Document Detail


Detecting spoiled fruit in the house of the future.
MedLine Citation:
PMID:  18486654     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
An electronic nose based on acoustic wave sensors has been developed to detect spoilt fruit. Different varieties of fruits, edible and rotten, were analysed. Starting from six sensors, the minimum number of sensors capable of discriminating between spoiled and unspoiled fruit was found. The discrimination capability of the sensor array was studied separately for each fruit variety, as well as for the whole set. Mathematical models were built to classify the fruits within a fruit variety, in an objective and clear way. The models were able to distinguish between edible and rotten fruits with 100% success for New Hall oranges, Golden apples, Kiwis and William pears, and with 97.2% of success for the Starking apples. Without forming fruit variety subsets, discrimination between edible and rotten fruit was achieved with 95% success.
Authors:
Daniel L A Fernandes; João A B P Oliveira; M Teresa S R Gomes
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Publication Detail:
Type:  Journal Article     Date:  2008-02-07
Journal Detail:
Title:  Analytica chimica acta     Volume:  617     ISSN:  1873-4324     ISO Abbreviation:  Anal. Chim. Acta     Publication Date:  2008 Jun 
Date Detail:
Created Date:  2008-05-19     Completed Date:  2008-06-23     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0370534     Medline TA:  Anal Chim Acta     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  171-6     Citation Subset:  -    
Affiliation:
CESAM & Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal.
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