Abstract
A mass spectrometer based chemical sensor was used to model citrus peel oils. Seven samples and one duplicate were analyzed and subsequently modeled with multivariate analyses such as principal component analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). Discrimination between samples was excellent with clear distinctions between the samples and considerable overlap of the duplicate sample. Samples were also analyzed with a gas chromatograph/mass spectrometer (GC/MS) using similar multivariate models. GCMS results were similar to the ones obtained by sampling the static headspace, but with longer analysis times. Statistics obtained using SIMCA analysis allowed for the determination of which samples were most similar to a target sample.
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