Statistical Analysis of Agarwood Oil Compounds based on GC-MS Data

Agarwood is a resinous heartwood and Aquilaria is one of many species that grows a lot in Asia. Traditionally, the quality of agarwood oil is based on color, odor, high fixative properties and consumer perception. This quality grading is performed by trained human graders using sensory panels. Human sensory panels has limitation such as fatigue. Therefore, this study focuses on chemical compounds of Agarwood oil. Using this compounds together with artificial intelligence technique, a new grading system will be proposed. This paper discusses only on the statistical analysis of the chemical compounds. 106 compounds were acquired using GC-MS analysis. To remove insignificant compounds, missing values ratio was computed and out of 109 only 19 compounds remained. These compounds were transformed using natural logarithm to improves the distribution of data.