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REVIEW
Contents Vol 65(8)

The potential of various phenotypic traits to predict feedlot production in cattle – a systematic review

Andreas H. R. Hentzen A and Dietmar E. Holm https://orcid.org/0000-0002-9340-6573 A *
+ Author Affiliations
- Author Affiliations

A Department of Production Animal Studies, Faculty of Veterinary Science, University of Pretoria, Private Bag X04, Onderstepoort 0110, South Africa.

* Correspondence to: dietmar.holm@up.ac.za

Handling Editor: Karen Harper

Animal Production Science 65, AN24245 https://doi.org/10.1071/AN24245
Submitted: 26 July 2024  Accepted: 28 April 2025  Published: 22 May 2025

© 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing

Abstract

Context

Visual evaluation of phenotypic traits is an old and still practiced management tool in the beef industry. Beef production has improved because of the constant visual re-evaluation of phenotypic traits that are associated with production. Current data exposed the need to put all existing knowledge together in context.

Aims

This literature review is to determine the value of individual predictor variables based on existing knowledge, with the view of further improving, expanding, and refining the measured traits.

Methods

This systematic literature review focused on phenotypic traits and their potential associations with production. The traits needed to be predictive in nature. We particularly focused on studies involving intensive production systems, such as feedlots. A search of keywords related to the topic was performed on published articles and textbooks. This included textbooks from the seed stock industry.

Key results

Several, but not all, studies have demonstrated a positive association between phenotypic cattle traits and subsequent feedlot performance. The sensitivity of the measurement varied. The phenotypic traits investigated were either visually appraised and/or linearly measured. Studies focused on muscle and skeletal development because of their contribution to growth. Specific phenotypic traits were investigated, rather than a more holistic approach and/or combination thereof. For example, two different studies evaluated the predictive ability of dimensions of the cannon bone: one investigating the circumference and another the length.

Conclusion

The consulted literature revealed limited evidence that phenotypic traits of incoming feeder calves can predict feedlot production. The current information needs more structure and refinement in measurement and reporting to find its application in a beef feedlot operation.

Implications

A structured phenotypic evaluation before onset of the feeding phase in beef feedlots carries numerous advantages in beef production. The potential of precision feeding calves to phenotypically established production-related profiles can result from this study.

Keywords: animal functional traits, animal production, cattle feedlot, feedlot efficiency, feedlot growth rate, phenotype, precision farming.

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