• DocumentCode
    508243
  • Title

    Application of Near Infrared Spectroscopy in Rapid Determination of Adenosine and Polysaccharide in Cordyceps Militaris

  • Author

    Chang-ji, Yuan ; Shi-jie, Lan ; Guo-dong, Yan ; Di, Wang ; Jia-hui, Lu ; Qing-fan, Meng

  • Author_Institution
    No. 1 Hosp., Jilin Univ., Changchun, China
  • Volume
    3
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    578
  • Lastpage
    582
  • Abstract
    The adenosine and polysaccharide contents in cordyceps militaris were analyzed with near infrared spectroscopy (NIRS) by establishing models with partial least square (PLS). Varies pretreating spectra methods were used for conversion of NIRS in order to remove the noise in the spectra. The pretreated spectra were applied to develop PLS quantitative analysis models respectively. Each model was optimized by selecting the most suitable amount of factors. The optimal model was selected depend on the root mean squares of calibration sets calculate by cross-validation (RMSECV) and the root mean squares of predicted sets (RMSEP). The RMSECV values of the optimum PLS models for determination adenosine and polysaccharide contents were 0.7592 and 0.0093 respectively. Using this optimum model for determination of adenosine and polysaccharide contents in cordyceps militaris mycelium powder, The RMSEP values were 0.6720 and 0.0083 respectively.
  • Keywords
    chemical variables measurement; least mean squares methods; signal processing equipment; spectrochemical analysis; adenosine; cordyceps militaris; cross validation; near infrared spectroscopy; partial least square; polysaccharide; root mean square; Biological system modeling; Calibration; Chemical analysis; Computer applications; Fungi; Infrared spectra; Least squares methods; Military computing; Powders; Root mean square;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.154
  • Filename
    5366186