The use of carcass traits as indicators of heifer pregnancy in Angus cattle

A primary driver of profitability in the cow-calf sector of the beef cattle industry is the reproductive ability of females, as revenue generated through calf sales to offsets female input costs and contributes to net income. An important measure of reproductive performance is heifer pregnancy, or the ability of heifers to conceive within the first breeding season. Heifers that fail to become pregnant in the first breeding season are often seen as an economic loss and culled from the herd. While these females may be fed out and marketed as feedlot cattle, heifer development costs typically exceed the cost of developing feedlot cattle. The higher capital investment of breeding heifers makes it difficult to generate a positive return on investment when potential replacement heifers are marketed as fed cattle. Heifer pregnancy is influenced by both management and genetics, and research regarding both factors has been performed. Management practices have focused on developing heifers to an ideal body weight at breeding and using body condition scoring (BCS) to evaluate fat coverage. While BCS may provide a good estimate of fat coverage, it is subjective to the individual assigning scores and their expertise. Furthermore, body weight and BCS alone are insufficient for assessing true body composition. Genetic methods of evaluating heifer pregnancy have been successful, but heritability estimates are low, indicating that genetic progress is made at a slow rate through selection. Unlike reproductive traits, carcass traits such as ribeye area (REA), backfat thickness (FAT), and intramuscular fat percentage (IMF) have moderate to high heritability and genetic progress can be made more quickly in these traits. The transition from marketing cattle based on liveweight to marketing cattle based on quality and quantity of product encourages selection of carcass traits. A question that arises from increased genetic selection pressure on carcass trait performance is how selection for these traits have impacted reproductive performance. The objectives of this thesis provide a roadmap to address the potential applications of body composition measures in heifer selection and how carcass trait selection has affected heifer pregnancy rate. Therefore, the objectives of this thesis are to: 1) evaluate the phenotypic relationship between heifer pregnancy and body composition traits, and 2) determine the genetic relationship between heifer pregnancy and carcass traits. Chapter 3 sought to assess the phenotypic relationship between heifer pregnancy and body composition traits. In this study, 124 purebred Angus heifers from the Iowa State University McNay Memorial Research and Demonstration Farm were evaluated during development from weaning until final pregnancy determination. One week after weaning, heifers were randomly allocated to two treatment groups; the restricted average daily gain (ADG) group, developed to 55% of expected mature body weight at breeding (restricted; n=61) and the non-restricted ADG, develop to 65% of expected mature body weight at breeding. The herd average mature body weight was 590 kg. Ultrasound technology was used to measure ribeye area (REA), backfat thickness (FAT), and intramuscular fat thickness (IMF) at five time points during this study. Heifers were synchronized for artificial insemination (AI) using a 7-day CO-Synch protocol. A heat detection patch was applied to monitor visual estrous response. Upon AI breeding, both groups of heifers were transitioned to pasture and managed as one group. Bulls were released for natural service (NS) 10 days following AI breeding for a 45-day breeding season. Pregnancy status was evaluated 33 days following AI breeding and again 30 days following bull removal. Results revealed that heifers developed to 65% of their expected mature body weight at breeding (non-restricted group) had significantly (P<0.05) higher body composition measurements during development, larger pelvic areas, and higher response rate to estrous synchronization, than heifers developed to 55% mature body weight at breeding (restricted group). The percentage of AI bred heifers was 30.19% in the restricted group and 45.76% in the non-restricted group. No significant (P>0.05) difference in AI pregnancy rate was found between the two treatment groups. The final pregnancy rates were 84.91% for the restricted group and 83.05% for the non-restricted group and were not significantly (P>0.05) different between groups. The numerically greater number of AI pregnancies in the non-restricted group is hypothesized to be related to nutrient partitioning in heifers. Since these females in the non-restricted group had a greater nutrient resource compared to the restricted group heifers, they were able to meet the needs of growth and development sooner and had nutrients available to initiate an estrous cycle before the restricted heifers. Two logistic regression models were used to analyze the association between pre-breeding carcass ultrasound traits and final pregnancy outcome. Model outcomes found treatment group and FAT to be significant predictors (P<0.05) of pregnancy outcome. The findings from this study highlight the potential application of FAT as a selection tool for replacement heifers. Furthermore, as industry trends place downward selection pressure on FAT, the consequences of this pressure on heifer pregnancy should be considered. Chapter 4 investigated the genetic relationship between heifer pregnancy and carcass traits using historical records between the years 1996 to 2024 from the ISU McNay Memorial Research and Demonstration Farm. A phenotype file was constructed from 1462 heifer pregnancy records, 4,519 carcass records, and 7,648 weaning weight records. A pedigree file of 10,455 animals with sire generations ranging from 1 to 9 and dam generations ranging from 1 to 11 was used to incorporate genetic relationship into the analysis. Univariate models were used to obtain initial variance component estimates and to provide single-trait heritability estimates as follows: 0.09 ± 0.05 for heifer pregnancy (HP), 0.14 ± 0.03 for weaning weight direct (WWTd), 0.34 ± 0.04 for hot carcass weight (HCW), 0.38 ± 0.04 for ribeye area (REA), 0.39 ± 0.04 for backfat thickness (FAT), and 0.48 for intramuscular fat score (IMF). Bivariate models were run between all traits to gain initial covariance estimates for multivariate modeling. The final multivariate model included HP, REA, FAT, IMF, and WWT. The residual covariance between HP and carcass traits was restricted to zero as not enough records for both HP and carcass traits were collected on the same heifers. The genetic covariance between weaning weight maternal (WWTm), and HP and carcass traits was restricted to zero due to difficulty in disentangling the contribution of WWTd and WWTm. Heritability estimates from multivariate modeling were comparable to those estimated from univariate modeling. Genetic correlations between all traits and HP were negative, with correlations of -0.26 ± 0.23 with REA, -0.21 ± 0.23 with FAT, -0.09 ± 0.21 with IMF, and -0.12 ± 0.27 with WWTd. The results from this chapter imply an antagonistic genetic relationship between HP and carcass traits for the ISU McNay Angus herd. However, future work is needed to validate these results on a large-scale population of Angus cattle, originating from multiple herds.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

thesis

Discipline thesis:degree_discipline

Animal sciences

Department dc:contributor.department

Department of Animal Science

Grantor

Iowa State University

Year dc:date.issued

2025

Author dc:creator

• Phelps, Sarah

Advisors dc:contributor.advisor

• Culbertson, Miranda M.
• Koltes, James E.
• Youngs, Curtis R.

Language dc:language.iso

en

DOI

https://doi.org/10.31274/td-20251215-418

OAI identifier oai:identifier

oai:dr.lib.iastate.edu:20.500.12876/RwyqBWkw