circuit parameters. Finally， the optimization results are verified by comparing NSGA-Ⅱ with manual methods， particle swarm algorithms， vortex search algorithms and genetic algorithms through simulation and physical testing of circuit boards. The experimental findings demonstrate that the NSGA-Ⅱ circuit parameter optimization method proposed in this study exhibits a substantial superiority over manual approaches in terms of circuit performance. In comparison with classical single-objective optimization， it also possesses advantages in terms of convergence speed and optimization stability. This method provides an efficient solution for the design of high-precision amplification circuits for forestry sensors， and it can be expanded to encompass the design optimization of other forestry equipment circuits in the future.
To address the issues of low efficiency， high labor cost， and safety risks associated with manual harvesting of deep-striped walnuts in Yunnan， and to provide a theoretical basis for the design of deep-striped walnuts branch-shaking harvesting equipment， a study on the vibration parameters for deep-striped walnut harvesting was conducted. A dynamic model for vibration-based harvesting of deep-striped walnuts was established， and the primary factors affecting harvesting performance were analyzed. Through static and dynamic detachment force tests， the operational parameter range for deep-striped walnuts vibration harvesting was determined. A multi-factor horizontal vibration experiment was designed to identify the optimal parameter combination for the branch-shaking harvesting device.The results showed that the primary factors affecting deep-striped walnut detachment， in descending order of influence， were excitation position， vibration frequency， and amplitude. Measurements indicated that the axial detachment force ranged from 18.2 to 24.8 N， the bending force from 4.0 to 61.4 N， and the inertial force from 5.1 to 42.3 N. Analysis revealed that bending fracture was the main detachment mode. Optimization analysis of the regression model yielded the optimal parameter combination： vibration frequency of 7 Hz， amplitude of 92 mm， and excitation position at 0.6 l （where l was the total length of the lateral branch）， under which the harvesting efficiency of deep-striped walnuts reached 95.7%.
To solve the problems of low efficiency， high labor intensity， and poor working environment in plywood production， a surface defect repair equipment for plywood based on visual detection and automation control technology to improve the surface quality and production efficiency of plywood was designed. The equipment mainly included a visual detection and intelligent control system， a positioning system， an extrusion system， and a repairing mechanism. The visual detection and intelligent control system identified the size and position of defects through visual detection technology and generated corresponding G-code instructions （the most widely used CNC programming language for computer numerical control machines）， which were transmitted to the positioning system and extrusion system. The positioning system used the CoreXY mechanism （dual motor drive （Motors M1 and M2）， timing belt drive， X-shaped structure）， and the system received the instructions and controls the repairing mechanism to determine the defect repair point through the coordination of M1， M2， and Z motors. The putty extrusion machine of the extrusion system was used to realize stable extrusion and even coverage of the putty at the defect site. The test showed that the detection accuracy of the equipment for holes， cracks and other defects reached 97.1% and 70.6% respectively， which can effectively cover the surface defects of the plywood and avoid large areas of coating. The repaired plywood is superior to manual repair in terms of putty residue， usage and repair time， providing an effective solution for the automatic repair of the plywood processing industry.
