The ability of chemical sensors to differentiate and match samples of apple flavors and essences is of interest to the flavor and food industries. This study evaluated the feasibility of using a prototype chemical sensor for the differentiation of apple flavors and essences. Volatile headspace gases from 20 flavors and four essences were measured with a gas chromatograph and the prototype chemical sensor. A principal component analysis (PCA) reduced the chemical sensor data into two principal factors that accounted for 96% of the variance in the sensor measurements. A hierarchical cluster analysis (HCA) of the PCA data put two flavors and essences into one cluster and the remaining 22 into another. The HCA analysis also provided a breakdown of the clusters into subgroups by similarity. The subgroups were used to determine matches with eight unknowns, six flavors, and two essences. The prototype chemical sensor correctly identified all six unknown flavors. Three were absolute matches, and three matched more than one unknown (one of which was the correct flavor). Visual comparisons of gas chromatograms of known and unknown samples led to absolute matches of five of the six unknown flavor samples. Neither measuring method identified the two unknown essences. These results suggest that it is feasible to use the chemical sensor prototype to differentiate between apple flavors or essences. One potential use of chemical sensor technology is in quality control and food safety programs of food ingredients and products.
|Original language||English (US)|
|Number of pages||4|
|Journal||Transactions of the American Society of Agricultural Engineers|
|State||Published - Sep 1 2005|
All Science Journal Classification (ASJC) codes
- Agricultural and Biological Sciences (miscellaneous)