{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T05:02:46Z","timestamp":1787029366785,"version":"build-2736575974"},"reference-count":51,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T00:00:00Z","timestamp":1767052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key R&D Program Project of Yunnan Province, China","award":["202503AA080013"],"award-info":[{"award-number":["202503AA080013"]}]},{"name":"Yunnan Fundamental Research Projects","award":["202501AT070245"],"award-info":[{"award-number":["202501AT070245"]}]},{"name":"Research on Intelligent Perception and Mending Methods for Rotary-Cut Veneer in Plywood","award":["YJS-KCJJ-2025-24"],"award-info":[{"award-number":["YJS-KCJJ-2025-24"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Plants"],"abstract":"<jats:p>Aimed at the problems of traditional wood species identification relying on manual experience, slow identification speed, and insufficient robustness, this study takes hyperspectral images of cross-sections of 10 typical wood species commonly found in Puer, Yunnan, China, as the research object. It comprehensively applies various spectral and texture feature extraction technologies and proposes an intelligent wood species identification method based on the fusion of multimodal texture-dominated features and deep learning. Firstly, an SOC710-VP hyperspectral imager is used to collect hyperspectral data under standard laboratory lighting conditions, and a hyperspectral database of wood cross-sections is constructed through reflectance calibration. Secondly, in the spectral space construction stage, a comprehensive similarity matrix is built based on four types of spectral similarity indicators. Representative bands are selected using two Max\u2013Min strategies: partitioned quota and coverage awareness. Multi-scale wavelet fusion is performed to generate high-resolution fused images and extract interest point features. Thirdly, in the texture space construction stage, three types of texture feature matrices are generated based on the PCA first principal component map, and interest point features are extracted. Fourthly, in the complementary collaborative learning stage, the ST-former model is constructed. The weights of the trained SpectralFormer++ and TextureFormer are imported, and only the fusion weights are optimized and learned to realize category-adaptive spectral\u2013texture feature fusion. Experimental results show that the overall classification accuracy of the proposed joint model reaches 90.27%, which is about 8% higher than that of single-modal models on average.<\/jats:p>","DOI":"10.3390\/plants15010108","type":"journal-article","created":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T13:30:52Z","timestamp":1767187852000},"page":"108","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Research on Intelligent Wood Species Identification Method Based on Multimodal Texture-Dominated Features and Deep Learning Fusion"],"prefix":"10.3390","volume":"15","author":[{"given":"Yuxiang","family":"Huang","sequence":"first","affiliation":[{"name":"College of Materials and Chemical Engineering, Southwest Forestry University, Kunming 650224, China"},{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9604-3286","authenticated-orcid":false,"given":"Tianqi","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihong","family":"Liang","sequence":"additional","affiliation":[{"name":"College of Materials and Chemical Engineering, Southwest Forestry University, Kunming 650224, China"},{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4744-2719","authenticated-orcid":false,"given":"Hongxu","family":"Li","sequence":"additional","affiliation":[{"name":"College of Materials and Chemical Engineering, Southwest Forestry University, Kunming 650224, China"},{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2957-9421","authenticated-orcid":false,"given":"Mingming","family":"Qin","sequence":"additional","affiliation":[{"name":"College of Materials and Chemical Engineering, Southwest Forestry University, Kunming 650224, China"},{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruicheng","family":"Niu","sequence":"additional","affiliation":[{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyuan","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingbo","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1007\/s40820-024-01414-4","article-title":"Leakage Proof, Flame-Retardant, and Electromagnetic Shield Wood Morphology Genetic Composite Phase Change Materials for Solar Thermal Energy Harvesting","volume":"16","author":"Chen","year":"2024","journal-title":"Nano-Micro Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2195","DOI":"10.1038\/s41559-024-02564-9","article-title":"The global distribution and drivers of wood density and their impact on forest carbon stocks","volume":"8","author":"Mo","year":"2024","journal-title":"Nat. Ecol. Evol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1007\/s12221-025-00874-8","article-title":"Unveiling Favorable Mechanical Properties of Lignocellulosic Wood\u2014Reinforced Thermoplastic Composites as Future Green and Sustainable Materials","volume":"26","author":"Khoo","year":"2025","journal-title":"Fibers Polym."