Abstract
Breeding companies need tools to monitor puberty onset that are fast, safe, and operable by any technician. Methods currently
available for assessing reproductive development in young bulls are neither safe nor practical enough for routine use. Manual scrotal
circumference (SC) measurement is typically performed once at around 12 months during breeding soundness evaluation, however
many companies have discontinued it altogether due to animal handling risks. Blood-based hormone analysis, while informative, is too
labour-intensive to perform routinely. Consequently, the peripubertal window, during which testicular development and the onset of
steroid hormone production determine future reproductive potential, is rarely monitored systematically. Earlier identification of bulls
ready for semen collection would shorten the generation interval and increase genetic gain, but achieving this requires a novel
monitoring approach.
Performance testing stations provide a unique setting for this: bulls of multiple breeds are present for an extended period, allowing
repeated sampling across the peripubertal window. We monitored 80 beef bulls of five breeds (Aberdeen Angus, Charolais, Hereford,
Limousin, Simmental) monthly over 8 consecutive months, covering ages 6 to 15 months, in collaboration with TYR, Norway's national
beef breeding organisation. Scrotal circumference was measured manually using scrotal tape, while LiDAR depth imaging data were
simultaneously captured via iPhone 16 Pro (iOS 26). The depth images form the training dataset for a deep learning model currently
under development to detect and measure SC by LiDAR only. The goal is to integrate this model into an easy-to-use mobile application
suitable for routine field use, without the need for specialised equipment. In parallel, tail hair samples were collected for LC-MS/MS
quantification of six hormones: five spanning the steroidogenesis pathway (DHEA-S, DHEA, androstenedione, testosterone, and
estradiol) and cortisol as a marker of stress response. Both whole-hair and segmental analyses are planned to resolve the temporal
hormone dynamics that single-timepoint blood sampling cannot capture. Hair segments reflect hormone incorporation during growth,
enabling retrospective measurements of their levels from a single sample.Manual SC growth curves have been completed for all 80
bulls, and iPhone LiDAR depth images have been successfully captured across all monitoring visits. An LC-MS/MS method for
simultaneous quantification of all six hormones in tail hair has been developed and validated on pilot samples by SINTEF, confirming
reliable extraction and detection sensitivity across the full steroid panel. Initial hormone profiling will focus on a selected subset of
Limousin and Angus samples, chosen to capture both breed-level contrast in peripubertal hormonal trajectories and the effect of hair
colour, as Limousin (brown) and Angus (black) represent the two contrasting coat colours among the five breeds studied. Hair colour
has previously been shown to influence testosterone levels measured in hair, making this comparison particularly informative for
method validation. Individual tail hair growth rate was measured in two bulls by shaving, yielding a rate of 2–3 cm/month, consistent
with values reported in the literature. Full calibration across all animals was not feasible, limiting the temporal precision of segmental
hormone assignment at the individual level. This combined approach could provide breeding companies and performance testing
stations with practical, non-invasive tools for routine longitudinal monitoring of reproductive development. The result would be earlier
and more accurate identification of bulls ready for semen collection, improving both breeding efficiency and animal welfare.