A novel NIRS modelling method with OPLS-SPA and MIX-PLS for timber evaluation  

作　　者：Jinhao Chen Huilig Yu Dapeng Jiang Yizhuo Zhang Keqi Wang 

机构地区：[1]College of Mechanical and Electrical Engineering,Northeast Forestry University,Harbin 150040,People’s Republic of China [2]College of Information and Computer Engineering,Northeast Forestry University,Harbin 150040,People’s Republic of China

出　　处：《Journal of Forestry Research》2022年第1期369-376,共8页林业研究（英文版）

基　　金：supported financially by the China State Forestry Administration“948”projects(2015-4-52);Heilongjiang Natural Science Foundation(C2017005)。

摘　　要：The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in its application,weak signals are extracted from complex,overlapping and changing information.This study focused on the stability of NIR modeling.The Orthogonal Partial Least Squares(OPLS)and Successive Projections Algorithm(SPA)eliminates noise and extracts effective spectra,and an ensemble learning method MIX-PLS,is applied to establish the model.The elastic modulus of timber is taken as an example,and 201 wood samples of three species,Xylosmacongesta(Lour.)Merr.,Acer pictum subsp.mono,and Betula pendula,samples were divided into three groups to investigate modelling performance.The results show that OPLS can preprocess the near-infrared spectroscopy information according to the target object in the face of the system error and reduce errors to minimum.SPA finally selects 13 spectral bands,simplifies the NIR spectral data and improves model accuracy.The Pearson's correlation coefficient of Calibration(Rc)and the Pearson's correlation coefficient of Prediction(Rp)of Mix Partial Least Squares(MIX-PLS)were 0.95 and 0.90,and Root Mean Square Error of Calibration(RMSEC)and Root Mean Square Error of Prediction(RMSEP)are 2.075 and 6.001,respectively,which shows the model has good generalization abilities.

关 键 词：NIR prediction Orthogonal partial least squares(OPLS) Successive projections algorithm(SPA) Mix partial least squares(MIX-PLS)modulus of elasticity 

分 类 号：S781[农业科学—木材科学与技术]