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Predicting quality measures in beef cattle using ultrasound imaging

Wilson Harron, R.D. Dony

Open publisher page 5 citations

Abstract

A method of determining two quality measures of beef cattle using different classification networks is presented. The method involves calculating texture features from ultrasound images of the beef cattle and then predicting the final percentage intramuscular fat (IMF) and marbling grades associated with the beef cattle. This method can be used in the cattle industry to enhance current breeding techniques.

About this research paper

What this paper is about

A method of determining two quality measures of beef cattle using different classification networks is presented. The method involves calculating texture features from ultrasound images of the beef cattle and then predicting the final percentage intramuscular fat (IMF) and marbling grades associated with the beef cattle. This method can be used in the cattle industry to enhance current breeding techniques.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Method / approach

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Available abstract

A method of determining two quality measures of beef cattle using different classification networks is presented. The method involves calculating texture features from ultrasound images of the beef cattle and then predicting the final percentage intramuscular fat (IMF) and marbling grades associated with the beef cattle. This method can be used in the cattle industry to enhance current breeding techniques.

Key concepts: Marbled meat, Intramuscular fat, Beef cattle, Quality (philosophy), Texture (cosmology), Ultrasound, Ultrasound imaging, Computer science

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