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Korjakins, A., Sahmenko, G., and Lapkovskis, V. (2025). A Short Review of Recent Innovations in Acoustic Materials and Panel Design: Emphasizing Wood Composites for Enhanced Performance and Sustainability. Appl. Sci., 15.","DOI":"10.3390\/app15094644"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3346","DOI":"10.1007\/s10853-025-10675-2","article-title":"Influence of degradation products from thermal wood modification on wood-water interactions","volume":"60","author":"DeLigne","year":"2025","journal-title":"J. Mater. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1111\/jipb.13589","article-title":"Wood of trees: Cellular structure, molecular formation, and genetic engineering","volume":"66","author":"Zhu","year":"2024","journal-title":"J. Integr. Plant Biol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"101354","DOI":"10.1016\/j.pmatsci.2024.101354","article-title":"Wood elasticity and compressible wood-based materials: Functional design and applications","volume":"147","author":"Fu","year":"2025","journal-title":"Prog. Mater. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"118430","DOI":"10.1016\/j.indcrop.2024.118430","article-title":"Effect of partial delignification and densification on chemical, morphological, and mechanical properties of wood: Structural property evolution","volume":"213","author":"Hussein","year":"2024","journal-title":"Ind. Crops Prod."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"7283","DOI":"10.1039\/D4RA00174E","article-title":"Making wood inspection easier: FTIR spectroscopy and machine learning for Brazilian native commercial wood species identification","volume":"14","author":"Everton","year":"2024","journal-title":"RSC Adv."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Reh, R., Kristak, L., Kral, P., Pipiska, T., and Jopek, M. (2024). Perspectives on Using Alder, Larch, and Birch Wood Species to Maintain the Increasing Particleboard Production Flow. Polymers, 16.","DOI":"10.3390\/polym16111532"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1080\/17480272.2022.2054726","article-title":"Critical wood-particle properties in the production of particleboard","volume":"17","author":"Niemz","year":"2022","journal-title":"Wood Mater. Sci. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Janceva, S., Andersone, A., Spulle, U., Tupciauskas, R., Papadopoulou, E., Bikovens, O., Andzs, M., Zaharova, N., Rieksts, G., and Telysheva, G. (2022). Eco-friendly adhesives based on the oligomeric condensed tannins-rich extract from alder bark for particleboard and plywood production. Materials, 15.","DOI":"10.3390\/ma15113894"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Szadkowska, D., Auriga, R., Lesiak, A., Szadkowski, J., and Marchwicka, M. (2022). Influence of Pine and Alder Woodchips Storage Method on the Chemical Composition and Sugar Yield in Liquid Biofuel Production. Polymers, 14.","DOI":"10.3390\/polym14173495"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.renene.2022.05.048","article-title":"Classifying waste wood from Amazonian species by near-infraredspectroscopy (NIRS) to improve charcoal production","volume":"193","author":"Lima","year":"2022","journal-title":"Renew. Energy"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Sydor, M., Mirski, R., Stuper-Szablewska, K., and Rogozi\u0144ski, T. (2021). Efficiency of Machine Sanding of Wood. Appl. Sci., 11.","DOI":"10.3390\/app11062860"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"11243","DOI":"10.1016\/j.matpr.2021.02.616","article-title":"Raw material particle terminologies for development of engineered wood","volume":"46","author":"Singh","year":"2021","journal-title":"Mater. Today Proc."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/s00107-022-01862-y","article-title":"Discrimination of amazonian forest species by NIR spectroscopy: Wood surface effects","volume":"81","author":"Novaes","year":"2023","journal-title":"Wood Prod."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"31","DOI":"10.22382\/wfs-2023-05","article-title":"The global wood species priority list: A living database of tree species most at risk for illegal logging, unsustainable deforestation, and high rates of trade globally","volume":"55","author":"Richardson","year":"2023","journal-title":"Wood Fiber Sci."