Wood and its products are widely used in people’s daily life， including furniture manufacturing， interior decoration， construction and other fields. The total annual output value of the wood industry has exceeded 3 trillion yuan， which is an important basic industry of the national economy. However， there are still problems such as low added value of products， weak innovation ability of enterprise， and decentralized production supply chain in the process of wood industry development. Starting towards the new and green departure， incubating new technologies and materials for functional wood manufacturing， and cultivating new productivity in the wood industry are important directions to boost the wood industry development and accumulatively achieve low-carbon transformation. This paper focuses on the frontier development direction of wood science， discusses the important quality productivity of wood industry， and clarifies the importance of scientific and technological innovation for wood industry development. Furthermore， this paper puts forward four directions for the future development of wood science， including the micro in-depth， the macro expansion， the extreme conditions， and the comprehensiveness， and summarizes the newly representative research results， sorts out the development status and trend of the representative wood new products and functional new materials， and lays the foundation for further proposing the development path of new quality productivity in China's wood industry.

The Larix gmelinii forests is one of the most important forest types in Northeast China， playing a crucial role in maintaining the stability of the forest ecosystem in the region. The woody plants in the permanent plot of Larix gmelinii forests in Northeast China were taken as the research object. Through field plot investigation， diversity index and spatial structure characteristics calculation， combined with variance partitioning analysis and redundancy analysis， this study explored the characteristics and influencing factors of tree species diversity in Larix gmelinii forests. The results showed that the average tree species richness of Larix gmelinii forests was 10.75 in Northeast China， Simpson index was 0.72， Shannon-Wiener index was 1.69， and Pielou evenness index was 0.76. The average mingling intensity was 0.57， indicating that the forest stands were moderately mixed. The uniform angle index was 0.54， and the forest stands were clustered. The breast diameter dominance was 0.51， indicating that the forest growth was in a moderate state. The spatial structure characteristics of forest stands and geoclimatic conditions jointly explained 35.9% of the changes in tree species diversity， followed by spatial structure characteristics， with an explanatory rate of 29.2%. Simple term effects showed that spatial structure and geoclimatic indicators such as mingling intensity， latitude， annual mean temperature， and annual mean precipitation were the main influencing factors of tree species diversity changes. The research results will provide theoretical basis and data support for the formulation of management strategies for Larix gmelinii forests in Northeast China.

In order to solve the problems of conventional radiative cooling devices limited by the theoretical cooling power limit of 150 W/m² and by the inhibition of radiant power by low-temperature condensate on the radiant surface and the intrinsic water under high humidity conditions， an asymmetric functional structure design based on unidirectional liquid transport proposes a passively cooled wood （REW） with radiative refrigeration and evaporative cooling integrated in series. The wood is delignified by a sodium chlorite solution to enhance its hydrophilicity； then a hydrophobic silica/epoxy solution with high reflectivity and infrared emission properties is coated on the top of the hydrophilic wood to form a hydrophobic radiative cooling layer， while the hydrophilic wood at the bottom serves as an evaporative cooling layer. By virtue of the asymmetric wetting design with unidirectional water transport， low-temperature condensate can be spontaneously transported through the radiation-cooling layer to the evaporative-cooling layer for evaporative cooling， whereas the native water in the evaporative-cooling layer is unable to pass through the radiation-cooling layer to inhibit radiation. As a result， based on the tandem integration of radiant-evaporative cooling， the REW achieves a maximum cooling power of 214 W/m² during daytime， and 172 W/m² even at high humidity of 80%， which is more than 2.8 times higher than that of radiant cooling alone. The potential application of REW in energy-efficient cooling of buildings is demonstrated through building models， providing a universal optimisation strategy for expanding the practical application of passive cooling and new insights into the functional utilisation of wood resources.

The moisture content of forest floor litter is a key factor in forest fire occurrences， and its accurate detection is crucial for fire prevention. Near-infrared spectroscopy （NIRS） can directly invert moisture content from spectral data， enabling rapid detection of litter moisture content. However， spectral characteristics differ between fuel types due to variations in light intensity data at different wavelengths， requiring separate detection models for litter from different tree species to match specific light intensity-moisture content inversion relationships. Collecting and labeling spectral data across different forest stands is time-consuming， limiting the practical application of the spectral method. To address this issue， this study proposes a moisture content detection method for forest floor litter based on Bi-LSTM （Bidirectional Long Short-Term Memory） transfer learning. By transferring the trained model parameters to new models， we avoid training models from scratch， thereby improving model learning efficiency and reducing the data required for training. The study demonstrates that the Bi-LSTM method surpasses the traditional inversion approach using LSTM in terms of detection accuracy. Specifically， the mean absolute error （MAE） for Quercus mongolica and Larix gmelinii is reduced by 0.62% and 0.87%， respectively， while the mean squared error （MSE） is reduced by 0.28% and 0.70%， respectively. Moreover， the Bi-LSTM-based transfer learning approach significantly lessens the reliance on labeled NIR spectral data. With a target domain sample size of 300 and a source domain sample size of 1 000， the detection model record an MAE of 3.27%， an MSE of 1.10%， and an R² of 0.918. When compared to models without source domain training， the MAE and MSE show reductions of 2.36% and 1.02%， respectively， and an increase in R² of 0.114. A comparative analysis before and after implementing transfer learning reveals that this methodology offers a novel strategy to diminish the time cost associated with modeling moisture content in spectral litter and to enhance the practical application of spectral detection.

By conducting multi-point regional trials on introduced Kazakhstan birch， analyzing its adaptability， screening out good family lines， and providing a theoretical basis for the selection and application of introduced birch family lines. In this study， we analyzed the genetic variation patterns of tree height， diameter at breast height （DBD）， volume of timber， straightness and other traits in 23 11-year-old Kazakhstani birch family lines and two Chinese birch family lines of the Mao'ershan seed source， which were planted in Daqing， Heilongjiang Province， Shangzhi， Heilongjiang Province， and Jinzhou City， Liaoning Province， and fitted a mixed linear model with heteroscedasticity by using the software package R-language ASReml4.0. Best linear unbiased prediction （BLUP） method was used to obtain the breeding values of each family line at different test locations， and combined with Genotype main effects and genotype × environment interaction （GGE） bisplot plots for comprehensive evaluation and selection of each participant and family line. In the mixed-effects model with location as a fixed effect， it was found that the environmental effects were significant among locations， and growth traits reached significant differences （P<0.05， （Z ratio）>1.5） among locations and among family lines within the same test site； family line No. 17 in the Daqing test site had the highest preservation rate and breeding value， and had better salt tolerance； the GGE biplot based on the BLUP method showed that the introduced birch fast-growing property of No.3 family line was the best， and the stability of No.9 family line was the strongest. Based on the comprehensive ranking of the stability and rapidity of each family line， four excellent family lines， No.20， 9， 7 and 24， were selected according to the 30% selection rate and combined with the genetic gain of the volume of each family line.

