- 期刊
- OpenAccess
以FT-NIR鑑別中草藥原料之研究
Identification for Raw Materials of Chinese Herbal Medicines Using FT-NIR Spectroscopy
摘要
中草藥在醫學上的用途越來越多而廣，因此中草藥的原料控管是藥廠很重要的一項工作。本研究以擷取自傅立葉轉換之近紅外光光譜（Fourier transform near-infrared, FT-NIR）建立18種中草藥粗原料之鑑別模式。在這項研究中，不同的中草藥原料以研磨成粗粉末型態進行光譜量測，並建立中草藥之光譜資料庫。以NIRFlex進行分光光度計之光譜取得，而光譜前處理和鑑別模式之建立方法則使用NIRCal進行資料轉換與分析。以粉末光譜建立之鑑別模式，對校正組71個樣本，可以達到100%的辨識率；對於驗證組34個樣本，以校正組所建立之模式進行預測分析，可準確辨識33個樣本，其辨識正確率達97%，綜合上論，以FT-NIR進行18種中草藥105個樣本之鑑別可達99%之辨識正確率。
並列摘要
The inclusion of herbal medicines in modern medication is steadily increasing, and the control and monitoring of the herbal medicine materials is a crucial work in the pharmaceutical factory. This study examined the discrimination analysis on FTNIR spectra of 18 kinds of raw medicinal herb materials. Several pattern recognition methods were compared in the identification of these herbal raw materials using Fourier transform near-infrared spectroscopy (FT-NIR). In this study, raw herbal materials (ground into a coarse powder) were used to develop the herbal spectra library. Samples were scanned and pattern recognition techniques were adopted to calculate variations among herbal materials. The spectral pretreatments and pattern recognition methods were conducted using NIRFlex and NIRCal. Regarding 71 samples in the calibration set, the identification accuracy was 100%. In the validation set of 34 samples, 33 samples were successfully discriminated, and the identification accuracy was 97%.