Discrimination of apricot cultivars by gas multisensor array using an artificial neural network
Giuseppina Paola Parpinello, Angelo Fabbri, Sara Domenichelli, Veronica Mesisca, Lisa Cavicchi and Andrea Versari
Biosystems Engineering, Volume 97, Issue 3, July 2007, Pages 371-378
2007
บทคัดย่อ
In this study, an array of 10 metal-oxide sensors, a so-called electronic nose, in combination with artificial neural networks (ANN), was used to analyse the headspace of apricot fruits in order to classify 10 different cultivars.
The ANN coupled to the electronic nose required a small computational effort to assure a satisfactory effectiveness. Different configurations were explored, ranging from one to three hidden layers. The single hidden layer ANN with 35 neurons gave a correlation index higher than 80% on test data set. The trained system allowed at least 90% correct classification of apricot cultivars, showing the potential of these new tools in the quality control of fruits.