},{"key":"ref_19","first-page":"3463","article-title":"Spectral Identification of Pterocarpus santalinus Based on Peak and Valley Feature Extraction Technology","volume":"44","author":"Zhuang","year":"2024","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4","DOI":"10.22382\/wfs-2023-03","article-title":"Use of a portable near infrared spectrometer for wood identification of four dalbergia species from Madagascar","volume":"55","author":"Raobelina","year":"2023","journal-title":"Wood Fiber Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1007\/s00107-023-02034-2","article-title":"Photo-stabilization effect of extractives on the photo-degradation of Red pine","volume":"82","author":"Peng","year":"2024","journal-title":"Eur. J. Wood Wood Prod."},{"key":"ref_22","first-page":"178","article-title":"Study on the Fractionation Law of C, H, O Stable Isotopes in Different Parts of Tree Plants","volume":"42","author":"Gao","year":"2022","journal-title":"J. Southwest For. Univ. (Nat. Sci.)"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1007\/s00226-024-01561-2","article-title":"How thermal treatment affects the chemical composition and the physical, mechanical and swelling properties of Scots pine juvenile and mature wood","volume":"58","author":"Broda","year":"2024","journal-title":"Wood Sci. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1186\/s10086-023-02095-0","article-title":"Geographical origin classification of Phoebe zhennan and Phoebe bournei by solid phase microextraction and gas chromatography-mass spectrometry","volume":"69","author":"Chen","year":"2023","journal-title":"Wood Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s40725-023-00195-0","article-title":"Recent Developments and Trends in Sustainable and Functional Wood Coatings","volume":"9","author":"Landry","year":"2023","journal-title":"Curr. For. Rep."},{"key":"ref_26","first-page":"1565","article-title":"Study on Origin Traceability of Pueraria lobata Based on Mineral Element Fingerprint","volume":"35","author":"He","year":"2021","journal-title":"J. Nucl. Agric. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"100709","DOI":"10.1016\/j.tfp.2024.100709","article-title":"Timber traceability, determining effective methods to combat illegal logging in Africa: A review","volume":"18","author":"Tonouewa","year":"2024","journal-title":"Trees For. People"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1515\/hf-2020-0229","article-title":"Cellular-level chemical changes in Japanese beech (Fagus crenata Blume) during artificial weathering","volume":"75","author":"Kanbayashi","year":"2021","journal-title":"Holzforschung"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"9500","DOI":"10.1002\/rcm.9500","article-title":"Effect of Formic Acid Treatment on Carbon and Nitrogen Stable Isotope Ratios in Sperm Whale Teeth Dentine","volume":"37","author":"Stukonyte","year":"2023","journal-title":"Rapid Commun. Mass Spectrom."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1111\/jipb.13717","article-title":"PagMYB128 regulates secondary cell wall formation by direct activation of cell wall biosynthetic genes during wood formation in poplar","volume":"66","author":"Hao","year":"2024","journal-title":"J. Integr. Plant Biol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.4014\/jmb.2312.12003","article-title":"Construction of a New Agrobacterium tumefaciens-Mediated Transformation System based on a Dual Auxotrophic Approach in Cordyceps militaris","volume":"34","author":"Yan","year":"2024","journal-title":"J. Microbiol. Biotechnol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1007\/s10529-023-03374-y","article-title":"An efficient Agrobacterium-mediated system based on the pyrG auxotrophic marker for recombinant expression in the filamentous fungus Penicillium rubens","volume":"45","author":"Tran","year":"2023","journal-title":"Biotechnol. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1007\/s00107-023-01969-w","article-title":"Prediction of the color change of surface thermally treated wood by artificial neural network","volume":"81","author":"Mo","year":"2023","journal-title":"Eur. J. Wood Wood Prod."},{"key":"ref_34","first-page":"298","article-title":"Tissue culture and Agrobacterium-mediated genetic transformation of the oil crop sunflower","volume":"19","author":"Chen","year":"2024","journal-title":"PLoS ONE"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"101048","DOI":"10.1016\/j.clet.2025.101048","article-title":"Fast and automatic solar module geo-labeling for optimized large-scale photovoltaic systems inspection from UAV thermal imagery using deep learning segmentation","volume":"28","author":"Zoubir","year":"2025","journal-title":"Clean. Eng. