Application of an electronic nose to the discrimination of coffees

✍ Scribed by J.W. Gardner; H.V. Shurmer; T.T. Tan

• Publisher: Elsevier Science
• Year: 1992
• Tongue: English
• Weight: 529 KB
• Volume: 6
• Category: Article
• ISSN: 0925-4005
• DOI: 10.1016/0925-4005(92)80033-t

✦ Synopsis

An investigation has been carried out into the response of an array of twelve tin oxide sensors to the headspace of cotT,ee packs. Discriminant and classification function analyses are performed on the array response to each of three commerdial coffees (covering two different blends and two roasts) as well as one coffee which has been subjected to a range of six roasting times. Multivariate functions are calculated from the entire data set (90 samples) or alternatively using half of it, to permit cross-validation. A success rate of 89.9% is achieved with the former procedure in classifying the three commercial coffee odours directly from the response (change in sensor conductances) of the array. This value falls to 81.1% when half of the data set is used for cross-validation. Preprocessing the array data, by normalizing the response of each sensor over the array, is found to increase the success rate (to 95.5%) on the entire data set only. The effect on coffee odour of a set of six roasting times (zero to 11.5 min) is also investigated and found to be considerable, some sensors registering an increase in conductance by a factor of three. A 100% group classification is achieved with zero and long roasting times, the overall success rate being 88.1%. The main conclusion is that tin oxide gas sensors can be used to discriminate between both the blend and roasting level of coffee, confirming their potential application in an electronic instrument for on-line quantitative process control in the food industry.