Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/55583
Title: Investigating the factors contributing to dark cutting in Australian Grain Fed Cattle - Dataset
Contributor(s): Steel, Cameron  (creator); McGilchrist, Peter  (supervisor)orcid ; Cowley, Frances  (supervisor)orcid 
Publication Date: 2022
DOI: 10.25952/j12h-7847
Handle Link: https://hdl.handle.net/1959.11/55583
Related Research Outputs: https://hdl.handle.net/1959.11/55582
Abstract/Context: A compilation of industry stakeholder data for the production and grading of grain-fed beef cattle across southern QLD and northern NSW. Contains 6 year retrospective MSA carcass grading data. 2011-2017. Compiled as cattle lot group data with N <10 removed. Contains BOM weather data from stations close to each of the corresponding cattle sources (Feedlots) Contains Feedlot data collected from the relative lots of cattle including, induction, health, exit and trucking records. Contains weather data captured and amalgamated from on site weather stations where available from feedlots and processors of cattle origin. Recorded in 15-minute or 30 minute increments. The files are recorded and compiled as .csv. The MSA grading feedback files as well as the relative feedlot, processor and weather data were combined and amalgamated to investigate the impacts of factors across the grain-fed cattle supply chain, to discover factors that are contributing to dark cutting beef.
Publication Type: Dataset
Fields of Research (FoR) 2020: 300399 Animal production not elsewhere classified
Socio-Economic Objective (SEO) 2020: 241303 Carcass meat (incl. fish and seafood)
Keywords: Dark cutting
cattle
feedlot
Weather
beef
Location: Southern Qld and Northern NSW
HERDC Category Description: X Dataset
Project: Bflt.0399
Rights Holder: University of New England
Dataset Stored at: University of New England
Primary Contact Details: Cameron Steel - camcsteel@gmail.com
Dataset Custodian Details: Cameron Steel - camcsteel@gmail.com
Appears in Collections:Dataset
School of Environmental and Rural Science

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