Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/52133
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dc.contributor.authorSteel, Cameronen
dc.contributor.authorLees, A Men
dc.contributor.authorTarr, Gen
dc.contributor.authorWarner, Ren
dc.contributor.authorDunshea, Fen
dc.contributor.authorCowley, Fen
dc.contributor.authorMcGilchrist, Pen
dc.date.accessioned2022-05-13T04:02:04Z-
dc.date.available2022-05-13T04:02:04Z-
dc.date.issued2022-05-
dc.identifier.citationInternational Journal of Biometeorology, 66(2), p. 263-274en
dc.identifier.issn1432-1254en
dc.identifier.issn0020-7128en
dc.identifier.urihttps://hdl.handle.net/1959.11/52133-
dc.description.abstract<p>This study conducted a retrospective analysis of historical Meat Standard Australia (MSA) carcass data in combination with Bureau of Meteorology (BOM) weather data, to evaluate the relationship between climatic conditions prior to feedlot departure on the incidence of dark cutting grain-fed beef. Data records for 2,795,754 carcasses from 17 commercial feedlots over a 6-year period were evaluated within this study. Carcasses were consigned to 16 abattoirs. Weather data from BOM were recorded at 30-min intervals and were obtained from weather stations with the closest proximity to each feedlot. These data were used to calculate the Temperature Humidity Index (THI). Climatic data were amalgamated into daily observations and a series of predictors including ambient temperature (T<sub>A</sub>, °C), relative humidity (RH, %), wind speed (WS, m/s), rainfall (mm) and THI. In addition, lag interactions from 24 h out to 28 days prior to exiting the feedlot were generated. The incidence of dark cutting was determined as percentage per cohort with an ultimate pH > 5.7. Data were analysed using three models: model 1 included feedlot, abattoir, hormone growth promotant status and sex as fixed effects. Model 2 incorporated the fixed effects within model 1 and minimum, maximum and standard deviation (SD) of T<sub>A</sub> and RH, daily range in T<sub>A</sub>, average WS and rainfall as random effects. Model 3 incorporated minimum, maximum, range and SD of THI, average WS and rainfall as random effects in addition to the fixed effects of model 1. The incidence of dark cutting within feedlot had a 10.1% range in estimated means with the lowest incidence was observed at feedlot 17 (0%) and highest incidence at feedlot 10 (10.1%). The inclusion of the climatic variables in model 2 and model 3 accounted for an additional 0.1 to 0.2% of the incidence of dark cutting carcasses. Higher maximum T<sub>A</sub>, RH and THI in the 3 to 28 days prior to consignment were all associated with an increased incidence of dark cutting (<i>P</i> < 0.05), but not in the 48 h preceding consignment (<i>P</i> > 0.05). Low minimum T<sub>A</sub> and low THI were also associated with an increase the incidence of dark cutting across all lag periods (<i>P</i> < 0.05). Increased variation in THI and T<sub>A</sub> in the 48 h prior to consignment increased dark cutting (<i>P</i> < 0.05) while increased standard deviation (SD) of temperature and THI range also increased dark cutting in the 14 and 28 day prior to feedlot exit (<i>P</i> < 0.05). Smaller minimum ranges in TA in the 28 days prior to consignment also reduced dark cutting (<i>P</i> < 0.05). Climatic conditions accounted for a further 0.1 to 0.2% of the incidence of dark cutting, whereas animal management factors, feedlot and abattoir were able to account for 21% of dark cutting. These data suggest that climatic conditions appear to have an inherent role in the incidence of dark cutting, albeit a small impact. Regardless, understanding the influence of climatic conditions on dark cutting allows for the implementation of management strategies within the supply chain to further reduce the impact of climatic conditions on grain-fed cattle.</p>en
dc.languageenen
dc.publisherSpringeren
dc.relation.ispartofInternational Journal of Biometeorologyen
dc.titleThe impact of weather on the incidence of dark cutting in Australian feedlot cattleen
dc.typeJournal Articleen
dc.identifier.doi10.1007/s00484-021-02180-3en
dc.identifier.pmid34468837en
dc.subject.keywordsTemperature Humidity Indexen
dc.subject.keywordsHeat loaden
dc.subject.keywordsThermal comforten
dc.subject.keywordsBiophysicsen
dc.subject.keywordsEnvironmental Sciencesen
dc.subject.keywordsMeteorology & Atmospheric Sciencesen
dc.subject.keywordsPhysiologyen
dc.subject.keywordsEnvironmental Sciences & Ecologyen
dc.subject.keywordsHeat stressen
local.contributor.firstnameCameronen
local.contributor.firstnameA Men
local.contributor.firstnameGen
local.contributor.firstnameRen
local.contributor.firstnameFen
local.contributor.firstnameFen
local.contributor.firstnamePen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emailcsteel5@une.edu.auen
local.profile.emailalees4@une.edu.auen
local.profile.emailfcowley@une.edu.auen
local.profile.emailpmcgilc2@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeGermanyen
local.format.startpage263en
local.format.endpage274en
local.identifier.scopusid85114038796en
local.peerreviewedYesen
local.identifier.volume66en
local.identifier.issue2en
local.contributor.lastnameSteelen
local.contributor.lastnameLeesen
local.contributor.lastnameTarren
local.contributor.lastnameWarneren
local.contributor.lastnameDunsheaen
local.contributor.lastnameCowleyen
local.contributor.lastnameMcGilchristen
dc.identifier.staffune-id:csteel5en
dc.identifier.staffune-id:alees4en
dc.identifier.staffune-id:fcowleyen
dc.identifier.staffune-id:pmcgilc2en
local.profile.orcid0000-0003-4898-2843en
local.profile.orcid0000-0002-6475-1503en
local.profile.orcid0000-0003-3265-1134en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/52133en
local.date.onlineversion2021-09-01-
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleThe impact of weather on the incidence of dark cutting in Australian feedlot cattleen
local.relation.fundingsourcenoteFunding for this study was provided by Meat and Livestock Australia P/L., North Sydney, NSW, Australia. Grant number: B.FLT.0399 – Evaluation of factors contributing to the incidence dark cutting in grain-fed cattle.en
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorSteel, Cameronen
local.search.authorLees, A Men
local.search.authorTarr, Gen
local.search.authorWarner, Ren
local.search.authorDunshea, Fen
local.search.authorCowley, Fen
local.search.authorMcGilchrist, Pen
local.uneassociationYesen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.identifier.wosid000691938900001en
local.year.available2021en
local.year.published2022en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/39166382-fe6f-4594-8d1e-7cfd84c1ad66en
local.subject.for2020300302 Animal managementen
local.subject.seo2020280101 Expanding knowledge in the agricultural, food and veterinary sciencesen
Appears in Collections:Journal Article
School of Environmental and Rural Science
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