木材识别技术研究进展:从传统经验分析到智能鉴定系统OA北大核心CHSSCDCSCD

Accurate wood identification holds significant ecological and economic value for ensuring the sustainable utilization of global forest resources,combating illegal logging and related trade,and protecting biodiversity.This paper reviews the research progress in wood identification technology,tracing its evolution from traditional empirical analysis towards integrated intelligent identification.It first reviews the value and limitations of the traditional empirical identification method relying on anatomical characteristics.Subsequently various techniques are elucidated,including chromatographic and mass spectrometric techniques based on chemical fingerprints,spectroscopic techniques based on optical perception,DNA barcoding and fingerprinting techniques based on genetic information,and image recognition techniques based on manually extracted features,and their principles and applications for addressing core challenges such as identifying closely related species and determining geographical origin are analyzed.Furthermore,it discusses the two main types of intelligent identification system:computer visual recognition systems based on deep learning convolutional neural networks(CNNs)and multimodal fusion systems that integrate multi-source information.At the end,the paper concludes that the future direction of the field lies in constructing integrated intelligent identification systems,and the core pathways include the breakthroughs in multimodal fusion algorithms,the co-construction and sharing of a global wood digital database,and the development of lightweight and rapid field detection technologies.