Fraxinus mandshurica is one of the precious broadleaf tree species in Northeast China. It has high economic and ecological value.There′s a shortage of F. mandshurica resources and a structural deficiency in resilient cultivars. It′s particularly important to select and breed F. mandshurica with excellent cold resistance in the context of global climate change. The F. mandshurica in Xiaoxing'an Mountains of Heilongjiang Province were selected as the reseach objects. Dendrochronology and wood anatomy were used to compare the radial growth of 52 F. mandshurica families（Families 1-77 in total）. The relationship between the radial growth and xylem anatomical characteristics of F. mandshurica and main climatic factors was clarified. The response of F. mandshurica families to low temperature event was studied. The results showed that there were significant differences in average annual radial growth of F. mandshurica families in Xiaoxing'an Mountains. The radial growth of No. 56， 46 and 38 F. mandshurica families were higher， the values were 4.07 mm， 3.82 mm and 3.71 mm， respectively. The radial growth of F. mandshurica was constrained by temperature and precipitation during the growing season. The radial growth was significantly negatively correlated with the temperature in October of the previous year， positively correlated with the temperature from January to April， and negatively correlated with the precipitation from March to April. Temperature was the primary climatic factor affecting xylem anatomical features of F. mandshurica families in Xiaoxing'an Mountains. Under low temperature stress， the ring width（RW）， mean vessel area （MVA）， total vessel area（TVA） and theoretical hydraulic conductivity（Kh） decreased by 25.5%， 38.2%， 21.8% and 55.1%， compared with non-low temperature years， while vessel density（VD） increased by 64.1%. There was difference in radial growth among F. mandshurica families under low temperature stress. No. 39， 70 and 36 families had stronger resistance to cold， the values of resistance were greater than 1. The recovery of No. 57， 17 and 70families were better， the values of recovery were higher than 1.63. The No.70 F. mandshurica family in Xiaoxing'an Mountains had excellent growth and stronger cold resistance， which could be used as an excellent F. mandshurica family for directional cultivation.

The identification of dominant tree species is an important part of forestry resource surveys. Improving the accuracy of dominant tree species identification has significant practical implications for conducting forest resource surveys and related research. Using the Google Earth Engine （GEE） cloud platform， we obtained Sentinel-2 time series images for the Huodong mining area from January to December 2023. The annual growth trajectory features of dominant tree species were constructed based on the CCDC algorithm and the NDFI index. A dominant tree species hierarchical identification method combining "trajectory features + spectral features + texture features" of long-time series remote sensing images was proposed. A control group of "spectral features + texture features" was set up， and hierarchical classification and random forest classification algorithms were used to identify 7 dominant tree species （Pinus tabuliformis， Quercus wutaishansea， Betula playphylla， Larix principis-rupprechtii， Platycladus orientalis， Populus davidiana， and poplars spp.） in the Huodong mining area. The results showed that： 1） The NDFI index can effectively distinguish between deciduous forests and evergreen forests； 2） The dominant tree species identification based on "trajectory features + spectral features + texture features" performed well， with an overall classification accuracy of 79.6% and a Kappa coefficient of 0.742 in the study area， which was 7.3% higher than the control group.

This study aims to clarify the spatial distribution characteristics of ridge plant belts on soil water-holding capacity and soil structure in sloping farmland， providing a scientific basis for optimizing ridge plant belt configurations and soil and water conservation measures in Northeast China's black soil region. Sloping farmland with ridge plant belts was selected as the research object （Ridge 1： ridge spacing of 12.5 m； Ridge 2： ridge spacing of 19.5 m）， and sloping farmland was selected as the control. The uniform spatial point sampling method was obtained using basic physical property indicators in the surface layer （0-15 cm）， and to quantify the differences in the spatial distribution characteristics of soil water-holding capacity and soil structure in sloping farmland with different spacing of ridge plant belts. The result showed that， the sloping farmland with ridge construction showed a significant increase in total porosity， capillary porosity， saturated water-holding capacity， field capacity， and capillary water-holding capacity， with a relatively uniform distribution across the slope. In addition， compared to the Ridge 2， the soil of Ridge 1 showed an increase of 0.96-1.11 times in total porosity， 1.21-1.31 times in capillary porosity， 1.03-1.25 times in saturated water-holding capacity， 1.22-1.78 times in field capacity， and 1.33-1.52 times in capillary water-holding capacity， respectively. The soil mechanical stable aggregate mass fraction， MWD （mean weight diameter）， water-stable aggregate mass fraction， and GMD （geometric mean diameter） in the sloping farmland with ridge showed significant improvements across all fields. Compared to the controls， the sloping farmland with ridge increased by 1.01-1.15 times， 0.94-1.61 times， 1-1.17 times， and 1.05-1.55 times， respectively. This indicated that the sloping farmland with ridge effectively improved soil structure compared to the control. Moreover， compared to the sloping farmland with Ridge 2， the soil mechanical stable aggregate mass fraction， MWD， water-stable aggregate mass fraction， and GMD in the sloping farmland with Ridge 1 increased by 1.08-1.14 times， 0.95-1.28 times， 1.07-1.15 times， and 1.14-1.40 times， respectively. Constructing ridges can improve water-holding capacity and soil structure characteristics， with a more significant improvement effect observed in relatively small distances smaller distances between ridges.

The optimization of stand spatial structure is a key issue in achieving sustainable forest management. Traditional optimization methods often exhibit low efficiency in handling complex spatial relationships and large-scale data. This study proposed a stand spatial structure optimization method based on Graph Attention Networks （GAT）. An integrated spatial structure evaluation system was established using the entropy-weighted matter-element analysis method， and a graph neural network model was constructed based on stand data from the Tanglin Forest Farm of the Xinqing Forestry bureau in northern Yichun，Heilongjiang Province. The model was applied to perform multi-objective optimization analysis of stand spatial structure. Experimental results showed that at a 25% harvesting intensity， the integrated spatial structure index improved from 4.336 to 7.256. The GAT model demonstrated superior performance in capturing complex spatial relationships and optimizing multi-objective tasks. This study provides an innovative and intelligent approach for optimizing stand spatial structure and managing forests， contributing to the enhancement of forest ecosystem health and stability.

In order to accurately obtain forest canopy height information， accurately estimate forest aboveground biomass， and evaluate forest carbon sink capacity， this study constructed 30 long time series feature variables based on ground measurements， multi-source remote sensing data， and digital elevation models， combined with machine learning algorithms （ML）， to invert the forest canopy height in Lishui City， Zhejiang Province. The study revealed that terrain factors had no significant impact on the inversion of forest canopy height， while vegetation factors related to the red and green bands were strongly correlated with forest canopy height. Adding long time series feature factors can help improve the accuracy of ML algorithm in inverting forest canopy height. The performance improvement of CNN was particularly significant， achieving an optimal coefficient of determination （R ²） increase of 0.39 and a root mean square error （RMSE in the formula， it is denoted as R _MES） decrease of 4.15. Random forest had the highest inversion accuracy among the four ML algorithms （R ²=0.79， R _MSE=1.65）， greater than support vector machine （R ²=0.65， R _MSE=1.97）， extreme gradient ascent method （R ²=0.76， R _MSE=1.81） and convolutional neural networks （R ²=0.71， R _MSE=1.83）.

Plant residues are an important source of forest soil carbon pool， and changes in soil carbon flux in woodland are closely related to soil carbon pool and carbon cycle. However， current studies on soil organic carbon stability mainly focus on farmland soil. In order to clarify the influence of exogenous carbon input changes on the stability of soil organic carbon， an indoor constant temperature culture experiment was set to study the litter species （Cherry， YH； Sycamore， WT； Poplar， YS）， additive amount （0， 2%， 4% and 6%）， particle size （2 mm， D； 0.25mm， X） as variables， 18 different treatments and 2 controls were concluded. The changes of soil CO₂ release， soil organic carbon content and mineralization intensity under different factors and their interactions were analyzed. Results showed that different litters had significant effects on soil total CO₂ release， and cherry blossom and poplar were more likely to promote soil total organic carbon mineralization. The highest total CO₂ release rate was observed in YHX6 treatment， and the cumulative total CO₂ release of YHD6 treatment was 4.37 times that of CK1. Compared with CK1， the potential mineralizable organic carbon C _p value of 6% added dose was significantly increased. The dynamic changes of soil total organic carbon accumulation mineralization over time can be fitted by the first-order kinetic equation， and the fitting results showed that exogenous carbon input accelerated soil carbon turnover， while litters in small particle size， 6% addition amount and YH type yielded the highest total soil organic carbon turnover rate. WTX2 significantly decreased total organic carbon mineralization intensity， which was only 1.67%. Organic carbon intensity in soil with small particle size was lower than that of large particle size treatment. Therefore， sycamore leaves in small particle size and added with low addition amount can be applied to increase the stability of soil organic carbon and promote the retention of carbon in soil in regional soil organic carbon management.

