Discrimination of Marihuana Using Cluster Analysis

Abstract

Marihuana was discriminated using cluster analysis programing in Basic. The peak areas of three compounds in marihuana separated using gas chromatography (GC) and the areas of eight mass fragment ions obtained using gas chromatograph-mass spectrometry (GC-MS) were used for the discrimination. These areas were correctedusing an internal standard and normalized according to a definite rule. This normalization method gave smaller experimental errors than those found by using only an internal standard. The normalization values were used for cluster analysis. As a result, the discrimination of marihuana was performed using the minimum Euclidean distance and the result was shown with the dendrogram obtained from the cluster analysis.