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- Title
Identification metliod of ginger-processed Pinelliaternata based on infrared spectroscopy data fusion.
- Authors
Sun Fei; Chen Yu; Wang Kaiyang; Qiu Yunqi; Wang Shumei; Liang Shengwang
- Abstract
Objective To establish a rapid identification method for differentiating the ginger-processed Pinelliaternata from the ginger-processed Pinellia Pedatisectaby data infusion with near-infrared ( NIR) and mid-infrared ( MIR ) spectroscopy techniques. Methods 22 batches of ginger-processed Pinelliaternata and 14 batches of ginger-processed Pinellia Pedattsecta were collected, and NIR and MIRspectral data of these samples were acquired. Discriminant modelsfor the individual data and the fused data were developed with the partial least squares-discriminant analysis ( PLS-DA) method, and were evaluated by the classification accuracy ( ACC) . Results The ACC of PLS-DA model for NIR data was 100% in the training set and 84. 62% in the test set respectively. The ACC of PLS-DA model for MIR data was 100% in the training set and 92.41% in the test set respectively. By combining NIR and MIR spectroscopy data, the ACC of PLS-DA model was 100% in both the training set and test set; moreover af erda afusion the samples present edobviousclus eringphenomenonin hela en variable space of PLS-DA model. Conclusion Such a data fusion approach might significantly improve the accuracy of infrared spectrum identification of ginger-processed Pineliternt and posibly provides a new research idea for identifying the ginger-processed PineUiaternata to ensure its safety and efficacy.
- Publication
Journal of Beijing University of Traditional Chinese Medicine, 2019, Vol 42, Issue 10, p869
- ISSN
1006-2157
- Publication type
Article
- DOI
10.3969/j.issn.1006-2157.2019.10.011