Literature DB >> 33642037

Lean meat yield estimation using a prototype 3D imaging approach.

Alen Alempijevic1, Teresa Vidal-Calleja2, Raphael Falque3, Phillip Quin4, Edwina Toohey5, Brad Walmsley6, Malcolm McPhee7.   

Abstract

Lean Meat Yield (LMY, %) of carcass is an important industry trait, which currently is not routinely measured in Australian beef abattoirs. Objective on-line technology to determine LMY is key for wider adoption. This paper presents a proof-of-concept approach for estimating the LMY of beef carcasses from the 3D information provided by RGB-D cameras. Moreover, a specifically designed on-line data acquisition system for abattoir applications is presented, consisting of three cameras moving on a scanning rig to generate 3D carcass side reconstructions. The hindquarter is then segmented consistently across all the 3D models to extract curvature information and LMY estimated via non-linear regression based on Gaussian Process models. Sides from 119 carcasses at two different commercial abattoirs were used to evaluate this approach. Results from this preliminary study (RMSE = 3.91%, R2 = 0.69) using curvature, P8 fat and HSCW indicate that 3D imaging of beef carcasses is a viable and relatively accurate technology to estimate LMY. Crown
Copyright © 2021. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Beef; Carcass grading; Computer vision; Lean meat yield

Year:  2021        PMID: 33642037     DOI: 10.1016/j.meatsci.2021.108470

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  1 in total

1.  Assessing the Feasibility of Using Kinect 3D Images to Predict Light Lamb Carcasses Composition from Leg Volume.

Authors:  Severiano R Silva; Mariana Almeida; Isabella Condotta; André Arantes; Cristina Guedes; Virgínia Santos
Journal:  Animals (Basel)       Date:  2021-12-19       Impact factor: 2.752

  1 in total

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