BCRC 3 - Prediction of carcass attributes in beef cattle

Summary

Failure to meet market specifications for carcass weight and fatness costs producers and the beefindustry a significant amount each year. It has been estimated that from 16 to 29% of feedlot cattle fail to meet specifications for these attributes, and up to 70% don't achieve the more demanding specifications for marbling. No-one really knows whatthe statistics of compliance to specifications and cost of nori-compliance are for grass finished cattle, exceptthat anecdotal evidence suggests that they are at least as great as for feedlot finished cattle. It is recommended that quantitative information on compliance of grass finished cattle be obtained and cost of noncompliance determined forthis sector. 
 Although breeding to better achieve market specifications is an action that can be taken, and is part of current breeding objectives, much of the failure to reach specifications is a consequence of management practices on-farm. Tools to help producers understand the impact of their management(gro^rth, implant, sex) on different cattle types (as described by Framesize and current fatness, and breed) have been developed in this project. These are primarily designed to teach producers the relationships between the things that they have control of (feed supply, growth rate, time, implants), and the way the animals they have respond in terms of fat thickness. "Beefspecs." a calculator that uses practical inputs from producers and combines them with an underpinning model of beef cattle growth and composition was developed during this project.  BeefSpecs Calculator is available on the MLA website​.
"Beefspecs" was developed with inputfrom more than 500 producers, and has been tested with research data and data obtained on-farm. With research data, Beefspecs provides answers within the error of measurement of fatthickness. When used with on-farm data, on average Beefspecs provided an estimate of fat thickness within error of that observed, but there were systematic errors with different farms (and types of cattle). Use of markedIy different underpinning models (computational procedures) generally produced similar results to Beefspecs. A constraint to effective use of "Beefspecs"is the animal assessment skills of producers. It is recommended that further training in practical animal assessment skills be provided to give producers the skills and confidence required to implement management changes to better meet specifications.