Li, X, Ha, M, Warner, RD et al. (1 more author) (2022) Meta-analysis of the relationship between collagen characteristics and meat tenderness. Meat Science, 185. 108717. ISSN 0309-1740
Abstract
Meta-analysis methods were used to investigate the effects of collagen content, solubility and pyridinoline cross-link content on Warner-Bratzler shear force (WBSF) and sensory tenderness in major meat species. Data was collected from the literature on pork, beef and lamb and analyzed independently for each species. The beef data was categorized into subgroups according to muscle (loin and other muscle) and age (young, <18 months and old, ≥18 months). The results showed that in beef, collagen content and pyridinoline cross-link content were positively correlated with WBSF and negatively with sensory tenderness, while collagen solubility was negatively correlated with WBSF. The correlation coefficients were greater in other beef muscles than loin. Significant correlations between collagen content and tenderness attributes were observed in old beef animals. However, non-significant relationships and large variations were found in pork and lamb. More studies with various muscles and ages are required for an in-depth understanding of the relationship between collagen characteristics and meat tenderness.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Meat Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Meta-analysis; Collagen; Tenderness; Correlation; Muscle; Age |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Aug 2022 13:25 |
Last Modified: | 19 Nov 2022 01:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.meatsci.2021.108717 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:190163 |
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