With the popularization of automated production lines， the pressing process of tea cakes has become particularly important for product quality. However， the quality control of Pu'er mini tea cakes produced by automated production lines often falls short of those made by hand. Therefore， the detection of the appearance quality of tea cakes after production by automated lines has become an urgent issue to be addressed. To this end， this study proposes an automated quality detection algorithm for Pu'er tea cakes based on machine vision. The algorithm comprehensively applies various image processing techniques， including Otsu threshold segmentation and Canny edge detection， and introduces multiple algorithm optimization strategies to improve detection accuracy and efficiency. The algorithm can automatically complete the detection and evaluation of the appearance quality of tea cakes and transmit the results in real-time to a Programmable Logic Controller （PLC）. Experimental results show that the algorithm can accurately identify appearance defects of tea cakes， with an average computational accuracy of 95.75%， demonstrating high robustness and reliability. It is suitable for quality control in automated production lines and has a wide range of application prospects， especially in the intelligent transformation of the tea production industry， where it has significant reference value.

Soluble solids content （SSC） is a key indicator for assessing the internal quality of fruits. This study proposes a non-destructive detection method based on hyperspectral image fusion to predict the SSC of blueberries. Three widely used wavelength dimensionality reduction algorithms are employed： Monte Carlo uninformative variable elimination （MC-UVE）， Competitive Adaptive Reweighted Sampling （CARS）， and Successive Projections Algorithm （SPA）， to identify optimal wavelengths. Additionally， a strategy integrating Local Binary Patterns （LBP） and Gray Level Co-occurrence Matrix （GLCM） is proposed for feature extraction. Using spectral features， image features， and fused features， Partial Least Squares （PLS）， Backpropagation Neural Network （BPNN）， and Support Vector Machine （SVM） models are developed for SSC prediction. The results demonstrate that the BPNN model， utilizing spectral features extracted via the CARS algorithm and image features derived from the LBP+GLCM algorithm， yields the highest prediction accuracy. The model's coefficient of determination （R {}_p^{\mathrm{2}}） is 0.926 1， while the Root Mean Square Error of Prediction （RMSEP） is 0.364 1. This study indicates that hyperspectral image fusion technology holds significant potential for the non-destructive prediction of blueberry SSC.

The production of plywood consumes a large amount of energy. In order to improve economic efficiency， support carbon peak and carbon neutrality goals， it is necessary to improve energy efficiency and reduce energy consumption. This article took 5 heat exchange logistics in the production process of plywood as the research object， used pinch point technology to analyze the heat exchange network under existing production conditions， and proposed optimization and improvement plans. Aspen Plus was applied to establish a heat exchange network in the plywood production process， calculate the stream flow rate and physical property data of each side line， divide the temperature range， determine the minimum heat transfer temperature difference， and calculate the pinch point temperature. The traditional pinch point method determined the minimum heat transfer temperature difference ∆ T_{\mathrm{m}\mathrm{i}\mathrm{n}} to be 9 ℃. After considering carbon emissions， the minimum heat transfer temperature difference ∆ T_{\mathrm{m}\mathrm{i}\mathrm{n}} was adjusted to 7 ℃， and the average pinch point temperature was 116.5 ℃. The pinch point temperature was used to analyze and diagnose the phenomenon of crossing pinch points in the heat exchange network， accurately located the bottleneck position of the heat exchange network， adjusted the improperly configured cold and hot stream heat exchangers， and achieved the goal of optimizing the entire heat exchange network. After optimization， the usage of cold and hot utilities in the system decreased by 862 465.0 kW and 202 642.0 kW respectively， significantly reducing the energy consumption of the equipment.

In the customization process of passive wooden window manufacturing， reducing material waste during frame cutting is key to cost reduction. This problem is modeled as a one-dimensional cutting stock problem. To address the issue of traditional genetic algorithms where the individual encoding method tends to lead to the destruction of cutting patterns and low exploration efficiency during iterations， a new individual encoding method is proposed to maintain the integrity of cutting patterns throughout the evolutionary process. Additionally， a heuristic strategy and a correction strategy are introduced for individual correction and population evolution. Simulation results show that for different test cases， the average material utilization rate， excluding the last remnants， exceeds 99%， with some improvements in the length of the last remnants compared to other algorithms. For two sets of real production data from enterprises， the proposed algorithm achieves the theoretical lower bound， with average utilization rates （excluding the last remnants） of 99.49% and 99.66%， respectively， outperforming the results of the company's existing software. This demonstrates the algorithm's potential to effectively reduce costs and provide practical solutions in engineering applications.

The effects of ethephon （ETH）， ethephon inhibitor 1-methylcyclopropene （1-MCP） and cysteine （CYS） on the yield and main quality indexes of rubber tree latex were analyzed， and the dosage threshold was calculated. An optimized orthogonal experimental design was used to analyze 14 treatments with three factors （ETH， 1-MCP， CYS） and four levels （four concentrations of each reagent） for applying rubber tree cut surfaces. Key indicators such as rubber latex yield， dry rubber content， molecular weight， initial plasticity value， plasticity retention index and Mooney viscosity were measured， and the correlation between the indicators was analyzed. The results showed that there were significant differences in yield and dry rubber content of 14 treated rubber trees. Correlation analysis showed that the number-average molecular weight was positively correlated with the weight-average molecular weight and Mooney viscosity， and the correlation coefficient was 0.71 and 0.83， respectively， and the correlation coefficient was negative with the polydispersity indexes， and the correlation coefficient was -0.91. Initial plasticity value was positively correlated with Mooney viscosity， and the correlation coefficient was 0.73. The polydispersity indexes was negatively correlated with Mooney viscosity with the correlation coefficient -0.89. The regression equations based on dry rubber content index were established respectively. The maximum concentration of ethephon， 1-MCP and CYS were 0.15%， 1.08% and 0.41 g/L， respectively. The optimized orthogonal test method can effectively calculate the threshold of the regulator and provide theoretical and practical guidance for the subsequent experiments.

