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dc.contributor.authorChannon, HA
dc.contributor.authorD'Souza, DN
dc.contributor.authorDunshea, FR
dc.date.accessioned2020-12-17T03:37:10Z
dc.date.available2020-12-17T03:37:10Z
dc.date.issued2017-12-01
dc.identifier.citationChannon, H. A., D'Souza, D. N. & Dunshea, F. R. (2017). Quantifying production, processing and post-slaughter effects on pork eating quality using random effects meta-regression. TRANSLATIONAL ANIMAL SCIENCE, 1 (4), pp.412-425. https://doi.org/10.2527/tas2017.0038.
dc.identifier.issn2573-2102
dc.identifier.urihttp://hdl.handle.net/11343/254960
dc.description.abstractRandom effects meta-regression techniques, analyzed using a restricted maximum likelihood (REML) approach, was used to determine the influence of various factors that may be experienced or imposed on pigs, carcases and pork on pork eating quality attributes and shear force of the M. longissimus dorsi (loin). This was done to inform the development of a pathway based eating quality system for pork. Estimated means of explanatory variables were obtained for those pathway factors where sufficient published studies met the criteria for inclusion in the analysis. Due to a lack of data for interactions between factors investigated, only single factors were included as fixed terms in the REML models. This analysis identified that moisture infusion (P < 0.001), ageing for more than 2 d post-slaughter (P = 0.006) and tenderstretching (P = 0.006) each resulted in significant improvements in tenderness. Cooking loins to an endpoint temperature of ≥ 80°C negatively impacted both tenderness (P = 0.022) and juiciness (P < 0.001) scores compared with 70 to 74°C. It was not possible to develop algorithms to reliably estimate the effects of multiple factors on pork eating quality attributes to a cuts-based level due to limited studies reporting data for treatment interactions.
dc.languageEnglish
dc.publisherOXFORD UNIV PRESS INC
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.titleQuantifying production, processing and post-slaughter effects on pork eating quality using random effects meta-regression
dc.typeJournal Article
dc.identifier.doi10.2527/tas2017.0038
melbourne.affiliation.departmentAgriculture and Food Systems
melbourne.source.titleTranslational Animal Science
melbourne.source.volume1
melbourne.source.issue4
melbourne.source.pages412-425
dc.rights.licenseCC BY-NC-ND
melbourne.elementsid1327208
melbourne.contributor.authorDunshea, Frank
melbourne.contributor.authorChannon, Heather
melbourne.contributor.authorD'Souza, Darryl
dc.identifier.eissn2573-2102
melbourne.accessrightsOpen Access


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