Prediction Model of Wood Basic Density in Multiple Pinus elliottii Half-sib Families Based on Near-Infrared Spectroscopy and Feature Wavelength Selection
1.Institute of Chemical Industry of Forest Products,Chinese Academy of Forestry(CAF),Nanjing 210042,Jiangsu,China
2.Yueyang Forest Paper Co.,Ltd.,Yueyang 414002,Hunan,China
3.Research Institute of Wood Industry,CAF, Beijing 100091,China
4.Guangdong Provincial Key Laboratory of Silviculture,Protection and Utilization, Guangdong Academy of Forestry,Guangzhou 510520,Guangdong,China
LIANG Long,WU Ting,ZHU Hongwei,et al.Prediction Model of Wood Basic Density in Multiple Pinus elliottii Half-sib Families Based on Near-Infrared Spectroscopy and Feature Wavelength Selection[J].Chinese Journal of Wood Science and Technology,2025,39(06):33-42. DOI: 10.12326/j.2096-9694.2025125.
Prediction Model of Wood Basic Density in Multiple Pinus elliottii Half-sib Families Based on Near-Infrared Spectroscopy and Feature Wavelength Selection
were used to analyze the longitudinal variation patterns of wood basic density and pulping potential
and to investigate the potential of developing a near-infrared (NIR) spectroscopy model to predict the basic density of multiple families. The results indicate that the basic density of three families decreased from the base to the top of the trunk. Among them
the EB2 family exhibited moderate density and the lowest coefficient of variation
demonstrating excellent pulping potential. Biological differences among families
combined with the high redundancy and high-dimensional nature of spectral data
limited the robustness and generalizability of multi-families full-spectrum models. By applying the competitive adaptive reweighted sampling (CARS) algorithm
17 feature wavelengths highly correlated with basic density were selected. The model developed with these wavelengths exhibited robust generalization across all the three families
achieving root mean square error of prediction (RMSEP) values between 19.6 to 23.23
kg/m³ and determination coefficients (
R
2
) exceeding 0.81. This enables fast
non-destructive assessment of wood basic density in
Pinus elliottii
. This study provides technical support for high-throughput evaluation of wood properties in pulpwood breeding programs.
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references
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