Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5792082 | Meat Science | 2012 | 8 Pages |
Abstract
Principal component analysis, partial least squares projection to latent structure - discriminant analysis and orthogonal partial least squares projection to latent structure - discriminant analysis were used to build models capable of discriminating the muscle type according to the breed. Data analysis led to an excellent classification for Buffalo and Chianina, while for Holstein Friesian the separation was lower. In the case of Maremmana the use of intelligent bucketing was necessary due to some resonances shifting allowed improvement of the discrimination ability. Finally, by using the Variable Importance in Projection values the metabolites relevant for the classification were identified.
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Authors
Mena Ritota, Lorena Casciani, Sebastiana Failla, Massimiliano Valentini,