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1007\/s00530-025-01726-4","article-title":"MSCA-Sp R-CNN: A segmentation algorithm for pneumonia small lesions integrating multi-scale channel attention and sub-pixel upsampling","volume":"31","author":"Lu","year":"2025","journal-title":"Multimed. Syst."},{"key":"ref_37","unstructured":"Doaa, A., Karma, M., and Sherin, M. (2024, January 12\u201314). Pan-BCS: An Enhanced Panoptic Biventricular 3D Cardiac Assistive Model Integrating Feature Pyramid Networks and Parallel Semantic Segmentation. Proceedings of the 2024 International Conference on Machine Intelligence and Smart Innovation, Alexandria, Egypt."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"232","DOI":"10.23939\/cds2024.01.232","article-title":"Using Neural Networks to Identify Objects in an Image","volume":"6","author":"Oleh","year":"2024","journal-title":"Comput. Des. Syst. Theory Pract."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1038\/s41586-024-08109-1","article-title":"A broadband hyperspectral image sensor with high spatio-temporal resolution","volume":"635","author":"Bian","year":"2024","journal-title":"Nature"},{"key":"ref_40","first-page":"5502405","article-title":"WaveFormer: Spectral-Spatial Wavelet Transformer for Hyperspectral Image Classification","volume":"21","author":"Ahmad","year":"2024","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"25654","DOI":"10.1109\/JSTARS.2025.3616436","article-title":"DMTF-GAN: A Dual-Branch Mapping GAN With Transformer for Few-Shot Hyperspectral Image Classification","volume":"18","author":"Yang","year":"2025","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"21400","DOI":"10.1109\/JSTARS.2025.3595434","article-title":"Squeeze-SwinFormer: Spectral Squeeze and Excitation Swin Transformer Network for Hyperspectral Image Classification","volume":"18","author":"Ullah","year":"2025","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"5518615","DOI":"10.1109\/TGRS.2021.3130716","article-title":"SpectralFormer: Rethinking hyperspectral image classification with transformers","volume":"60","author":"Hong","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., and Sun, G. (2018, January 18\u201323). Squeeze-and-Excitation Networks. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref_45","first-page":"56","article-title":"A Qualitative and Quantitative NIRs Study on Larch Wood Surface Color Change by UV Light Irradiation","volume":"42","author":"Fu","year":"2022","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1080\/02773813.2025.2455183","article-title":"Application of near-infrared spectroscopy (NIRS) in the chemical characterization of Corymbia hybrid wood","volume":"45","author":"Noernberg","year":"2025","journal-title":"J. Wood Chem. Technol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"159887","DOI":"10.1016\/j.scitotenv.2022.159887","article-title":"Combining conventional tree-ring measurements with wood anatomy and strontium isotope analyses enables dendroprovenancing at the local scale","volume":"858","author":"Andrea","year":"2023","journal-title":"Sci. Total Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"e2025GL117556","DOI":"10.1029\/2025GL117556","article-title":"Potential and Limitations of Strontium Isotopic Fingerprinting in Wood","volume":"52","author":"Buntgen","year":"2025","journal-title":"Geophys. Res. Lett."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Kim, M., Im, S., and Kim, T. (2024). DNA Barcodes for Wood Identification of Anatomically Similar Species of Genus Chamaecyparis. Forests, 15.","DOI":"10.3390\/f15071106"},{"key":"ref_50","first-page":"1","article-title":"Early detection and tracking of wood borers using improved environmental DNA aggregation and TaqMan quantitative PCR approaches in forests","volume":"52","author":"Qi","year":"2025","journal-title":"Insect Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1007\/s00107-023-02014-6","article-title":"Effect of moisture on the edgewise flexural properties of acetylated and unmodified birch plywood: A comparison of strength, stiffness and brittleness properties","volume":"82","author":"Wang","year":"2023","journal-title":"Eur. J. Wood Wood Prod."}],"container-title":["Plants"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2223-7747\/15\/1\/108\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T13:54:52Z","timestamp":1767189292000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2223-7747\/15\/1\/108"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,30]]},"references-count":51,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["plants15010108"],"URL":"https:\/\/doi.org\/10.3390\/plants15010108","relation":{},"ISSN":["2223-7747"],"issn-type":[{"value":"2223-7747","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,30]]}}}