In order to realize the high-value and large-scale utilization of metallurgical solid waste materials， the soil curing agent was synergistically prepared by using metallurgical solid waste materials （blast furnace slag， fly ash， calcium carbide slag and gypsum）， and the effects of different solid waste materials on the mechanical properties of the cured soil were investigated by orthogonal ratio optimization experiments and the optimal parameter formulations were obtained. The mechanical properties （unconfined compressive strength， splitting strength， delayed molding） and weathering properties （water stability， freeze-thaw cycle） of the solidified soil with solid waste-based curing agent （SWC） were systematically studied and compared with PO 42.5 silicate cement （OPC）. The results showed that： calcium carbide slag played an important role in the curing agent system， and the appropriate gypsum dosage had a positive effect on the strength growth； the strength of cured soil increased with the increase of SWC dosage and the age of curing， and the 7 day unconfined compressive strength of the cured soil at 4% dosage was more than 1 MPa， and the splitting strength was basically comparable to that of the OPC cured soil； the SWC cured soil showed a longer allowable delay in construction， and there was no trend of decreasing strength within 12 h after mixing； the water stability coefficient was more than 90% when the dosage was more than 5%， and the anti-freezing coefficient under the same dosage was increased by 3%-5% compared with that of cement， so it had good water stability and anti-freezing property； X-ray Diffraction （XRD） and Scanning Electron Microscope （SEM） analyses showed that SWC cured soils generate expansionary hydration products， calcite alumina （AFt） and hydrated calcium silicate （C-S-H）， during the hydration process， and that calcite crystals played a significant role in improving the cleavage strength of cured soils and increasing the resistance to cracking and deformation.

Rare and endangered plants have formed a stable association with their associated tree species in the long-term evolution process， but whether this association is related to allelopathy produced by litters is still unknown. Taking the unique rare and endangered plant Davidia involucrata Baill. and its associated species Cornus controversa Hemsl. in China as research objects， the allelopathic effects of water extracts from different types of litter （branch litter， leaf litter， and their mixture litter） at natural concentrations on each other's seedlings were studied. The results revealed that， 1）the water extract from the branch litter of C. controversa significantly promoted the basal diameter and root length growth of D. involucrata seedlings， and increased the contents of chlorophyll a and b， total chlorophyll， leaf mass fraction of N， and P， while the extracts from leaf litter and branch-leaf mixture litter did not show significant promotional effects. 2）The water extract from the branch litter of D. involucrata significantly promoted the basal diameter growth of C. controversa seedlings and increased the contents of chlorophyll a and b， and total chlorophyll， whereas the extracts from leaf litter and branch-leaf mixture litter significantly reduced the contents of chlorophyll a and b， total chlorophyll， leaf mass fraction of N. 3）The allelopathic effect index indicated that different litter types from C. controversa had allelopathic promotional effects on D. involucrata seedlings， the intensity from large to small was branch， branch-leaf mixture， and leaf； the allelopathic effects of different litter types from D. involucrata on C. controversa seedling were varied， showing promotion by branch litter， and inhibition by leaf litter and branch-leaf mixture litter， with the mixture litter exhibiting stronger inhibitory effects. These findings suggest that the water extracts from different types of litter from D. involucrata and C. controversa have distinct allelopathic effects on each other's seedling growth， and the extracts from the two types of branch litter exhibit the greatest allelopathic promotional effects on seedlings.

In early spring， the sap of Betula platyphylla was easy to collect and had a high yield. In order to explore the effect of temperature on the change of Betula platyphylla sap and the change of sap component concentration in different developmental periods， the natural secondary forest of B. platyphylla in Mao'ershan Experimental Forest， Northeast Forestry University in Heilongjiang Province was selected. In 2022 and 2023， sap of B. platyphylla was collected to calculate the spring sap flow rate. The concentration of carbohydrates， amino acids， total triterpenes， soluble proteins， pH， potassium， calcium， sodium and magnesium in the sap of B. platyphylla was determined at different developmental periods in 2023， and the variation patterns of sap components were analyzed. The B. platyphylla sap component concentration extracted from two consecutive years was compared with that extracted in the same year， in order to explore whether continuous extraction of sap had an effect on B. platyphylla. The results showed that sap of B. platyphylla production showed an overall trend of increasing and then decreasing from April to June， with the highest production in April and May. The increase in temperature promoted sap production. The concentration of total triterpenes， carbohydrates， amino acids and protein fractions in the sap showed a trend of increasing， then decreasing and then increasing during the whole period of phenological development. All of them were the lowest during the vigorous growth period. The pH value of sap showed an overall decreasing trend with the development of the phenology， and it was acidified continuously before the complete leaf expansion. The ion concentration showed a trend of increasing and then decreasing. Continuous sap extraction did not significantly affect the total triterpenes， amino acids and protein concentration of sap， but decreased the carbohydrate concentration and pH. The research results provided scientific guidance for the collection of sap of B. platyphylla in the eastern mountainous of Heilongjiang Province.

To study the synergistic antioxidant activity of four small berry polyphenols， including Vaccinium uliginosum L.， Vacciniumvitis-idaea L.， Lonicera caerulea L.var.edulis Turcz.ex Herd.， and Vaccinium macrocarpon Ait. （labeled as D2， H2， L2， and M2， respectively）， was studied. The uniform experimental design method was used to optimize the synergistic antioxidant combination of small berry polyphenols. After statistical analysis and mathematical regression model fitting， the optimal combination was obtained as follows： the optimal concentrations of Vaccinium uliginosum L. polyphenol （D2）， Vacciniumvitis-idaea L. polyphenol （H2）， Lonicera caerulea L. var. edulis Turcz. ex Herd. Polyphenol （L2）， and Vaccinium macrocarpon Ait. Polyphenol （M2） were 42 μg/mL， 138 μg/mL， 172 μg/mL， and 0 μg/mL， respectively. The actual clearance rate of DPPH free radicals was 98.07 ± 0.31%， which was close to the theoretical expected value of 100%， indicating the feasibility of the selected combination in the model. Through synergistic effect analysis， the combination index （CI） values of the synergistic effect index of the selected combination for clearing DPPH and hydroxyl radicals were 0.57 and 0.64， indicated that the D2， H2， and L2 had significant synergistic antioxidant effects. The research results can provide a basis for the development of natural antioxidants and small berry functional products.

In order to develop formaldehyde-free adhesive for particleboard and meet the broad market demand， this paper focused on the application problems of traditional starch adhesive， such as low solid content， high viscosity， poor water resistance and so on， and a novel formaldehyde-free starch adhesive DSA was used to prepare particleboard. The effects of hot pressing curves， dosage of adhesive， and the combined application of DSA and pMDI on the properties of particleboard were investigated. The results showed that the performance of the novel formaldehyde-free starch adhesive DSA was slightly inferior to that of pMDI， but the combined use of DSA and pMDI exhibited a synergistic effect of saving adhesive and enhancing efficiency. Furthermore， the use of DSA could replace approximately 20% of isocyanate adhesive， meanwhile the hot pressing factor was reduced by 13.3%， which was beneficial for improving the production efficiency of E_NF grade particleboard. When DSA adhesive was used alone or in combination with pMDI， it could effectively play the role of bonding， filling， chain extension and curing. The application of DSA could help to solve the key problems of poor technological performance and poor water-resistant bonding performance of traditional starch adhesive， and promote the large-scale application of biomass green adhesive in wood-based particle boards.

In order to solve the problem that the target detection algorithm is prone to leakage detection and insufficient detection accuracy in pedestrian detection in forest areas， a forest pedestrian target detection algorithm based on improved YOLOv8 is proposed. The C2f_DWRSeg module is used to replace the C2f module， and the number of initial convolutional channels is expanded so that the network can extract multi-scale features more efficiently. A reconstructed detector head is proposed to increase the complexity of the convolution layer during training， and a single branch structure is used in inference， so as to enrich the feature representation of the network and maintain efficient inference speed； add CGA， the convolution attention mechanism module， before feature fusion， to reduce the amount of calculation； use the Focaler-ShapeIoU loss function to replace the CIoU loss function to make up for the shortcomings of the boundary box regression method and further improve the detection ability. Experimental results show that compared with benchmark model， the improved algorithm mAP50 has increased by 2%， mAP50-95 has increased by 2.4%， and FPS has increased by 4.33%. It proves that the improved algorithm can be better applied to the task of pedestrian detection in forest areas.

