The use of principal component analysis (PCA) to characterize beef

The use of principal component analysis (PCA) to characterize beef Principal component analysis was performed to study the relationships between chemical, physical and sensory variables ( n =18) measured on longissimus thoracis et lumborum of 79 young bulls from the following ethnic groups: hypertrophied Piemontese, normal Piemontese, Friesian, crossbred hypertrophied Piemontese×Friesian, Belgian Blue and White. The first three PCs explained about 63% of total variability. Sensory characteristics, protein content, shear force and cooking losses resulted the most effective variables for the PC1, while hydroxyproline and ether extract content, as well as hue and lightness were useful to define the PC2. The distribution of the objects on the axes of the first two PCs allowed the identification of two groups, the first one including meats of the hypertrophied animals (Piemontese and Belgian Blue and White) the second one including normal Piemontese and Friesian. However, a considerable variability within groups was noted. The crossbreds were placed between the two previous groups. In conclusion, PCA proved to be a very effective procedure to obtain a synthetic judgement of meat quality. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Meat Science Elsevier

The use of principal component analysis (PCA) to characterize beef

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Publisher
Elsevier
Copyright
Copyright © 2000 Elsevier Science Ltd
ISSN
0309-1740
D.O.I.
10.1016/S0309-1740(00)00050-4
Publisher site
See Article on Publisher Site

Abstract

Principal component analysis was performed to study the relationships between chemical, physical and sensory variables ( n =18) measured on longissimus thoracis et lumborum of 79 young bulls from the following ethnic groups: hypertrophied Piemontese, normal Piemontese, Friesian, crossbred hypertrophied Piemontese×Friesian, Belgian Blue and White. The first three PCs explained about 63% of total variability. Sensory characteristics, protein content, shear force and cooking losses resulted the most effective variables for the PC1, while hydroxyproline and ether extract content, as well as hue and lightness were useful to define the PC2. The distribution of the objects on the axes of the first two PCs allowed the identification of two groups, the first one including meats of the hypertrophied animals (Piemontese and Belgian Blue and White) the second one including normal Piemontese and Friesian. However, a considerable variability within groups was noted. The crossbreds were placed between the two previous groups. In conclusion, PCA proved to be a very effective procedure to obtain a synthetic judgement of meat quality.

Journal

Meat ScienceElsevier

Published: Nov 1, 2000

References

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