Qualitative and quantitative analysis in sandalwood oils using near infrared spectroscopy combined with chemometric techniques

Sandalwood oil is an essential oil which finds very wide application in the flavor and fragrance, pharmaceutical industry. The objective of this study is to use the potential of near infrared spectroscopy as a rapid analytical technique for the qualitative and quantitative assessment of purity in sandalwood oils. The quality and efficacy of sandalwood oils, even though come from the same species, are somewhat different according to growing conditions (origin) and poor extraction methods. Classification of sandal oils based on their NIR spectra is performed by principal component analysis, hierarchical cluster analysis and self organising map (Kohonen neural network). All these techniques clearly differentiate the oils according to the area from which the sandalwood has been cut. Support vector machine regression (SVM R) is used to predict the purity of the oils.