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首页> 外文期刊>Journal of spectroscopy >Rapid Recognition of Geoherbalism and Authenticity of a Chinese Herb by Data Fusion of Near-Infrared Spectroscopy (NIR) and Mid-Infrared (MIR) Spectroscopy Combined with Chemometrics
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Rapid Recognition of Geoherbalism and Authenticity of a Chinese Herb by Data Fusion of Near-Infrared Spectroscopy (NIR) and Mid-Infrared (MIR) Spectroscopy Combined with Chemometrics

机译：通过近红外光谱（NIR）和中红外光谱（MIR）光谱与化学计量学结合的近红外光谱（NIR）和中红外线（MIR）光谱法的快速识别中国药草

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摘要

Fourier transform near-infrared (NIR) spectroscopy and mid-infrared (MIR) spectroscopy play important roles in all fingerprint techniques because of their unique characteristics such as reliability, versatility, precision, and ease of measurement. In this paper, a supervised pattern recognition method based on the PLSDA algorithm by NIR and the NIR-MIR fusion spectra has been established to identify geoherbalism of Angelica dahurica from different regions and authenticity of Corydalis yanhusuo W. T. Wang. Comparing principle component analysis (PCA) cannot successfully identify geographical origins of Angelica dahurica. Linear discriminant analysis (LDA) also hardly distinguishes those origins. Furthermore, the PLSDA model based on the data fusion of NIR and IR was more accurate and efficient. But, the identification of authenticity of Corydalis yanhusuo W. T. Wang was still inaccurate in the PLSDA model. Consequently, data fusion of NIR-MIR original spectra combined with moving window partial least-squares discriminant analysis was firstly used and showed perfect properties on authenticity and adulteration discrimination of Corydalis yanhusuo W. T. Wang. It indicated that data fusion of NIR-MIR spectra combined with MWPLSDA could be considered as the promising tool for rapid discrimination of the geoherbalism and authenticity of more Chinese herbs in the future.
机译：傅里叶变换近红外（NIR）光谱和中红外（MIR）光谱在所有指纹技术中起重要作用，因为它们具有可靠性，多功能性，精度和测量的独特特性。本文，基于NIR和NIR-MIR融合光谱的基于PLSDA算法的监督模式识别方法，从不同地区和Corydalis Yanhusuo W.T. Wang的不同地区和真实性识别Angelica Dahurica的地球血界。比较原理分析分析（PCA）不能成功识别Angelica Dahurica的地理起源。线性判别分析（LDA）也几乎不区分这些起源。此外，基于NIR和IR数据融合的PLSDA模型更准确，高效。但是，在PLSDA模型中仍然不准确地识别Corydalis Yanhusuo W.T. Wang的真实性。因此，首先使用了NIR-MIR原始光谱的数据融合，以及移动窗口局部最小二乘判别分析，并显示了围栏yanhusuo W.T. Wang的真实性和掺假歧视的完美性质。它表明，NIR-MIR光谱与MWPLSDA相结合的数据融合可被认为是未来更多中国草药的地球钟主义和真实性的有前途的工具。

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