NDLI: Identification of meat spoilage by FTIR spectroscopy and neural networks

Content Provider	IEEE Xplore Digital Library
Author	Kodogiannis, V.S. Petrounias, I. Kontogianni, E.
Copyright Year	2014
Description	Author affiliation: Fac. of Sci. & Technol., Univ. of Westminster, London, UK (Kodogiannis, V.S.) \|\| Manchester Bus. Sch., Univ. of Manchester, Manchester, UK (Petrounias, I.) \|\| Regional Unit of Heraklion, Gen. Directorate of Dev., Heraklion, Greece (Kontogianni, E.)
Abstract	Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid determination of meat spoilage, Fourier transform infrared (FTIR) spectroscopy technique, with the help of advanced learning-based methods, was attempted in this work. FTIR spectra were obtained from the surface of beef samples during aerobic storage at various temperatures, while a microbiological analysis had identified the population of Total viable counts. A fuzzy principal component algorithm has been also developed to reduce the dimensionality of the spectral data. The results confirmed the superiority of the adopted scheme compared to the partial least squares technique, currently used in food microbiology.
Starting Page	1644
Ending Page	1651
File Size	2747567
Page Count	8
File Format	PDF
ISSN	21614407
e-ISBN	9781479914845
DOI	10.1109/IJCNN.2014.6889395
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Principal component analysis Training Spectroscopy Eigenvalues and eigenfunctions Microorganisms Educational institutions
Content Type	Text
Resource Type	Article

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