Development of the BeefSpecs fat calculator to assist decision making to increase compliance rates with beef carcass specifications

Abstract

The BeefSpecs fat calculator is a decision-support system developed to assist decision making on-farm to improve compliance rates with beef carcass specifications. BeefSpecs is underpinned by a research model run in conjunction with a translation process that converts inputs recorded in live animal and carcass assessment language into research model parameters. In contrast to many other research modelling systems, the changes in body composition predicted by the research model that underpins BeefSpecs are driven by growth rate. Use of this model removes the need for information concerning feed intake and dietary characteristics, which are impractical to collect on a routine basis in commercial production systems. A translation process was developed to use traits that are recorded routinely on-farm during normal production activities while allowing the original modelling system to run efficiently and accurately. This process aligns BeefSpecs with the language used by industry and increases the confidence of users in the underlying model theories. The outputs produced by BeefSpecs include final liveweight, final subcutaneous fat depth and hot standard carcass weight at the end of a specified feeding period. These traits contribute to the carcass specifications used to determine carcass value in the domestic and international markets supplied by the Australian beef industry, which directly aligns BeefSpecs with the decision-making styles of beef producers. During the development of BeefSpecs, potential users were consulted and enlisted in the evaluation process.

Postweaning substitution of grazed forage with a high-energy concentrate has variable long-term effects on subcutaneous fat and marbling in Bos taurus genotypes1

“…These findings, coupled with other data and samples obtained, will enable more detailed studies of fat depot development and beef quality and allow for the development and refinement of phenotypic prediction models (e.g., Walmsley et al, 2014). In regard to the latter, this experiment has been used to determine total body fatness and the relative proportions of fat in subcutaneous, in- Table 7.…”

Genetic variation in residual feed intake is associated with body composition, behavior, rumen, heat production, hematology, and immune competence traits in Angus cattle1

“…This required calculation of the energy as fat and protein in the empty body weight, and multiplying each by their respective energy densities. Empty body fat (EBF; kg) and protein (EBP; kg) were calculated using the model described by Walmsley et al (2014), and used BW and RIBFAT as inputs, then multiplying EBF and EBP by their respective energy densities (39.3 and 23.6 MJ/kg). Heat production for tissue gain (HPgain) was calculated as ER as fat divided by 0.75 plus ER as protein divided by 0.20.…”

Prediction of ossification from live and carcass traits in young beef cattle: model development and evaluation1

“…The weakness of model H is HSCW and even CP8 fat depth are not simple measures to record accurately on live animals. However, when used in association with a phenotypic prediction system like the BeefSpecs calculator (Walmsley et al, 2014), which predicts carcass P8 rump fat and HSCW, model H could produce predictions of ossification that align with physiological expectations.…”

“…The predictions made by carcass grading systems can be used in association with phenotypic prediction systems, such as the BeefSpecs calculator (Walmsley et al, 2014), to provide predictions of eating quality up to 200 d prior to slaughter. This has the capacity to assist producers make management decisions to improve compliance rates with carcass market specifications and improve eating quality.…”