Title :
Coffee analysis with an electronic nose
Author :
Pardo, Matteo ; Sberveglieri, Giorgio
Author_Institution :
Dept. of Chem. & Phys., Univ. of Brescia, Italy
fDate :
12/1/2002 12:00:00 AM
Abstract :
We present the Pico-1 electronic nose based on thin-film semiconductor sensors and an application to the analysis of two groups of seven coffees each. Cups of coffee were also analyzed by two panels of trained judges who assessed quantitative descriptors and a global index (called Hedonic Index, HI) characterizing the sensorial appeal of the coffee. Two tasks are performed by Pico-1. First, for each group, we performed the classification of the seven different coffee types using principal component analysis and multilayer perceptrons for the data analysis. Classification rates were above 90%. Secondly, the panel test descriptors were predicted starting from the measurements performed with Pico-1. The standard deviations for the prediction of the HI are comparable to the uncertainty of the HI itself (0.2 on a 1 to 9 scale for one group of coffees).
Keywords :
food processing industry; gas sensors; multilayer perceptrons; pattern classification; principal component analysis; semiconductor devices; thin film devices; PCA; Pico-1 electronic nose; SnO2; classification rates; coffee analysis; data analysis; gas sensors; multilayer perceptrons; principal component analysis; thin-film semiconductor sensors; Biological materials; Chemical sensors; Crystalline materials; Data analysis; Electronic noses; Multilayer perceptrons; Organic materials; Semiconductor thin films; Sensor arrays; Thin film sensors;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2002.808038