1.中国林业科学研究院木材工业研究所，北京 100091
2.南京林业大学林业资源高效加工利用协同创新中心，江苏南京 210037
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石兰兰,汪睿,任海青等.应用近红外光谱技术预测进口辐射松木材抗压和抗弯性能[J].木材科学与技术,2023,37(01):55-60.
SHI Lanlan,WANG Rui,REN Haiqing,et al.Compressive and Bending Property Prediction of Imported Pinus radiata Wood based on Near-Infrared Spectroscopy[J].Chinese Journal of Wood Science and Technology,2023,37(01):55-60.
以进口辐射松（,Pinus radiata,）木材为研究对象，探究应用近红外光谱技术预测辐射松木材抗压和抗弯性能的可行性，比较不同切面采谱、不同光谱预处理方法以及不同谱区波段的建模效果。结果表明，用弦切面的光谱建立的校正模型精度最高。原始光谱建立的校正模型精度较好，相关系数达0.85及以上，抗压强度模型在经过S-G卷积平滑处理后相关系数可提高到0.92。在全波段建立的校正模型效果最好。经外部验证，抗压强度、抗弯强度和抗弯弹性模量预测值与实测值相关性较高，相关系数达0.82及以上。研究结果可为辐射松木材的抗压和抗弯性能的快速评价提供新方法。
The feasibility of predicting the compressive and bending properties was explored based on near-infrared spectroscopy for imported, Pinus radiata,. The various modeling were compared based on different wood sections, spectral pretreatment methods, and wavebands in different spectral regions respectively. The results showed that the calibration models established by the spectra of the tangential section had the highest accuracy. The calibration models with the original spectra had good accuracy, and the correlation coefficients were 0.85 and above. The correlation coefficient of the compressive strength model treated by S-G convolution smoothing raised to 0.92. The calibration models in the whole wavelength all had the best effect. The external validation of the calibration models showed that the predicted value of the prediction model for the compressive strength parallel to the grain, MOR, and MOE of ,Pinus radiata, had a high correlation with the measured value and the correlation coefficient was 0.82 and above. The results provide a new method for rapid evaluation of the compressive and bending properties in ,Pinus radiata,.
辐射松近红外光谱预测模型抗压性能抗弯性能
Pinus radiatanear-infrared spectroscopyprediction modelcompressive propertiesbending properties
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