Food Science of Animal Resources (한국축산식품학회지)

Korean Society for Food Science of Animal Resources (한국축산식품학회)
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Nondestructive Estimation of Lean Meat Yield of South Korean Pig Carcasses Using Machine Vision Technique

  • Lohumi, Santosh (Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University) ;
  • Wakholi, Collins (Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University) ;
  • Baek, Jong Ho (Korea Institute for Animal Products Quality Evaluation) ;
  • Kim, Byeoung Do (Korea Institute for Animal Products Quality Evaluation) ;
  • Kang, Se Joo (Korea Institute for Animal Products Quality Evaluation) ;
  • Kim, Hak Sung (Korea Institute for Animal Products Quality Evaluation) ;
  • Yun, Yeong Kwon (Korea Institute for Animal Products Quality Evaluation) ;
  • Lee, Wang Yeol (Korea Institute for Animal Products Quality Evaluation) ;
  • Yoon, Sung Ho (Korea Institute for Animal Products Quality Evaluation) ;
  • Cho, Byoung-Kwan (Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University)
  • Received : 2018.09.10
  • Accepted : 2018.10.04
  • Published : 2018.10.31
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Abstract

In this paper, we report the development of a nondestructive prediction model for lean meat percentage (LMP) in Korean pig carcasses and in the major cuts using a machine vision technique. A popular vision system in the meat industry, the VCS2000 was installed in a modern Korean slaughterhouse, and the images of half carcasses were captured using three cameras from 175 selected pork carcasses (86 castrated males and 89 females). The imaged carcasses were divided into calibration (n=135) and validation (n=39) sets and a multilinear regression (MLR) analysis was utilized to develop the prediction equation from the calibration set. The efficiency of the prediction equation was then evaluated by an independent validation set. We found that the prediction equation - developed to estimate LMP in whole carcasses based on six variables - was characterized by a coefficient of determination ($R^2_v$) value of 0.77 (root-mean square error [RMSEV] of 2.12%). In addition, the predicted LMP values for the major cuts: ham, belly, and shoulder exhibited $R^2_v$ values${\geq}0.8$ (0.73 for loin parts) with low RMSEV values. However, lower accuracy ($R^2_v=0.67$) was achieved for tenderloin cuts. These results indicate that the LMP in Korean pig carcasses and major cuts can be predicted successfully using the VCS2000-based prediction equation developed here. The ultimate advantages of this technique are compatibility and speed, as the VCS2000 imaging system can be installed in any slaughterhouse with minor modifications to facilitate the on-line and real-time prediction of LMP in pig carcasses.

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References

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Cited by

  1. Erratum to: Nondestructive Estimation of Lean Meat Yield of South Korean Pig Carcasses Using Machine Vision Technique vol.39, pp.3, 2018, https://doi.org/10.5851/kosfa.2019.e47
  2. Economic Analysis of the Use of VCS2000 for Pork Carcass Meat Yield Grading in Korea vol.11, pp.5, 2021, https://doi.org/10.3390/ani11051297