Using advanced technologies to quantify beef cattle behavior1

Abstract

For decades, we have relied upon visual observation of animal behavior to define clinical disease, assist in breeding selection, and predict growth performance. Limitations of visual monitoring of cattle behavior include training of personnel, subjectivity, and brevity. In addition, extensive time and labor is required to visually monitor behavior in large numbers of animals, and the prey instinct of cattle to disguise abnormal behaviors in the presence of a human evaluator is problematic. More recently, cattle behavior has been quantified objectively and continuously using advanced technologies to assess animal welfare, indicate lameness or disease, and detect estrus in both production and research settings. The current review will summarize three methodologies for quantification of cattle behavior with focus on U.S. beef production systems; 1) three-axis accelerometers that quantify physical behavior, 2) systems that document feeding and watering behavior via radio frequency, and 3) triangulation or global positioning systems to determine location and movement of cattle within a pen or pasture. Furthermore, advances in Wi-Fi and radio frequency technology have allowed many of these systems to operate remotely and in real-time and efforts are underway to develop commercial applications that may allow early detection of respiratory or other cattle diseases in the production environment. Current challenges with commercial application of technology for early disease detection include establishment of an appropriate algorithm to ensure maximum sensitivity and specificity, reliable and repeatable data collection in harsh environments, cost:benefit, and integration with traditional methodology for clinical diagnosis. Advanced technologies have also allowed cattle researchers to determine temporal variance in behavior or variability between experimental treatments. However, these data sets are typically very large and challenges exist regarding statistical analysis and reporting.

Animal Welfare Implications of Digital Tools for Monitoring and Management of Cattle and Sheep on Pasture

“…PLF is generally defined as a management system that offers continuous, automatic monitoring and control of animal behaviour, health, welfare, production and reproduction, as well as environmental impact of the production, in real time [ 6 , 7 ]. By continuous monitoring of the animals, the farmer can immediately detect changes that may indicate that something is wrong [ 6 , 8 ]. PLF has the potential to completely or partially replace direct inspections on-site once or several times a day.…”

“…Active transponders are connected to a battery and transmit radio waves actively, which gives them a wider range than passive ones (about 100 m, compared to 3 m or less). In a review [ 8 ], technologies to quantify beef cattle behaviours in U.S. beef production systems were presented, including accelerometers, radio frequencies and global positioning systems. In conclusion, each behaviour monitoring system has the potential to enhance research on animal welfare, health, nutrition and reproduction.…”

Locomotion behavior changes in peripartum beef cows and heifers

“…3. These accelerometers allow for tri-axial movement detection, continuous data logging, and data summary into specific increments of time (Richeson et al, 2018). These locomotion devices have been validated for accuracy against video monitoring in late gestation dairy cows by other groups (Mattachini et al, 2013;Borchers et al, 2016).…”

“…Commercially available accelerometer devices such as IceTag and IceQube products (iceRobotics, Ltd., Edinburgh, UK) have been well validated against visual behavioral monitoring in dairy cattle (Nielsen et al, 2010), where use of this technology for early recognition of parturition is being explored (Huzzey et al, 2005;Miedema et al, 2011b;Borchers et al, 2017). Use of accelerometers in beef cattle has been limited to research in the early detection of feedlot morbidity (Pillen et al, 2016;Richeson et al, 2018), but dairy data suggest that these may have utility in detection of calving in beef females as well.…”

Behavior assessment and applications for BRD diagnosis: beef

“…The available systems include (1) three-axis accelerometers that quantify physical behaviors such as steps, standing/lying time, rumination time, or overall activity index, (2) systems that document feeding and watering behavior via RFID detection at the feed bunk and water trough, and (3) triangulation systems that continuously document spatial behavior within a pen, including the ability to locate important features in the pen, such as feed or water source, and to monitor those specific activities. Previous reviews (Theurer et al ., 2013; Wolfger et al ., 2015; Richeson et al ., 2018) outlined the specific functions of each behavior assessment system and highlighted some of the research conducted. The focus of this review was to provide a general discussion on the potential benefits and challenges associated with the implementation of novel behavior assessment systems to assist in BRD detection in the commercial feedlot.…”