To expand the application of wood in the field of outdoor reflective materials， a series of calcium carbonate/eucalyptus wood composite materials with different calcium carbonate （CaCO₃） contents were prepared by hot pressing method using the mineralization method of alternating vacuum impregnation of eucalyptus wood with calcium chloride and sodium bicarbonate to mimic the organic/inorganic composite structure of natural pearl layer. The effects of CaCO₃ on the structure and properties of the mineralized materials were investigated through structural characterization and performance tests. The results showed that CaCO₃ could enhance the mechanical properties of the mineralized material， improve its thermal stability and reflective ability to sunlight， and reduce the temperature at which the material was heated by light. When the mineralization time was lower than 3 days， the tensile strength increased with the increase of CaCO₃ content， up to 18.35 MPa， and the fracture process showed multiple fracture； when the mineralization time reached 4 days， the material's reflectance of sunlight reached more than 80 %， which reduced the temperature of the original wood by 10 ℃ compared with the original wood itself. This environmentally friendly material has a certain application potential in the field of outdoor reflective insulation field.

As the main part of plant photosynthesis， chlorophyll plays an important role in monitoring vegetation growth and evaluating the capacity of carbon sequestration. Remote sensing technology， which is a high efficiency and low cost earth observation technology， can realize the estimation of chlorophyll content by leaf reflection spectrum characteristics. However， the accuracy of chlorophyll content estimation will be reduced due to the influence of leaf water content and leaf cell structure on leaf spectrum. Solar-induced chlorophyll fluorescence （SIF） is a technology of detecting the fluorescence information of chlorophyll excited fluorescence signal and the variation of fluorescence signal is directly related to chlorophyll content， which has great potential in chlorophyll content estimation. In this study， the fluorescence sensitive band of chlorophyll content was determined by sensitivity analysis using the fluorescence radiation transfer model SCOPE （Soil Canopy Observation， Photo-chemistry and Energy fluxes） and the chlorophyll content estimation model was established based on the fluorescence spectrum. Finally， the robustness of the model was verified by the measured data. The results showed that 700 nm and 730 nm were the highest and lowest sensitive bands of chlorophyll content， respectively. The band of 760 nm was the highest correlated band of chlorophyll content. The chlorophyll content estimation model were established based on the indices of fluorescence ratio of these three bands. SIF₇₆₀/SIF₇₀₀ had the best modeling accuracy with the R² of 0.998 1 and root mean square error （RMSE） of 0.043 5 μg/cm². The accuracy of SIF₇₀₀/SIF₇₃₀ and chlorophyll content （Cab） was the lowest in three models with R² and RMSE 0.904 8 and 0.088 6 μg/cm²， respectively. Independent samples of measured data were used to verify the above three estimated methods. SIF₇₆₀/SIF₇₃₀ had the best estimation results， with RMSE of 0.210 8 μg/cm²， followed by SIF₇₀₀/SIF₇₃₀， with RMSE of 0.345 4 μg/cm². But estimated model by using SIF₇₀₀/SIF₇₃₀ showed an overall overestimating results. The estimated results of SIF₇₆₀/SIF₇₀₀ showed a different results compared with measured data with RMSE of 0.743 5 μg/cm². In summary， the ratio vegetation index calculated by SIF₇₆₀/SIF₇₃₀ showed higher accuracy of modeling and excellent robustness of chlorophyll content estimation. Relevant studies provide technical references for the estimation of leaf biochemical parameters by chlorophyll fluorescence remote sensing technology.

In view of the limitations of existing indicators， in order to better evaluate the high and low temperature performance of warm mix asphalt binder， different amounts of Sasobit and Evotherm 3G warm mix agent were selected to be mixed with 70^# matrix asphalt and SBS modified asphalt to prepare modified asphalt. Two parameters of complex shear modulus G^* and phase angle δ were obtained and analyzed by dynamic shear rheological （DSR） test. The rutting factor G^*/sinδ， improved rutting factor G^* /（sinδ）⁹ index and critical temperatureT_{G\mathrm{*}/\mathrm{s}\mathrm{i}\mathrm{n}\delta }， improved critical temperatureT_{G\mathrm{*}/{(\mathrm{s}\mathrm{i}\mathrm{n}\delta )}^{\mathrm{9}}} index were used to comprehensively evaluate and analyze the high temperature performance of modified asphalt. Two parameters of creep stiffness modulus S and creep rate m were obtained and analyzed by low temperature bending rheological （BBR） test. The k index was established and the creep compliance J（t） index was introduced to evaluate the low temperature performance of modified asphalt. The test results and data analysis showed that： G^* /（sinδ）⁹ was more accurate than G^*/sinδ in evaluating the high temperature performance of warm mix asphalt， and T_{G\mathrm{*}/{(\mathrm{s}\mathrm{i}\mathrm{n}\delta )}^{\mathrm{9}}} was suitable for the high temperature performance evaluation of SBS warm mix asphalt， and there was no obvious difference for 70^# matrix asphalt. The k index can distinguish the difference of low temperature performance between matrix asphalt and modified asphalt， and the J（t） index can well reflect the low temperature creep performance of warm mix asphalt. Finally， the weight analysis of high and low temperature indexes was carried out by analytic hierarchy process （AHP）， and the weight values of T_{G\mathrm{*}/{(\mathrm{s}\mathrm{i}\mathrm{n}\delta )}^{\mathrm{9}}} and J（t） were the largest. It was suggested that T_{G\mathrm{*}/{(\mathrm{s}\mathrm{i}\mathrm{n}\delta )}^{\mathrm{9}}} was used to evaluate the high temperature performance of warm mix asphalt， and J（t） was used to evaluate the low temperature performance of warm mix asphalt.

To investigate the effects of different stand ages on the litter and soil water conservation ability in apple tree plantation， and clarify the water characteristics of apple tree plantation， is of great significance for establishing a reasonable orchard management system， consiolidating and expanding the achievements of poverty alleviation and realizing rural revitalization. Taking apple tree plantation of different stand ages （4， 6， 15 and 30 a） in Linyi County， Yuncheng City as the research object， this paper quantitatively described and studied the differences of litter and soil water conservation ability in apple tree plantation through field investigation and laboratory test. The results showed that： the total storage of the litter about the four stand ages in apple tree plantation ranged from 0.82 to 2.09 t/hm²， the maximum water holding capacity ranged from 4.91 to 13.09 t/hm²， and the water conservation capacity ranged from 3.36 to 9.38 t/hm². With the increase of tree age， these parameters increased first and then decreased， and the maximum was 15 years old. There were good logarithmic and power function relationships between water holding capacity， water absorption rate and soaking time of litter layer respectively. Within the range of 0 to 60 cm， as the tree age increased， the soil bulk density decreased gradually， the total porosity and the maximum water holding increased gradually， and the maximum was 30 a. With the deepening of soil layer， the soil bulk density of apple tree plantation of different stand ages increased first and then decreased. Except 4 a， the total soil porosity of the remaining trees decreased gradually， but the difference between different soil layers was not significant. The maximum soil water holding capacity of 30 a orchard gradually decreased with the deepening of the soil layer， and the other trees showed a trend of decreasing first and then increasing at the age of 0 to 10 cm soil layer， and the minimum water holding capacity at 20 to 40 cm soil layer. According to the coordinate comprehensive evaluation method， the performance of litter and soil water conservation capacity of different stand ages was the strongest at the age of 15 years， the second at the age of 30 years， and the weakest at 4 a years.

