ArticleJournal of animal science2026
Phenotypic characterization of heifer development using carcass ultrasound in Angus cattle.
Article in Journal of animal science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The utility of carcass ultrasound measurements in heifer development as indicators of reproductive performance was evaluated. Current methods of assessing heifer development include body weight (BW), nutritional status, and body condition score. However, these methods do not measure actual body composition, and the relationship between actual pre-breeding body composition measurements and heifer fertility is poorly understood. Measurements were collected on 124 purebred Angus heifers at the Iowa State University McNay Memorial and Demonstration Research Farm. One week post-weaning (day 0), heifers were randomly allocated into two dietary treatment groups stratified by age and weight. One group of heifers was developed to reach 55% of expected mature BW at the time of breeding (restricted), and the second group was developed to reach 65% of expected mature BW at breeding (non-restricted). Carcass ultrasound measurements and BW data were collected at six time points during heifer development from October 2023 to September 2024 (day 0, 55, 123, 178, 231, and 338). Carcass ultrasound measurements included ribeye area (REA), backfat thickness (FAT), rump fat thickness (RUMP), and percent intramuscular fat (IMF). A controlled internal drug release (CIDR) was used to synchronize heifer estrus cycles for timed-artificial insemination (AI), and Estrotect heat detection patches (Estrotect, Rockway, Inc., Spring Valley, WI) were used to measure estrus response. The final pregnancy diagnosis was made by a veterinarian on day 338, 12 weeks post initial AI in September 2024. Data were analyzed using R Statistical Software 4.4.1. Treatment group differences (P < 0.05) were identified at day 55 for mean measurements of weight, REA, FAT, and RUMP, and at day 178 for IMF. Estrous response rate was higher in the non-restricted group than the restricted (P < 0.05), but the overall pregnancy rates between groups was not significant (P = 0.79). Two logistic regression models were analyzed to capture pregnancy response using body composition measures. Backfat was a significant predictor of heifer pregnancy (P < 0.05). Results from this study can help beef cattle producers determine the appropriate percentage of expected mature BW for developing heifers in their operation, based on specific management practices. Additionally, findings can inspire prospective researchers to further investigate the ideal FAT levels for optimal heifer reproductive performance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.