Assessing maternal behaviour and calf health in beef cattle

Research output: Book chapter/Published conference paperConference paperpeer-review

Abstract

• Calf mortality is a key issue for the northern Australian beef industry.
• Blood hormonal profiling could be a promising technique to predict maternal behaviour.
• Animal behaviour and environmental interactions can be monitored using wireless sensor systems.

Calf mortality continues to be a key issue for the northern Australian beef industry, and results in significant reductions in productivity, economic profitability, as well as poor animal welfare outcomes (Burns et al., 2010; Chang et al, 2020).

Calf loss during the first two weeks of life alone, has been estimated to cost the northern Australian beef industry more than $54 million annually (Barnes et al., 2017). Calf wastage specifically attributed to post-natal losses within 48 hours has been hard to objectively quantify due to the extensive nature of most pastoral enterprises, although losses in general between calving and weaning remain significant (Burns et al., 2010; Chang et al., 2020). Similar studies for the period immediately post-partum have been done in similar environments in the United States. Large scale studies in the US have demonstrated the majority of calf wastage (57.4 percent) occurs within 24 hours of calving, with almost 75% of total deaths occurring within one week of calving (Patterson et al., 1987). During this period, maternal behaviour of cattle has been found to be an important determinant of neonatal survival (Veissier et al., 1998). This suggests that maternal behaviour may significantly contribute to the economic losses associated with calf wastage post calving.

Maternal behaviour is genetically controlled (Michenet et al., 2016), thus there is the potential to identify cattle with superior maternal behaviour to reduce calf wastage. But a key challenge associated with behavioural traits is the difficulty in measuring and quantifying them. Recording maternal behaviour on a large scale, particularly in extensive production systems is often impractical, and there is a need to explore alternative traits that are easily measured and could be used as indicators of maternal behaviour.

Blood hormonal profiles offer a promising opportunity as an alternative trait. Past studies have demonstrated the influence of prolactin during the periparturient period is a crucial determinant of maternal behaviour. Of particular interest is that high prolactin during late gestation in mammals can program an offspring’s ability to become a good mother (Sairenji et al., 2017).
Given that maternal behaviour is highly conserved across mammals, it is possible that a similar relationship exists in cattle, which if characterised, offers several opportunities for genetic selection for improved prolactin, or alternatively management-based interventions that ensure high prolactin levels during late gestation. Such strategies would not only improve maternal behaviour, but also mitigate losses associated with calf wastage attributable to poor maternal behaviour.

A key challenge associated with characterising behavioural traits in cattle reared in extensive production systems, is that it is often difficult to phenotype cattle for maternal behaviour. But with recent investments in automated sensing devices, social behaviour can be accurately and objectively measured.
Original languageEnglish
Title of host publication2021 Graham Centre Livestock Forum proceedings
Place of PublicationWagga Wagga
Pages23-24
Number of pages2
Edition2021
Publication statusPublished - 30 Jul 2021
EventGraham Centre Livestock Forum - Convention Centre, CSU, Wagga Wagga, Australia
Duration: 26 Jul 201926 Jul 2019
https://www.csu.edu.au/research/grahamcentre/events/livestock-forum
https://cdn.csu.edu.au/__data/assets/pdf_file/0009/3234195/2019-Livestock-Forum-Proceedings.PDF (proceedings)

Conference

ConferenceGraham Centre Livestock Forum
Country/TerritoryAustralia
CityWagga Wagga
Period26/07/1926/07/19
Internet address

Grant Number

  • MLA Funded

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