On the compositional analysis of fatty acids in pork

Fatty acid (FA) composition of pork is an important issue for the pig industry and consumers. Fatty acid composition is commonly described as the percentages of a set of FA relative to total FA and therefore should be statistically treated as compositional data. To our knowledge there is no referenc...

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Bibliographic Details
Authors: Ros Freixedes, Roger, Estany Illa, Joan
Format: article
Status:Versión aceptada para publicación
Publication Date:2014
Country:España
Institution:Universitat de Lleida (UdL)
Repository:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/67946
Online Access:https://doi.org/10.1007/s13253-013-0162-x
http://hdl.handle.net/10459.1/67946
Access Level:Open access
Keyword:Compositional data
Intramuscular fat
Meat quality
Subcutaneous fat
Description
Summary:Fatty acid (FA) composition of pork is an important issue for the pig industry and consumers. Fatty acid composition is commonly described as the percentages of a set of FA relative to total FA and therefore should be statistically treated as compositional data. To our knowledge there is no reference in the literature where specific methods for compositional data analysis have been applied to analyze FA composition in meat quality research. The purposes of this study were (1) to present an overview of compositional data analysis techniques, (2) to apply them to the analysis of the FA composition of muscles and subcutaneous fat from 941 pigs as a case study, and (3) to discuss and interpret the results with respect to those obtained using standard techniques. Results from both approaches indicate that FA composition differed across tissues and muscles but also, for a given muscle, with the intramuscular fat content. It is concluded that FA composition in pork did not display enough variability to become critical for standard statistics, particularly if the individual FA parts remain the same across experiments. However, even in such case, compositional analysis may be useful to correctly interpret the correlation structure among FA.