| 引用本文:沈国芳1，黄俊航2，许麦成3，金强3.基于近红外高光谱成像鉴别不同产地的红参[J].世界中医药,2021,(23):. |
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| 基于近红外高光谱成像鉴别不同产地的红参 |
| Discriminant Analysis of Red Ginseng from Different Origins Based on NIR-Hyperspectral Imaging Technology |
| 投稿时间：2021-10-25 |
| DOI：10.3969/j.issn.1673-7202.2021.23.003 |
| 中文关键词: 高光谱成像 红参 数据融合 产地鉴别 |
| English Keywords:Hyperspectral imaging Red ginseng Data fusion Origin identification |
| 基金项目:浙江省市场监督管理局雏鹰计划培育项目（CY2022345） |
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| 摘要点击次数: 256 |
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| 中文摘要: |
| 目的：建立一种基于近红外(NIR)高光谱成像技术融合近红外光谱和图像纹理特征,鉴别不同产地红参药材的方法。方法：提取红参ROI近红外高光谱数据,采用多种预处理算法对光谱数据进行降噪处理。利用灰度共生矩阵(GLCM)和灰度游程矩阵(GLRLM)提取图像纹理特征,实现NIR光谱和图像纹理数据融合。利用偏最小二乘判别分析(PLS-DA)和支持向量机分类(SVC)建立产地分类模型。结果：全波段光谱融合GLRLM所构建的模型性能最佳,准确率分别为90.0%和91.2%。进一步地使用混淆矩阵和ROC曲线对模型进行评估。混淆矩阵中SVC模型表现优异,对吉林、黑龙江和辽宁3个产地的分类准确率可达100%、91%和83%;经ROC特征曲线评估,2个模型的最优曲线下面积值分别达到了0.97和0.96。结论：本研究为快速鉴别红参药材不同产地提供了一种新方法。 |
| English Summary: |
| To establish a method based on near-infrared(NIR) hyperspectral imaging technology which could identify red ginseng from different origins by fusing NIR spectra and image texture features.Methods:The near-infrared hyperspectral data of red ginseng ROI were extracted to be further de-noised by various pre-processing algorithm.Texture features are extracted from images using gray co-occurrence matrix(GLCM) and gray run matrix(GLRLM)，and near-infrared spectroscopy and image data are fused.Partial least squares discriminant analysis(PLS-DA) and support vector machine classification(SVC) were used here to establish the origin classification model.Results:The model constructed by full-band spectral combined with GLRLM gained the best performance，with accuracy of 90.0% and 91.2%，respectively.The model was further evaluated using confusion matrix and ROC curves.The SVC model performed better in the confusion matrix，with the classification accuracy of 100%，91% and 83% for red ginseng from Jilin，Heilongjiang and Liaoning.According to ROC characteristic curve evaluation，the areas under the optimal curve of the two models are 0.97 and 0.96，respectively.Conclusion:This research provides a new method for rapid identification of red ginseng from different origins. |
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