The aroma emanating from fruits can indicate the maturity level and thus the quality and shelf life of the products. In this work it is presented an odour sampling system system (called also electronic nose), to classify the aroma of Diospyros kaki, whose working parameters can have variable configuration making the system flexible. The system can be appropriately reconfigured for each type of sampling. It is formed by a metal oxide semiconductor (MOS) commercial sensors matrix, which are individually controlled, being able to modify by software several parameters of their operating point. Working this way there is not a limited number of sensors but a very high number of virtual sensors. The system shows the ability to discriminate aroma of two Diospyros kaki cultivars. Moreover the instrument is capable to distinguish the fruits, inside the persimmon cultivar cluster, according to the ripe state after few days of storage.

Odour sampling system with modifiable parameters applied to fruit classification

Guarrasi V
2013

Abstract

The aroma emanating from fruits can indicate the maturity level and thus the quality and shelf life of the products. In this work it is presented an odour sampling system system (called also electronic nose), to classify the aroma of Diospyros kaki, whose working parameters can have variable configuration making the system flexible. The system can be appropriately reconfigured for each type of sampling. It is formed by a metal oxide semiconductor (MOS) commercial sensors matrix, which are individually controlled, being able to modify by software several parameters of their operating point. Working this way there is not a limited number of sensors but a very high number of virtual sensors. The system shows the ability to discriminate aroma of two Diospyros kaki cultivars. Moreover the instrument is capable to distinguish the fruits, inside the persimmon cultivar cluster, according to the ripe state after few days of storage.
2013
Istituto di Biofisica - IBF
Electronic nose
Pattern recognition
Microcontroller
Food classification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/172283
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