Helan Mountain is located in the arid and semi-arid region of northwest China. Systematic analysis of the composition characteristics of soil fungal communities in this area is of great significance for clarifying the fungal diversity and community functions in forest ecosystems of arid and semi-arid regions. The Illumina Miseq high-throughput sequencing technology was used to analyze the fungal diversity， community composition， and their responses to changes of soil physicochemical properties in three main constructive tree species—Picea crassifolia， Pinus tabuliformis and Betula platyphylla in Helan Mountain. The results revealed that a total of 276， 353 and 433 fungal OTUs were obtained from rhizosphere soil with 60 shared OTUs. All fungal OTUs belonged to 17 phyla， 42 classes， 107 orders， 210 families and 326 genera. At the phylum level， Basidiomycota and Ascomycota were dominant， with relative abundances of 58.7% and 35.7%， respectively. At the genus level， the top five dominant genera were Sebacina（6.7%）， Tomentela（6.5%）， Inocybe（6.1%）， Geminibasidium（3.7%） and Penicillium（2.9%）. Significant differences were observed in the composition of dominant fungi community at the genus level among different tree species. The genera with the highest relative abundance in the rhizosphere soil are Geminibasidium（10.8%）， Inocybe（16.9%）， and Sebacina（9.0%） respectively. RDA was used to analysis the driving factors of fungal community composition difference in the rhizosphere soil of the main constructive tree species in Helan Mountain. Soil total nitrogen content （TN） and soil water content （SWC） exert significant influences on the composition of fungal communities， accounting for explanation of 41.6% and 39.1%， respectively. This study enriches the biological information of fungal resources in the rhizosphere soil of the main tree species in Helan Mountain， and can provide theoretical basis for the excavation and research of fungal resources in forest ecosystems in arid and semi-arid areas.

Under the background of new quality productivity， blockchain has brought new opportunities for transformation and upgrading of traditional industries with its transparency and traceability， and also opened up a new path for carbon emission reduction cooperation in wood supply chain. In view of this， this paper constructs an evolutionary game model of China-Russia wood supply chain， and studies the operating evolution law of the four parties-Russian wood suppliers， China wood processing manufacturers， wood products distribution retailers and the government in the carbon emission reduction cooperation mechanism under the blockchain platform. The results show that the initial strategy probability of supply chain members， consumers' low-carbon preference and the increase of manufacturers' carbon emission reduction can effectively encourage the main members of the wood supply chain to actively participate in the carbon emission reduction cooperation mechanism. At the same time， the government reward and punishment mechanism will also affect the final stable result of the game system. The greater the punishment for hitchhiking， the better the game system will reach the ideal state， while excessive subsidies will weaken the possibility of the system reaching the optimal equilibrium. The research results provide theoretical inspiration and reference for carbon emission reduction cooperation in China-Russia wood supply chain.

In order to investigate the differences in soil fungal diversity between healthy Pinus sylvestris var.mongolica natural forests and different areas of blight disease-susceptible P.sylvestris forests， this study used healthy natural forests of P.sylvestris in Honghuaerji Nature Reserve as the control， susceptible P.sylvestris in natural forests of Honghuaerji Nature Reserve， and in plantation forests in Tailai County and Zhanggutai as the study objects. The soil fungal community composition was analyzed using lllumina Miseq high-throughput sequencing technology. The results showed that 5 564 fungal Amplicon Sequence Variants （ASV） were obtained from the soil samples of 4 groups from three regions， with higher relative abundance of Basidiomycota and Ascomycota. The abundance and species of dominant genera varied in different soil depths in different regions. The dominant genus of soil fungi in the surface layer of healthy natural forests was Amphinema， and the dominant genus of soil fungi in the 0-10 cm and 10-20 cm depths was Cortinarius. In the understorey soil of susceptible P.sylvestris， the dominant genera of soil fungi in the surface layer， 0-10 cm and 10-20 cm depth of natural forests were the genera of Trichoderma， Talaromyces and Suillus， and the dominant genera of soil fungi in the surface layer， 0-10 cm and 10-20 cm depth of plantation forests in Tailai County were the genera of Delastria， Pseudogymnoascus and Sagenomella， and the dominant genus of soil fungi in the surface layer of Zhanggutai plantation forest was Knufia， while the dominant genus of soil fungi in the 0-10 cm and 10-20 cm depths were Pseudogymnoascus. In addition， the phytopathogenic fungi in the soil fungal community of the susceptible plantation forests were in the percentages of 2.63% and 5.04%， respectively， which were much lower than those of the susceptible natural forests （8.77%） and healthy natural forests （8.11%）. The content of ectomycorrhizal in the soil fungal community of plantation was lower than that of natural forest. It is hypothesised that plantation forests have a lower abundance of exogenous mycorrhizal fungi due to their monoculture， making P. sylvestris less resistant to disease.

To explore the changes and main influencing factors of soil active carbon during the autumn freeze-thaw period of three forest types in the permafrost region of the Great Daxing'an Mountains， and to provide assistance for forest soil carbon sink management in the permafrost region.Taking the Larix gmelinii forest （LY）， Pinus sylvestris var. mongolica forest （ZZ） and Betula platyphylla forest （BH） as the research objects， soil samples were taken from different soil layers （0-5， 5-10， and 10-20 cm） to determine the content of soil active carbon components （dissolved organic carbon， microbial biomass carbon， and readily oxidizable organic carbon） from October 10th to November 18th， 2022， and to explore their dynamic characteristics and influencing factors.Results showed that， from October 10th to November 18th， the soil temperature in the Larix gmelinii forest， Betula platyphylla forest and Pinus sylvestris var. mongolica forest all decreased with decreasing temperature， with ranges of -0.49 to 3.71， -2.10 to 2.39， and -1.04 to 3.48 ℃， respectively. The content of dissolved organic carbon （DOC） in different soil layers of three forest types showed a trend of first increasing and then decreasing with the decrease of temperature， the content of microbial biomass carbon （MBC） first decreased and then increased， while the content of readily oxidizable organic carbon （ROC） fluctuated， ranging from 78.75 to 214.32， 101.06 to 988.40， and 1.52 to 13.94 g/kg， respectively. Among them， the soil DOC and ROC contents in the Betula platyphylla forest were significantly higher than those in the Larix gmelinii forest and Pinus sylvestris var. mongolica forest， while the soil MBC content was the highest in the Larix gmelinii forest. The three types of active carbon showed a ‘surface aggregation effect’ in different forest types， and the soil DOC content increased and the soil MBC content decreased during the freeze-thaw period， but the soil ROC content did not change significantly. The changes in soil active carbon content in Larix gmelinii forest were mainly influenced by soil moisture and microbial biomass nitrogen. Ammonium nitrogen was the dominant factor affecting the three types of soil active carbon in Betula platyphylla forest， while soil pH was the main influencing factor for the three types of soil active carbon in Pinus sylvestris var. mongolica forest.Research indicates that， the freeze-thaw effect has a significant impact on the active carbon content of typical forest soils in the permafrost regions of the Great Daxing'an Mountains， increasing soil DOC content and reducing soil MBC content， while the impact on ROC content is relatively small.

