Characterisation of vegetable oils by surface acoustic wave sensing electronic nose

Flavour analysis is typically performed by human organoleptic analysis, which is often expensive and subjective. A novel approach using a surface acoustic wave sensing electronic nose (zNose(TM)) for flavour analysis was explored to characterise 16 types of vegetable oils. Fatty acid composition, iodine value, peroxide value, p-anisidine value and free fatty acid analyses were conducted to determine the quality and characteristics of vegetable oils. The zNose(TM) was employed successfully for qualitative distinction of flavour in different vegetable oils. This is achieved using a visual fragrance pattern, called a VaporPrint(TM), derived from the frequency of the SAW detector. VaporPrint(TM) was shown to be particularly useful for assessing vegetable oil aroma profile in its entirety. This image is created by transforming the time variable to a radial angle with the beginning and end of the analysis occurring at 0degrees, or vertical. A Chemometric method, particularly principal component analysis (PCA), was conducted for electronic nose data processing and identification. Analysis of the score plot of the PCA for the zNose(TM) measurement showed that 97% of the total variance in the data was described by PC 1 and PC 2. The loading plot revealed that five compounds (m, k, n, s, and p) were important for differentiate the vegetable oils. (C) 2004 Elsevier Ltd. All rights reserved.