Development and validation of novel tool to assess reproductive traits and improve beef cattle reproductive efficiency
|Project start date:||01 June 2016|
|Project end date:||15 September 2018|
|Publication date:||30 October 2018|
|Livestock species:||Grassfed cattle|
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Reproductive performance is the single most important factor related to profitability of northern beef breeding enterprises. Reproductive performance is influenced by the age of puberty, the length of the post-partum anoestrus interval (PPAI; length of time from calving to next oestrus) and the total lifetime productivity or total weight of calves weaned per cow (Mukasa-Mugerwa 1989; Burns et al. 2010). The extensive nature of the northern Australian beef industry hinders data collection on these parameters when compared with beef produced on smaller and more intensive production systems in temperate environments, thus northern businesses are operating without pivotal information to allow them to benchmark and improve future herds.
Northern Australia typically experiences much lower pregnancy rates and weaning rates, especially in first calf heifers, than temperate zones (McGowan et al. 2014). The harsh environments create a significant challenge for breeding cows. Identifying cows that have high reproductive efficiency and building on their superior genetics has the potential to increase reproductive rates in Northern Australia, however, there is a lack of fertility parameter recording. More detailed recording of reproductive performance will lead to robust genetic evaluations and more accurate estimated breeding values (EBV's), which should then lead to greater uptake of those genetics by the commercial industry.
In addition to the issues of performance recording and obtaining knowledge on individual cattle performance, some producers report calf losses between 10-15% from positive pregnancy test diagnosis through to weaning. This translates into $100s of millions in lost production annually on a national scale (McGowan 2014), thus signifying the economic and animal welfare significance of this issue. thus signifying the economic and animal welfare significance of this issue. There are many reasons why calf loss can occur, such as disease, predation, calving difficulty, but due to the extensive environment recording this information is extremely difficult.
Automated livestock management systems (ALMS) present an opportunity to improve individual animal monitoring and management strategies while delivering labour, economic and production benefits. Location telemetry has been used to provide information related to bull/cow (O'Neill et al. 2014) and cow/calf interactions (Swain and Bishop-Hurley 2007). These social interaction data are related to biological effects such as age of puberty and length of postpartum anoestrus. In addition, when combining the social information with data from a Walk-Over-Weighing (WoW) system there is the potential to determine maternal parentage, date of birth and estimated birth weight. There have been a number of studies that have demonstrated that spatial monitoring of social interactions between cattle can be used to determine oestrus and maternal behaviour (Swain and Bishop-Hurley 2007; O'Neill et al. 2014). This project aims to integrate ALMS technologies and determine how emerging precision livestock management can be used within the seedstock industry. The focus is on delivering more accurate quantitative measures of reproductive performance.
Objectives and Aims
The overall aim of the project is to use a range of ALMS technologies to identify various stages of the reproductive cycle in an extensive beef breeding operation, by monitoring both adult cows and pre-pubertal heifers. Reproductive measures include the onset of puberty, oestrus and mating activity, date of calving, calf and cow weights, maternal parentage, cow/calf interactions signifying mothering ability, calving interval and postpartum anoestrus. The measures will be recorded using a combination of technologies including: walk over weighing systems, proximity loggers, accelerometers and visual recognition software.
The range of technology that has been used in this project can be combined to provide almost a complete picture of the heifer's development and determine both the age of puberty and date of conception.
Identifying age of puberty
The proximity sensor data was analysed to identify the formation of small sub groups of cattle in oestrus, known as a sexually active group (SAG), by comparing the confirmed time of oestrus with changes in regular social associations for those heifers, as per the social network analyses in Handcock et al. (2009). The sequence that animals traverse a WoW platform has been linked to maternal parentage (Menzies et al. 2018) and oestrus events (Corbet et al. 2018), thus the WoW sequential data was analysed for patterns reflected in the proximity data to determine if first oestrus, and hence puberty, can be determined using WoW data alone. This can be cross-referenced with images of activated Heatmount detectors that were taken as their RFID tags were read as they entered the water compound.
Identifying date of conception
Recording mating information was not an initial objective of the project, however, this information was readily recorded using the range of technology used in this project and further demonstrates the technologies usefulness for commercial application. An estimate of foetal age was recorded at each ultrasound, which can be compared with peaks in heifer-bull contacts recorded by proximity sensors to indicate date of conception, as reported by O'Neill et al. (2014). Independently, the sequences in the RFID data can be compared at similar time points to determine if the bull and heifer in oestrus cross the RFID reader together to provide an estimate of oestrus and date of conception, similar to Corbet et al. (2018).
Outcomes for industry
The use of paddock based automated data capture is still relatively new technology. This project is the first time that it has been used to attempt to identify age of puberty in cattle. Each new application and new group of cattle provides new challenges but also helps provide some new learnings that will ensure the technology progresses to deliver practical applied solutions for industry.
|Project manager:||Nick Sangster|
|Primary researcher:||Central Queensland University|