文献类型：期刊文献

英文题名：Measuring wood density of different tree species using the micro-drilling resistance method

作者：Yao, Jianfeng[1,2,3] Liu, Hengyuan[1] Lu, Jun[4]

第一作者：Yao, Jianfeng

通信作者：Lu, J[1]

机构：[1]Xinyang Normal Univ, Coll Comp & Informat Technol, Xinyang 464000, Peoples R China;[2]Henan Dabieshan Natl Field Observat & Res Stn Fore, Zhengzhou 450046, Peoples R China;[3]Xinyang Acad Ecol Res, Xinyang 464000, Peoples R China;[4]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China

年份：2025

卷号：83

期号：1

外文期刊名：EUROPEAN JOURNAL OF WOOD AND WOOD PRODUCTS

收录：;EI(收录号：20250217655596);Scopus(收录号：2-s2.0-85214201368);WOS:【SCI-EXPANDED(收录号:WOS:001391669100001)】；

基金：We would like to express our gratitude to Dr. Shouzheng Tang of Chinese Academy of Science (CAS) for the guidance on topic selection and supervision.

语种：英文

外文关键词：Core drilling - Forestry

摘要：In order to reduce modeling workload and improve the accuracy of wood density measurement, a modeling method for establishing an overall model for multiple tree species was studied. Firstly, the wood cores and drill resistance of 9 tree species were collected. The absolute dry density, wood moisture content, and average drill resistance for each wood core were calculated. Secondly, the random forest algorithm was used to rank the relative importance of each factor affecting wood density, and factors with relative importance higher than 0.05 were selected as independent variables for building the overall mathematical model for total tree species and sub model for individual tree species. The results showed that: (1) the relative importance of tree species and drill resistance on wood density was higher than 0.05; (2) the relative importance of moisture content and drill usage frequency (less than 150 times) on wood density was lower than 0.05; (3) the average estimation accuracy of overall model was 91.42%, while that of the sub model was only 90.44%; (4) among the 9 tree species, the standard deviation of the overall model for 5 tree species was lower than that of the sub model. The results showed that the accuracy and stability of the overall model were superior to those of the sub models, and it is feasible to establish an overall model to estimate wood density.