Format

Send to

Choose Destination
Lett Appl Microbiol. 2006 Feb;42(2):121-6.

Fast identification of ten clinically important micro-organisms using an electronic nose.

Author information

1
Department of Chemistry, University of Antwerp, Wilrijk, Belgium.

Abstract

AIMS:

To evaluate the electronic nose (EN) as method for the identification of ten clinically important micro-organisms.

METHODS AND RESULTS:

A commercial EN system with a series of ten metal oxide sensors was used to characterize the headspace of the cultured organisms. The measurement procedure was optimized to obtain reproducible results. Artificial neural networks (ANNs) and a k-nearest neighbour (k-NN) algorithm in combination with a feature selection technique were used as pattern recognition tools. Hundred percent correct identification can be achieved by EN technology, provided that sufficient attention is paid to data handling.

CONCLUSIONS:

Even for a set containing a number of closely related species in addition to four unrelated organisms, an EN is capable of 100% correct identification.

SIGNIFICANCE AND IMPACT OF THE STUDY:

The time between isolation and identification of the sample can be dramatically reduced to 17 h.

[Indexed for MEDLINE]
Free full text

Supplemental Content

Full text links

Icon for Wiley
Loading ...
Support Center