Visual Image Analysis for a new classification method of bovine carcasses according to EU legislation criteria

Meat Sci. 2022 Jan:183:108654. doi: 10.1016/j.meatsci.2021.108654. Epub 2021 Aug 12.


In the European Community, conformation and fat cover of bovine carcasses is assessed using the SEUROP grading system. In this study we pursued the development of an application software (App) based on Visual Image Analysis, useful for SEUROP and Fat Cover grading of bovine carcasses using a smartphone. The App was trained using 500 bovine carcasses. Carcass conformation and Fat Cover classes were assessed in parallel by expert evaluators and by App. Overall, a high correspondence was found between the measurements of carcasses parameters by operators and by the App, as high as 84.2% for SEUROP and 86.4% for the Fat Cover. In the 15.8% of samples with discordant SEUROP evaluation, and in the 13.6% of samples with discordant Fat Cover evaluation, the operators' and App measurements deviated by only one class. All values also aligned with the requirements expected by the current legislation for the use of automated and/or semi-automated systems able to determine the market value of carcasses.

Keywords: App-Android; SEUROP; Visual Image Analysis.

MeSH terms

  • Adipose Tissue / anatomy & histology*
  • Animals
  • Body Composition
  • Cattle
  • European Union
  • Image Processing, Computer-Assisted / methods*
  • Red Meat / analysis*
  • Red Meat / standards