[1]汪紫阳,尹世逵,李春旭,等. 可见/近红外光谱技术识别树叶树种的研究[J].西北林学院学报,2019,34(1):229-236.[doi:10.3969/j.issn.1001-7461.2019.01.35]
　WANG Zi-yang,YIN Shi-kui,LI Chun-xu,et al. Identification of Tree Leaf and Species by Vis/NIR Spectroscopy[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2019,34(1):229-236.[doi:10.3969/j.issn.1001-7461.2019.01.35]
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 可见/近红外光谱技术识别树叶树种的研究()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第34卷
期数:
2019年第1期
页码:
229-236
栏目:
出版日期:
2019-01-31

文章信息/Info

Title:
 Identification of Tree Leaf and Species by Vis/NIR Spectroscopy
文章编号:
1001-7461(2019)01-0229-08
作者:
 汪紫阳; 尹世逵; 李春旭; 李耀翔*
 （东北林业大学，黑龙江 哈尔滨 150040）
Author(s):
 WANG Zi-yang; YIN Shi-kui; LI Chun-xu; LI Yao-xiang*
 (Northeast Forestry University,Harbin 150040,Heilongjiang,China)
关键词:
 ; 可见/近红外光谱; 树种识别; 树叶; 偏最小二乘法
Keywords:
 ; Vis/NIR spectroscopy;  Tree identification;  Leaf;  PLS-DA
分类号:
S781.1
DOI:
10.3969/j.issn.1001-7461.2019.01.35
文献标志码:
A
摘要:
 探索使用可见/近红外光谱技术识别树叶树种的可行性，为野外可见/近红外光谱技术用于树种识别提供方法。本试验识别了9个树种，测试了光谱预处理方法、识别方法对可见/近红外光谱识别的准确率的影响。对9种阔叶树种共46棵树，分别采用距离法和PLS-DA建立识别模型，比较不同波段和导数预处理方法对模型预测效果的影响。结果表明，使用距离法对原始光谱进行识别时，识别准确率<50%，不能够有效识别树叶树种。使用距离法对预处理后的光谱进行识别时，识别准确率为近红外350~2 500 nm（99.16%）＞350~1 000 nm（88.05%）＞1 000~2 500 nm（81.24%），且任意单个树种的识别准确率都>98%，能够有效识别树叶树种。使用偏最小二乘法（PLS-DA）结合单列识别变量矩阵时，识别准确率高达100%，识别模型的相关系数为0.993 6，RMSEC为0.120，RMSEP为0.144，但只能成功识别4种树叶树种，当树叶种数＞4时，预测模型的识别准确率陡降。使用偏最小二乘法（PLS-DA）结合多列识别变量矩阵对9种树叶的识别准确率高达99.58%，识别模型的相关系数为0.888 6～0.956 9，RMSEC为0.084 5～0.15，RMSEP为0.088 7～0.155。本试验为可见/近红外光谱技术快速识别树种提供了一种新的方法和思路。
Abstract:
 A feasibility study was carried out to identify tree leaf and species by visible and near infrared spectroscopy (Vis/NIRS) technique to provide a practical method for the identification of tree species in the field.Forty-six broad-leaved trees of 9 species were sampled to examine the influences of different spectral pretreatments and identification methods on the rate of identification accuracy were tested.Different wavelengths and identification methods (distance method and PLS-DA) were compared over the effect of model prediction.The results showed that by using distance method to identify the raw spectrum,the rates of identification accuracy of all species were under 50%,which could not effectively identify the tree species.However,when the distance method was used to identify the pretreated spectra,the rates of identification accuracy were 99.16% (350-2 500 nm ),88.05% (350-1 000 nm) and 81.24% (1 000-2 500 nm),respectively.With the wavelength of 350-2 500 nm,the accuracy rates for all the individual tree species achieved over 98%.When the PLS-DA method combined with single column identification variable matrix was used,the rates of identification accuracy were 100%,with the correlation coefficient of 0.993 6,RMSEC 0.120,and RMSEP 0.144.With this method,the maximum number of identifying tree species was 4,over 4,the rate of identification accuracy decreased significantly.When the PLS-DA method combined with multiple column identification variable matrix was used to identify the 1st and smoothing spectrum of 9 species,the rate of identification accuracy was 99.58%,with correlation coefficients of 0.888 6-0.956 9,RMSEC 0.084 5-0.15,and RMSEP 0.088 7-0.155.The results of this study would provide a new method and way in rapid identification of common tree species.

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备注/Memo

备注/Memo:
 收稿日期：2018-03-15修回日期：2018-07-16
基金项目：林业公益性行业科研专项（201504508）；十三五国家重点研发计划项目（2017YFC0504103）。
作者简介：汪紫阳，男，硕士，研究方向：木材无损检测。E-mail：w730@vip.qq.com
*通信作者：李耀翔，女，博士，教授，研究方向：木材无损检测。E-mail:yaoxiangli@nefu.edu.cn
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