Monitoring Animal Behavior Using Remote Sensing and GIS Technologies

In behavioral studies, cattle within the same pasture are not considered as independent experimental units because of the potential confounding effects of the herd’s social interactions. However, evaluating cattle behavior on extensive rangelands is logistically challenging for researchers, and treating individual animals as independent experimental units may be beneficial for answering specific research questions. The objective of this study was to evaluate the association patterns among global positioning system (GPS)-tracked cattle at six different study sites in the western United States. A Half-Weight Index (HWI) association value was calculated for each pair of GPS-tracked cows (i.e., dyad) to determine the proportion of time that cattle were within 75 m and 500 m of each other. Cattle at two study sites exhibited relatively low mean HWI-association values (i.e., less than 0.23 HWI); whereas, cattle at other study sites tended to have greater mean HWI associations (i.e., greater than 0.35 HWI). Distinguishing features between study sites with low and high association values were the management of cattle prior to the study, herd size, pasture size, and the number of watering points. However, at all ranches except one, at least 75% of all dyadic associations had HWI values of less than 0.5 at 500 m, indicating that most of the GPS-tracked cows were greater than 500 m from each other for over 50% of tracking period. While interactions among cattle in the same pasture are often inevitable, our data suggests that under some situations, movement patterns of a sub-set of individual GPS-tracked cows may have levels of independence that are sufficient for analysis as individual experimental units. Understanding the level of independence among GPS-tracked cattle may provide options for analysis of grazing behavior for individual cattle within the same pasture. Full article

Combining technologies for monitoring spatial behaviour of livestock with technologies that monitor pasture availability, offers the opportunity to improve the management and welfare of extensively produced beef cattle. The aims of the study were to investigate changes to beef cattle behaviour as pasture availability changed, and to determine whether Global Navigation Satellite System (GNSS) technology could determine livestock grazing preference and hence improve pasture management and paddock utilisation. Data derived from GNSS collars included distance travelled and location in the paddock. The latter enabled investigation of individual animal interactions with the underlying Normalised Difference Vegetation Index (NDVI) and pasture biomass of the paddock. As expected, there was a significant temporal decrease in NDVI during the study and an increase in distance travelled by cattle (P < 0.001; r² = 0.88). The proportion of time budget occupied in grazing behaviour also increased (P < 0.001; r² = 0.71). Cattle showed a partial preference for areas of higher pasture biomass/NDVI, although there was a large amount of variation over the course of the study. In conclusion, cattle behaviour changed in response to declining NDVI, highlighting how technologies that monitor these two variables may be used in the future as management tools to assist producers better manage cattle, to manipulate grazing intensity and paddock utilisation. Full article

The automation of farm tasks in dairy production has been on the rise, with an increasing focus on technologies that measure aspects of animal welfare; however, such technologies are not often validated for use in tie-stall farms. The objectives of the current study were to (1) determine the ability of the IceTag 3D pedometer to accurately measure step data for cows in tie-stalls, and (2) determine whether the leg on which the pedometer is mounted impacts step data. Twenty randomly selected Holstein dairy cows were equipped with pedometers on each rear leg and recorded for 6 h over three 2-h periods. Two observers were trained to measure step activity and the total number of steps per minute were measured. Hourly averages for right and left leg data were analyzed separately using a multivariate mixed model to determine the correlation between pedometer and video step data as well as the correlation between left and right leg step data. The analysis of the video versus pedometer data yielded a high overall correlation for both the left (r = 0.93) and right (r = 0.95) legs. Additionally, there was good correlation between the left and right leg step data (r = 0.80). These results indicate that the IceTag 3D pedometers were accurate for calculating step activity in tie-stall housed dairy cows and can be mounted on either leg of a cow. This study confirms that these pedometers could be a useful automated tool in both a research and commercial setting to better address welfare issues in dairy cows housed in tie-stalls. Full article