Linked Life Data

21645699

Source:http://linkedlifedata.com/resource/pubmed/id/21645699

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2011-6-7
pubmed:abstractText
A rapid method based on hyperspectral imaging for detection of Escherichia coli contamination in fresh vegetable was developed. E. coli K12 was inoculated into spinach with different initial concentrations. Samples were analyzed using a colony count and a hyperspectroscopic technique. A hyperspectral camera of 400-1000 nm, with a spectral resolution of 5 nm was employed to acquire hyperspectral images of packaged spinach. Reflectance spectra were obtained from various positions on the sample surface and pretreated using Sawitzky-Golay. Chemometrics including principal component analysis (PCA) and artificial neural network (ANN) were then used to analyze the pre-processed data. The PCA was implemented to remove redundant information of the hyperspectral data. The ANN was trained using Bayesian regularization and was capable of correlating hyperspectral data with number of E. coli. Once trained, the ANN was also used to construct a prediction map of all pixel spectra of an image to display the number of E. coli in the sample. The prediction map allowed a rapid and easy interpretation of the hyperspectral data. The results suggested that incorporation of hyperspectral imaging with chemometrics provided a rapid and innovative approach for the detection of E. coli contamination in packaged fresh spinach.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1873-3573
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 Elsevier B.V. All rights reserved.
pubmed:issnType
Electronic
pubmed:day
15
pubmed:volume
85
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
276-81
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Rapid detection of Escherichia coli contamination in packaged fresh spinach using hyperspectral imaging.
pubmed:affiliation
Department of Food Technology, Faculty of Science, Chulalongkorn University, Bangkok, Thailand. ubonratana.s@chula.ac.th
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't