The live weight (LW) and live weight change (LWC) of cattle in extensive beef production is associated with pasture availability and quality. The remote monitoring of pastures and cattle LWC can be achieved with a combination of satellite imagery and walk-over-weighing (WoW) stations. The objective of the present study is to determine the association, if any, between vegetation indices (VIs) (pasture availability) and the LWC of beef cattle in an extensive breeding operation in Northern Australia. The study also tests a suite of VIs along with variables such as rainfall and Julian day to predict the LWC of breeding cows. The VIs were calculated from Sentinel-2 satellite imagery over a 2-year period from a paddock with 378 cattle. Animal LW was measured remotely using a weighing scale at the water point. The relationship between VIs, the LWC, and LW was assessed using linear mixed-effects regression models and random forest modelling. Findings demonstrate that all VIs calculated had a significant positive relationship with the LWC and LW (p < 0.001). Machine learning predictive modelling showed that the LWC of breeding cows could be predicted from VIs, Julian day, and rainfall information, with a Lin’s Concordance Correlation Coefficient of 0.62 when using the leave-one-month-out cross-validation. The LW and LWC were greater during the wet season when VIs were higher compared to the dry season (p < 0.001). Results suggest that the remote monitoring of pasture availability, the LWC and LW is possible under extensive grazing conditions. Further, the use of VIs and other readily available data such as rainfall can be used to predict the LWC of a breeding herd in extensive conditions. Such information could be used to increase the productivity and land management in extensive beef production. The integration of these data streams offers great potential to improve the monitoring, management, and productivity of grazing or cropping enterprises.
Observing calves at birth may help to identify risk factors for, and reduce, calf loss in extensive beef systems. The objectives of this study were to: (1) evaluate two commercial satellite birth alert systems to enable the observation of newborn calves and (2) assess behavioral changes of cows around calving. Vaginal Implant Transmitters (VIT) paired with Global Navigation Satellite System (GNSS) collars were worn by 20 cows in Trial 1 and 10 cows in Trial 2 to identify birthing events. The VIT and GNSS collars contained a temperature sensor, accelerometer, and very high frequency (VHF) to communicate with a handheld tracker, and ultra-high frequency (UHF) for communication between the VIT and GNSS collar, which had two-way communication using Iridium satellites. A change (Brand 1) or drop (Brand 2) in temperature of more than 3 °C and inactivity triggered the VIT to communicate an expelled alert to the collar, which transmitted the birth alert information via Iridium (device ID, date, time and geolocation of the GNSS collar at expulsion). Cows and calves were tracked in the paddock following a birth alert to assess their health and status. Overall, true birth alerts occurred in only 27.6% of devices. Cows remained active on the day of calving travelling 5.54 ± 4.11 and 5.00 ± 2.80 km/day compared to 6.45 ± 2.79 and 6.12 ± 2.30 km/d on days when calving did not occur for Trial 1 and 2, respectively (mean ± SD). Average activity of the accelerometer X- and Y-axis on calving day was reduced by 15%–20% compared to other days in Trial 1 (p < 0.05) but not in Trial 2 (p > 0.05). Results suggest that these two birth alert systems are not suitable for use in extensive systems and the further development of the technology is required. Cows in the current trials remained active on the day of, and after, calving, indicating that a faster, real-time alert system and communication protocol would be required to achieve the aim of finding newborn calves.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.