Cow-Calf Commentary for Iowa Cattleman Magazine
By Audrey Tarochione - Master’s student with Dr. Randie Culbertson
June 2026
Genetic selection for improved weaned calf health
Bovine respiratory disease (BRD) is one of the most frustrating diseases facing cattle producers. It can be difficult to prevent, reduces calf performance and carcass value, and can leave lasting effects on calf health. The BRD complex is estimated to cost the U.S. feedlot industry at least $1 billion annually in production losses. As cattle markets tighten profit margins and pressure mounts for improved animal health with fewer antimicrobial interventions, understanding what drives BRD - and how to stay ahead of it - has become increasingly important.
Good management remains the foundation for BRD prevention, but practices such as vaccination and low-stress handling are not completely effective at mitigating BRD. Through genetic selection, the industry has an opportunity to make permanent, cumulative gains in BRD resilience. In a recent study at Iowa State University, the heritability of various BRD traits was found to range from 0.050 – 0.097. These estimates are low, which is expected for health traits subject to high environmental influence. That being said, sufficient genetic variation exists to allow for gradual genetic improvement.
The beef industry currently does not have a national cattle evaluation (NCE) for BRD. Multiple challenges contribute to this:
- Animal traceability: Industry segmentation hinders connectivity and data flow through the beef chain. When ownership of calves transfers after weaning, data is lost, including pedigree information that is necessary for genetic evaluations.
- Data collection: Cattle instinctively hide illness, making accurate BRD detection difficult. Subclinical BRD also contributes to performance and economic losses, but these cases generally remain unobserved unless lung scores are recorded at slaughter.
- Phenotyping guidelines: Disease detection is subjective across operations, and the industry has no standardized trait definition or phenotyping guidelines for BRD. This leads to limited and inconsistent data reporting.
The previously mentioned project at Iowa State explored the third limitation by investigating various trait definitions and statistical procedures for use in a genetic evaluation for BRD. Historical treatment records on weaned seedstock calves were used to characterize BRD traits (Table 1). Disease incidence was defined as a binary trait, where a calf either remained untreated (0) or received one or more treatments for BRD (1). Disease severity provided additional granularity and was assessed with two traits. Severity1-3 described number of treatments, where calves were scored as healthy (1), treated once (2), or treated two or more times (3). Severity1-4 incorporated death records with a fourth response level to indicate respiratory death (4).
The current study found trait definition to be more impactful than modelling procedure, and results suggest that a severity trait offers the most potential for a genetic evaluation. Due to the binary status of BRD incidence, there is no observable difference between a calf that recovers after a single treatment and a calf that requires multiple treatments or dies. The increased granularity of disease severity compared to incidence allows for greater capture of between-animal differences. Severity traits showed increased heritability and prediction accuracy, both of which are advantageous to genetic improvement, compared to BRD incidence.
While the development of a BRD national cattle evaluation is not out of the question, it will require coordinated efforts across cow-calf and feedlot sectors, and it starts with good record keeping! Tools such as EID tags can facilitate animal tracking through the production chain, allowing feedlot health events to be linked to verified animal identities. Data collection should include number of treatments and death to leverage as much useful information as possible. Collaboration between producers and breed associations, marketing programs, and data management providers can help to generate large, connected datasets. With consistent data collection and integration across sectors, a reliable and practical genetic evaluation for BRD becomes achievable in time.
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