The preparation technology of MF-IPBC microcapsule mildew inhibitor were optimized， and the effects of the optimum preparation conditions on the anti aging， slow release and mildew resistance of the microcapsule were investigated， in order to provide theoretical basis for the preparation， testing and application of the microcapsule mildew inhibitor. MF-IPBC microcapsules mildew inhibitor were prepared by in-situ polymerization with melamine formaldehyde resin （MF） as wall material， iodopropylene-butylamine carboxylate （IPBC） as core material and styryl-maleic anhydride copolymer （SMA） as emulsifier. The change of core-wall mass ratio， temperature， pH value on the microcapsule morphology and particle size distribution were studied by single factor variable method. Exploring the changes in performance of microcapsule mildew inhibitor under different temperature and ultraviolet aging environment， the slow-release performance of MF-IPBC microcapsule was studied. The bacteriostatic performance of the anti-mold agent was studied by the antibacterial zone method. The experimental results indicated that， the optimal preparation process for microcapsule synthesis： when the core wall mass ratio was 2∶1， reaction temperature was 55 ℃， pH was 4.5， reaction time was 2 h and stirring rate was 600 r/min， microcapsules were observed to have uniform particle size distribution under microscopic morphology， the average partical size was 4.23 μm， and after treatment in poplar， they appeared as a membrane covering the wood cell wall. The results of aging experiment showed that the color of MF-IPBC microcapsule was similar to that of IPBC powder under UV aging for 24 h and 6 h， and the color of MF-IPBC microcapsule aged at 90 ℃ was similar to that of IPBC powder at 70 ℃. MF-IPBC microcapsules had not been melted at high temperatures in the range of 40 to 100 ℃， while IPBC powder began to convert to liquid at 70 ℃. The microcapsules were diluted with 20% xylene aqueous solution， and the release rate was fast in the first 0.5 h， then slowed down in the subsequent 4.5 h， and was basically completely released at 5 h， reaching a stable state. The results of antibacterial zone experiment showed that when the mass fraction of microcapsule was 1%， the antibacterial zone diameter of Botryodiplodia theobromae Pat was the largest， and when the mass fraction of microcapsule was 0.8%， the antibacterial zone diameter of A. niger， T viride and P citrinum were the largest. The MF-IPBC microcapsule mildew inhibitor with preparation in this study effectively improves the aging resistance of IPBC， making the core material IPBC have a slow-release effect， and has an inhibitory effect of four strains， especially the inhibition effect on Botryodiplodia theobromae Pat is the most obvious.

In order to study the propagation behavior of acoustic emission （AE） signals in wood， COMSOL 3D simulation models were established for four kinds of wood specimens， including Populus simonii， Castanopsis hystrix， Pinus sylvestris and Cunninghamia lanceolata. The elastic wave point source was simulated using a given displacement method， and then， the longitudinal propagation of the AE signal along the wood was analyzed with the help of the stress maps of the simulation process. The longitudinal wave velocity of the AE source was calculated by the time difference of arrival （TDOA） method with respect to the time difference between the two positions of the AE source arriving at the surface of the model. The AE tests were carried out on the wood specimen under the same conditions and the longitudinal wave velocities were calculated. The final results were consistent with the simulation model. The results showed that the relative errors between the simulated and tested longitudinal wave velocities of Populus simonii， Castanopsis hystrix， Pinus sylvestris and Cunninghamia lanceolata were 1.47%，1.04%， 0.46% and 2.33%， respectively. The simulation model can objectively reflect the propagation behavior of the AE signals in wood， which provided a new way to visualize the propagation process of the AE signals in wood. However， the relative error of AE signal amplitude was large， and the model cannot objectively respond to the change rule of amplitude in wood.

To systematically analyze the impact of human activities on the transportation environment， scientifically assess the level of smart transportation development， and accurately identify the influencing factors of the urban transportation industry in the process of smart transformation， we construct a smart transportation development evaluation index system based on the DPSIR（drivers pressures state impact response） model， evaluate the dynamic changes in the level of smart transportation development in Beijing from 2013—2022， and identify the limiting factors affecting the development of urban smart transportation. The results of the study show that， 1） the comprehensive development level of smart transportation in Beijing continues to rise from 2013—2022， showing an overall improvement trend； 2） the development level of the driving force and response subsystems of smart transportation in Beijing shows an overall decreasing trend， and the development level of the pressure， state and influence subsystems shows an overall increasing trend； 3） in 2013—2018， the main factors affecting the development of smart transportation in Beijing are the number of electronic police installations at intersections and the average travel time consumption of citizens during peak hours， in 2019—2022， the density of transportation network construction， population density， and the number of public parking spaces for automobile societies become the main factors. Therefore， suggestions are made to strengthen the smart transportation's own hematopoietic ability， improve the supply side level， and promote the transformation of urban transportation to smart and low-carbon， in order to make improvements for the short-board factors of Beijing's smart transportation governance.

The steel-wood composite beam with I-section is made of laminated veneer lumber （LVL） and cold-formed thin-wall steel by structural adhesive. The flexural properties of nine composite beams are tested with parameters such as LVL plate thickness， section height， thin wall steel thickness and flange LVL width. The failure forms， deflection development， strain distribution and bearing capacity of specimen are observed， the influence factors of flexural property are analyzed， and a formula for calculating mid-span deflection considering the slip effect is proposed. The results show that steel-LVL composite beams have good overall working performance. The composite beam has a high deformation ability before failure， and the most typical failure mode is the lower flange LVL fracture. The material properties are fully utilized， showing good ductility. The flexural bearing capacity of composite beams can be improved by increasing the ratio of section height to width and web height to thickness and reducing the ratio of flange width to thickness. The slip between the LVL and the section steel reduces the stiffness of the composite beam. Compared with the results without taking slip into account， the theoretical calculation results of mid-span deflection of composite beam with interface slip effect are closer to the real deformation， and the calculation accuracy is improved by 2.38%.

Xinjiang is an important forest and fruit industry base in China， and the characteristic forest and fruit industry is an important part of regional economic development. In order to prevent fruit tree diseases from restricting the development of forest and fruit industry， a MobileNet-V2 NAM fruit tree leaf classification and disease identification model was designed in this study. It incorporated a lightweight normalization-based attention module to improve the model's sensitivity to feature information and make the model focus on salient features. At the same time， L1 regularization was added to the loss function to penalize the sparsity of the weights and suppress the non-significant weights. The experimental results showed that： in leaf classification， the model performed well in the classification results of self-built， Plant Village， and mixed datasets， with the accuracy rates reaching 97.05%， 98.73%， and 94.91%， respectively， and had good generalization ability. In disease identification， the MobileNet-V2 NAM model achieved a recognition accuracy of 94.55%， which was higher than the AlexNet， VGG16 classic CNN models， and the number of parameters of the model was only 3.56M. MobileNet-V2 NAM has good accuracy while maintaining a low amount of model parameters， provides technical support for embedding deep learning models into mobile devices.

