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. 2020 Aug 24;4(3):txaa155.
doi: 10.1093/tas/txaa155. eCollection 2020 Jul.

Towards sensor-based calving detection in the rangelands: a systematic review of credible behavioral and physiological indicators

Affiliations

Towards sensor-based calving detection in the rangelands: a systematic review of credible behavioral and physiological indicators

Anita Z Chang et al. Transl Anim Sci. .

Abstract

Calving is a critical point in both a cow and calf's life, when both become more susceptible to disease and risk of death. Ideally, this period is carefully monitored. In extensive grazing systems, however, it is often not economically or physically possible for producers to continuously monitor animals, and thus, calving frequently goes undetected. The development of sensor systems, particularly in these environments, could provide significant benefits to the industry by increasing the quantity and quality of individual animal monitoring. In the time surrounding calving, cows undergo a series of behavioral and physiological changes, which can potentially be detected using sensing technologies. Before developing a sensor-based approach, it is worthwhile considering these behavioral and physiological changes, such that the appropriate technologies can be designed and developed. A systematic literature review was conducted to identify changes in the dam's behavioral and physiological states in response to a calving event. Articles (n = 104) consisting of 111 independent experiments were assessed following an intensive search of electronic databases. Commonly reported indicators of parturition (n = 38) were identified, and temporal trend graphs were generated for 13 of these changes. The results compare trends in behavioral and physiological changes across a variety of animal-related factors and identifies several reliable indicators of parturition for detection with sensors, namely calf grooming behavior, changes in rumination duration, and lying bouts. This synthesis of literature suggests that variability exists between individuals and thus, combining several calving indicators may result in a more broadly applicable and accurate detection of parturition.

Keywords: behavior; cattle; parturition; precision livestock management.

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Figures

Figure 1.
Figure 1.
Distribution of articles that were accessed in which there were independent experiments conducted with extensive beef cattle, intensive beef cattle, and dairy cattle. The experimental animals were dairy cattle in the vast majority of the retrieved articles.
Figure 2.
Figure 2.
Methodology and technology utilization in all studies. Sensor technologies utilized included devices capable of storing or transmitting data to the observer, although traditional methodologies required manual data collection. Although a wider range of sensor technologies were used in the various experiments, there was an overall preference for use of traditional methodologies.
Figure 3.
Figure 3.
Long- and short-term temporal graphs generated for (a) β-hydroxybutyric acid (BHBA) (long-term), (b) glucose (long-term), (c) insulin (long-term), (d) non-esterified fatty acids (NEFA) (long-term), (e) progesterone (short-term), (f) progesterone (long-term), (g) dry matter intake (short-term), (h) dry matter intake (long-term), (i) drinking duration (short-term), (j) drinking duration (long-term), (k) feeding duration (short-term), (l) feeding duration (long-term), (m) calf licking (short-term), (n) calf licking (long-term), (o) lying bouts (short-term), (p) lying bouts (long-term), (q) lying duration (short-term), (r) lying duration (long-term), (s) rumination duration (short-term), (t) rumination duration (long-term), (u) standing duration (short-term), and (v) standing duration (long-term). Graphs for short-term assessments had time ranges from the day prior to and following parturition, although long-term graphs include a 30 d period from before and after calving. A secondary axis was generated where there was more than one unit of measurement used. Data associated with the secondary axis are depicted with a cross marker, as opposed to the circle marker for data corresponding to the primary axis. Thick grey lines depict the rolling average trendline, and darker grey thick lines correspond to the secondary axis. Crosses used for graphing the short-term calf licking pattern refer to the time taken for the cow to initiate licking after birth. These data were excluded from the trendline analysis. Numbers in the legend coincide with a reference, as listed in Supplementary Table S1.

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