Title :
Electronic nose for coffee quality control
Author :
Pardo, Matteo ; Faglia, Guido ; Sberveglieri, Giorgio ; Quercia, Luigi
Author_Institution :
Brescia Univ., Italy
Abstract :
Two groups of seven coffees have been analyzed with the Pico-1 Electronic Nose (EN) developed at Brescia University. Inside each group, coffees have been classified with PCA and multilayer perceptrons giving classification rates above 90%. Cups of coffee were analyzed by two panels of trained judges who assessed quantitative descriptors and a global index (Hedonic Index, HI) characterizing the sensorial appeal of the coffee. These parameters were predicted starting from the measurements performed with Pico-1. The standard deviation for the prediction of the HI are comparable to the uncertainty of the HI itself (0.2 on a 1 to 9 scale)
Keywords :
array signal processing; feature extraction; food processing industry; gas sensors; intelligent sensors; learning (artificial intelligence); multilayer perceptrons; pattern classification; principal component analysis; quality control; Hedonic Index; PCA; Pico-1 nose; coffee quality control; electronic nose; feature extraction; global index; high classification rates; multilayer perceptrons; quantitative descriptors; sensorial appeal; supervised learning; thin film sensors; Biological materials; Chemical sensors; Crystalline materials; Electronic noses; Inorganic materials; Instruments; Organic materials; Performance evaluation; Quality control; Sensor arrays;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE
Conference_Location :
Budapest
Print_ISBN :
0-7803-6646-8
DOI :
10.1109/IMTC.2001.928799