Soil organic carbon mineralization is highly sensitive to forest recovery methods. In order to understand the rate of soil organic carbon mineralization under different recovery methods and its relationship with carbon components. In June 2023， the soil of two different forest stands （Natural recovery formed Betual costata secondary forest， artificial recovery formed man-made Korean pine forest） formed under two different recovery methods in the area of Xiaoxing’anling Mountains broad-leaved Korean pine forest clear cutting site was selected as the research object， and the forest soil of undisturbed original broad-leaved Korean pine forest was used as the control. Using the combination of field sample setting and investigation， soil sample collection and indoor culture and measurement， the response of the organic carbon mineralization rate to different recovery methods was analyzed， and the relationship between the organic carbon mineralization rate and the soil carbon form under different recovery methods was explored， combined with the distribution of soil carbon form. Research results indicated that， 1） The mineralization rate of soil organic carbon decreased with the increase of culture time from the third day until it became stable， and the mineralization rate gradually decreased with the deepening of soil layer. 2） The mineralization rate of original broadleaved Korean pine forest （PK） was the highest， followed by Betual costata secondary forest （BC） and man-made Korean pine forest （PM） was the lowest. 3） In the soil of two recovery methods， the total organic carbon， mineral-bound organic carbon and inactive organic carbon from large to small were PK， BC， PM； the content of particulate organic carbon from large to small was BC， PM， PK. 4） The content of soil total organic carbon， particulate organic carbon and easily oxidized organic carbon decreased gradually with the change of organic carbon mineralization rate during the culture process， and had a significant negative correlation with the amount of organic carbon mineralization. Among them， easily oxidized organic carbon had the greatest influence on the mineralization rate of soil organic carbon， and the correlation coefficient was 0.622. There was no significant correlation between mineral-bound organic carbon and inactive organic carbon and soil organic carbon mineralization. Compared with the man-made Korean pine forest， the Betual costata secondary forest enhanced the soil organic carbon mineralization rate， and in the two recovery methods， the active organic carbon dominated the soil organic carbon mineralization rate.

With the issuance of the Opinions on Promoting the Prosperity and Development of Academic Journals by Publicity Department of the Communist Party of China in 2021， the country has paid more attention to the development of journals， and the high-quality development model of academic journals has become a research hotspot in the current publishing industry. From the perspective of the sustainable development of journals， talent is crucial. The talent of journal includes editors， authors and editorial board （young editorial board）， among which young editorial board plays an increasingly important role in the development process of periodicals. Based on the work experience of the young editorial board in Forest Engineering for more than 10 years， focusing on the role of young editorial board as peer reviewers in the development of journals， the participation and importance of young editorial board in the running of scientific and technological journals are deeply discussed， so as to provide reference for the high-quality and sustainable development of academic journals.

Satisfactory image segmentation results can improve the accuracy of tree species classification， and the segmentation effect depends on the selection of the optimal scale parameter （OSP）. Previous studies have relied on manually set scale sequences， resulting in subjectivity. To avoid this issue， this study used GF-2 images as the data source and proposed an unsupervised selection method of OSP based on effective scale intervals to determine at which scale the optimal segmentation results for different forest types occur. Multi-resolution segmentation （MRS） algorithm was used to segment images， and constructing effective scale interval estimation functions （ESF） and combining with the overall goodness F-measure （OGF）， the OSPs of different forest types at different scale intervals were obtained. Finally， the optimal segmentation results were determined by supervised segmentation accuracy analysis combined with Google map visual interpretation. The results showed that the OSPs obtained from the effective scale interval Ⅲ achieved the best segmentation results for each forest type， with the lowest and highest F-measure of 0.7311 and 0.8733， respectively. Meanwhile， in the segmentation task of tree species classification based on GF-2 image， OSP was related to tree species and forest types. This paper provided technical support for object extraction of object-based tree species classification based on high-resolution remote sensing images and also provided a methodological reference for the selection of scale parameters for images composed of different geographical objects.

This paper aims to compare the differences of burning properties of 12 typical tree species in Xiaoxing’anling，and to provide reference for the selection and allocation of fireproof forest tree species. In the study， the 12 kinds of shrubs in the Xiaoxing’anling region of Heilongjiang Province are taken as the main research subjects， with their stems， branches， and leaves measured separately for the combustibility indicators. The hierarchical analysis method （AHP） is then applied to construct a hierarchical model of the combustibility of shrub plants， determining the weights of each index of combustibility， calculating the combustibility values of different parts of the shrub， and confirming the weight ratio of each part of the shrub in combination with expert scoring methods to arrive at the combustibility ranking of 12 kinds of shrub. It has been revealed by the research results that： in terms of the whole plant， Rosa davurica has the strongest combustibility， while Lonicera japonica has the weakest. Compared the combustibility of the stem， the most easily ignited is Sambucus williamsii and the hardest to ignite is Lonicera japonica. Compared the branch combustibility， the most easily ignited is Sambucus williamsii and the hardest to ignite is Lonicera japonica. Compared the combustibility of leaves， those of Acanthopanax senticosus are most easily ignited and those of Tamarix ramosissima are the hardest to be ignited. The results can provide a theoretical basis for the shrub′s combustibility and a support for predicting forest fire behavior， and combustible materials management.

To explore the genetic variation patterns of growth traits during the seedling stage in Larix kaempferi seed orchards and plantation of superior tree open pollination families， and provide reference for afforestation and genetic improvement of excellent families in the later stage. Using 25 open pollinated families and 30 open pollinated families of superior trees in plantation as experimental materials in the Larix kaempferi primary clonal seed orchard of the Shaba National Larch/Spruce Seed Base. Mixed seed seedlings in the seed orchard were used as controls， and a randomized complete block experimental design was used in the field experiment. The seedling growth experiment was conducted in the nursery of the Shaba National Larch/Spruce Seed Base. The data was analyzed using SPSS 16.0 for variance analysis， multiple comparisons， and estimated heritability and genetic gain. The 2-year-old seedling ground diameter， seedling height， and new shoot growth were used as indicators， and the Brykin multi trait comprehensive evaluation method was used for family evaluation and selection. There were rich genetic variations in the growth traits of 1-year-old and 2-year-old seedlings （ground diameter， height， and new shoot growth of 2-year-old seedlings） in seed orchards and open pollination families of superior trees in plantation， with significant differences in growth traits （P<0.05） or extremely significant （P<0.01） positive correlation， with great potential for family selection. The coefficient of variation （CV） for 2-year-old seedling ground diameter， seedling height， and new shoot growth of the open pollinated family in the seed orchard were 27.61%， 36.82%， and 44.28%， respectively. The heritability of the family was 0.76， 0.79， and 0.79， respectively. The phenotypic CV for the ground diameter， seedling height， and new shoot growth of the open pollinated family in the plantation was 25.57%， 32.94%， and 38.83%， respectively. The heritability of the family was 0.90， 0.92， and 0.92， respectively， indicating high heritability. The growth traits of a family were strongly controlled by genetics and had a certain degree of stable genetic ability. The genetic gain of family selection was significant. Select excellent families with good seedling performance based on a 50% selection rate， thirteen families including species 1， species 25， species 8， species 34， species 26， species12， species 16， species20， species 2， species 100， species 7， species 21， and species 101 were selected for the seed orchard. The genetic gains in ground diameter， seedling height， and shoot growth of the selected families reached 1.89%， 6.18%， and 7.65%， respectively. Fifteen families， including You19， You8， You2， You28， You30， You3， You7， You1， You18， You6， You15， You26， You25， You24， and You13， were selected for open pollination of superior trees in plantation. The genetic gains of ground diameter， seedling height， and new shoot growth of the selected families were 3.73%， 9.31%， and 11.19%， respectively. Regardless of whether it is a seed orchard or an planted forest， the excellent family selected using the Brykin comprehensive evaluation method is precisely the one with the highest seedling height selected. Therefore， it is recommended that Larix kaempferi open pollination families use a single trait - seedling height - as an evaluation and selection indicator during the seedling stage， which is more intuitive， economical， and effective. At a 50% selection rate， 13 and 15 families are selected during the seedling stage for open pollination of superior trees in seed orchards and plantation， respectively. The initial selection of families during the seedling stage provides reference for afforestation experiments and later genetic improvement. Effectively reduce the scale of field experiments and improve selection efficiency. As an evaluation and selection indicator， seedling height is more intuitive， convenient， and practical in production.