Development of the BeefSpecs fat calculator: a tool designed to assist decision making to increase on-farm and feedlot profitability

Walmsley, B. J.; Oddy, V. H.; McPhee, M. J.; Mayer, David G.; McKiernan, W. A.

doi:10.36334/modsim.2011.b1.walmsley

Cited by 3 publications

References 9 publications

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

2014

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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.

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

2014

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BeefSpecs fat calculator to assist decision making to increase compliance rates with beef carcass specifications: evaluation of inputs and outputs

et al. 2014

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This study evaluated the BeefSpecs fat calculator, a decision-support system developed to assist the beef industry to increase compliance rates with carcass specifications (weight and fat specifications). A challenge to the BeefSpecs calculator and a sensitivity analysis were used to evaluate the inputs and outputs of BeefSpecs. Five industry datasets (n = 80, 97, 68, 25, and 13 for Datasets 1–5, respectively) of Bos taurus, Bos indicus, and Bos taurus × Bos indicus breeds for steers and heifers were collated to challenge BeefSpecs, and a nine-way factorial matrix (n = 57 600) of input variables was created for the sensitivity analysis. There were no significant (P > 0.05) differences in the mean bias between observed and predicted values in any of the datasets but there were significant (P < 0.01) differences in the unity of slope for Datasets 2, 3, and 5. The root-mean-square error was 1.72, 2.61, 2.87, 2.68, and 2.00 mm for Datasets 1–5. The decomposition of the mean-square error of prediction indicated that most of the error contained in the predictions of all models was of a random nature (94%, 85%, 85%, 95% for Datasets 1–4), except in Dataset 5, which had a 47% proportion of error in the slope component. All datasets indicated little bias (0.13%, 12.19%, 12.69%, 0.60%, and 0.12% for Datasets 1–5) in the model predictions. An analysis of variance with the nine-way factorial matrix on the predicted output of final P8 fat was conducted for the sensitivity analysis. A significant (P < 0.01) four-way interaction of days on feed × frame score × initial liveweight × sex was detected. Final P8 fat was sensitive to measurement error in the inputs of frame score when animals had longer feeding periods (e.g. 180 days) and to initial P8 fat when animals had lower initial liveweights (e.g. 200 kg) and higher frame scores (e.g. 7). For each unit of error in estimating frame score, BeefSpecs predicts final P8 with an error of up to 2.3 mm in heifers and up to 1.7 mm in steers. Error in the estimation of initial P8 fat of 2 mm will result in an error of up to 3 mm in the prediction of final P8 fat. The sensitivity analysis of BeefSpecs input variables (frame score and initial P8 fat) on the prediction of final P8 fat indicates that increasing the accuracy of estimating frame score and P8 fat is an issue that needs addressing.

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Modelling trimmed fat from commercial primal cuts

Laurenson¹,

Walmsley²,

Oddy³

et al. 2013

Piantadosi, J., Anderssen, R.S. And Boland J. (Eds) MODSIM2013, 20th International Congress on Modelling and Simulation

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A number of studies over the last five years have been conducted to determine total body fat (kg) in cattle and subsequently retail beef yield. Abattoirs are not consistent in the quantity of fat they trim off commercial bone-out primal cuts (e.g., striploin, cube roll etc.). The trimming of fat on a single primal by different abattoirs can range from 3 to 7 mm. If a relationship between mm of fat trimmed and kg of fat removed from primal cuts was developed then total body fat (kg) from commercial slaughters could then be estimated. The estimate of total body fat would assist in establishing a method for determining denuded yield which would then be used as a national standard for describing retail beef yield independent of abattoir. The estimate of retail beef yield would then be implemented into the BeefSpecs calculator.The objective of this study was to develop a relationship between trim (mm) and kg of fat removed. Images from X-ray computed tomography (CT) scans of 8 primal cuts from 10 Angus steers were manipulated to generate CT scan images for trims ranging from 0 to 15 mm. These images were analysed to determine the weights of fat and muscle in each primal, which were subsequently converted to ratios. Eleven non-linear growth functions were fitted to the generated data and compared to assess their ability to accurately predict the trimmed muscle ratio. The Schnute growth function was identified as the best fit model with the lowest AICc (corrected Akaike's Information Criterion) (AICc = -480.879, adjusted R 2 = 0.945, RMSE = 0.023). The proposed model (and parameter estimates) can be used to estimate the kg of fat removed and therefore aid in the estimation of retail beef yield.

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Development of the BeefSpecs fat calculator: a tool designed to assist decision making to increase on-farm and feedlot profitability

Cited by 3 publications

References 9 publications

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

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

BeefSpecs fat calculator to assist decision making to increase compliance rates with beef carcass specifications: evaluation of inputs and outputs

Modelling trimmed fat from commercial primal cuts

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