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Data fusion strategy based on near infrared spectra and ultraviolet spectra for simultaneous determination of ginsenosides and saccharides in Chinese herbal injection

机译:基于近红外光谱和紫外光谱的数据融合策略同时测定中草药注射剂中的人参皂苷和糖类

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A data fusion method based on near infrared (NIR) spectra and ultraviolet (UV) spectra for simultaneous determination of six ginsenosides and four saccharides in Chinese herbal injection (CHI) was developed. Two data fusion strategies (low-level data fusion and mid-level data fusion) combined with partial least squares (PLS) regression and uninformative variable elimination by PLS (UVEPLS) regression were implemented, respectively. Compared with the models established by independent NIR or UV spectra, there was a significant improvement provided by two data fusion strategies, which benefited from the synergistic effect of complementary information obtained from near infrared spectroscopy (NIRS) and ultraviolet spectroscopy (UVS). The results in this work showed data fusion of NIR and UV spectra combined with a regression algorithm could be a promising strategy to determine the ginsenosides and saccharides in CHI rapidly and simultaneously.
机译:建立了一种基于近红外光谱和紫外光谱的数据融合方法,同时测定中草药注射剂中的六种人参皂苷和四种糖类。分别实现了两种数据融合策略(低级数据融合和中级数据融合),偏最小二乘(PLS)回归和PLS消除无信息变量(UVEPLS)回归。与通过独立NIR或UV光谱建立的模型相比,两种数据融合策略提供了显着改进,这得益于从近红外光谱(NIRS)和紫外光谱(UVS)获得的互补信息的协同效应。这项工作的结果表明,近红外光谱和紫外光谱的数据融合与回归算法相结合,可能是一种快速,同时测定CHI中人参皂甙和糖类的有前途的策略。

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