• DocumentCode
    2003368
  • Title

    Analysis of Agarwood oil (Aquilaria Malaccensis) based on GC-MS data

  • Author

    Ali, Nor Azah Mohd ; Ismail, Nurlaila ; Taib, Mohd Nasir

  • Author_Institution
    Forest Res. Inst. Malaysia, Selangor, Malaysia
  • fYear
    2012
  • fDate
    23-25 March 2012
  • Firstpage
    470
  • Lastpage
    473
  • Abstract
    Agarwood oil has been widely used especially in fragrance, incense, prayers and traditional medicinal. In the Middle East, the market demand for Agarwood oil is very high. Agarwood oil is traded based on high grade and low grade, corresponding to expensive price and cheap price, respectively. Currently, the grading of Agarwood oil, specifically Aquilaria Malaccensis, depends on its physical appearance such as color and odour. This paper presents the analysis of Aquilaria Malaccensis based on GC-MS data. The work involves of statistical technique such as boxplot and PCA. The analysis part was done on 64 chemical compounds on 7 samples of agarwood oil obtained by Forest Research Institute Malaysia (FRIM). It was done via MATLAB ver. R2010a. The result shows that the distribution of chemical compounds in Agarwood oil is not normal and five componets is identified from 64 variables Agarwood oil samples, gathered by boxplot and PCA, individually.
  • Keywords
    chromatography; mass spectra; oils; principal component analysis; statistical analysis; Aquilaria Malaccensis; Forest Research Institute Malaysia; GC-MS; PCA; agarwood oil; chemical compounds; color property; gas chromatography-mass spectra; odour property; physical property; principle component analysis; statistical method; Artificial neural networks; Chemical compounds; Chemicals; Oils; Principal component analysis; Sensors; Signal processing; ARX; Agarwood oil; PCA; data reduction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and its Applications (CSPA), 2012 IEEE 8th International Colloquium on
  • Conference_Location
    Melaka
  • Print_ISBN
    978-1-4673-0960-8
  • Type

    conf

  • DOI
    10.1109/CSPA.2012.6194771
  • Filename
    6194771