Premium
Classification of Adipose Tissue Species using Raman Spectroscopy
Author(s) -
Beattie J. Renwick,
Bell Steven E. J.,
Borggaard Claus,
Fearon Anna M.,
Moss Bruce W.
Publication year - 2007
Publication title -
lipids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.601
H-Index - 120
eISSN - 1558-9307
pISSN - 0024-4201
DOI - 10.1007/s11745-007-3059-z
Subject(s) - principal component analysis , linear discriminant analysis , partial least squares regression , multivariate statistics , adipose tissue , pattern recognition (psychology) , multivariate analysis , artificial intelligence , mathematics , chemistry , statistics , computer science , biochemistry
In this study multivariate analysis of Raman spectra has been used to classify adipose tissue from four different species (chicken, beef, lamb and pork). The adipose samples were dissected from the carcass and their spectra recorded without further preparation. 102 samples were used to create and compare a range of statistical models, which were then tested on 153 independent samples. Of the classical multivariate methods employed, Partial Least Squares Discriminant Analysis (PLSDA) performed best with 99.6% correct classification of species in the test set compared with 96.7% for Principal Component Linear Discrimination Analysis (PCLDA). Kohenen and Feed‐forward artificial neural networks compared well with the PLSDA, giving 98.4 and 99.2% correct classification, respectively.