Monitoring Behavior and Welfare of Cattle in Response to Summer Weather in an Arizona Rangeland Pasture Using a Commercial Rumen Bolus
Amadeus O. Barto, Derek W. Bailey, Ly Ly Trieu, Pippa Pryor, Kieren D. McCosker, and Santigo Utsumi
In: Animals 2025, 15(10), 1448
Summary:
Monitoring the welfare of cattle on rangelands is logistically challenging, and hot weather can adversely affect animal health and productivity. The aim of this study was to evaluate the use of a commercially available rumen bolus (SmaXtec) to measure the body temperature and behavior of cattle grazing rangelands during the summer in Arizona. The cattle body temperature increased with higher wet bulb globe temperatures, an index used to monitor heat stress in humans. Cattle activity levels were most closely associated with relative humidity, surprisingly increasing at more humid levels. The estimated water intake of cattle decreased at higher humidity levels. The rumen bolus appears to be an effective tool for remotely monitoring cattle activity and body temperature while grazing extensive pastures.
In: Animals 2025, 15(10), 1448
Summary:
Monitoring the welfare of cattle on rangelands is logistically challenging, and hot weather can adversely affect animal health and productivity. The aim of this study was to evaluate the use of a commercially available rumen bolus (SmaXtec) to measure the body temperature and behavior of cattle grazing rangelands during the summer in Arizona. The cattle body temperature increased with higher wet bulb globe temperatures, an index used to monitor heat stress in humans. Cattle activity levels were most closely associated with relative humidity, surprisingly increasing at more humid levels. The estimated water intake of cattle decreased at higher humidity levels. The rumen bolus appears to be an effective tool for remotely monitoring cattle activity and body temperature while grazing extensive pastures.
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Using a Commercial Rumen Bolus to Monitor the Well-being of Cattle Grazing Rangelands During Hot Summer Weather
Amadeus O. Barto, Derek W. Bailey, Marcy A. Ward, Samuel T. Smallidge
In: pubs.nmsu.edu 2025, Cooperative Extension Service, Circular 712
Summary:
Heat stress and other climate concerns such as droughts are forecasted to increase in coming years, negatively impacting livestock grazing rangelands in both subtropic and temperate zones. Cattle must maintain a narrow range of core body temperature for optimal health. Extended exposure to high ambient air temperatures, relative humidity, and solar load can increase the risk of heat stress. The core body temperature of cattle experiencing heat stress will rise, often followed by behavioral changes such as increased water intake, reduced feed intake, and lower activity levels. If heat stress persists, negative effects on production, reproduction, and immune responses may occur.
In: pubs.nmsu.edu 2025, Cooperative Extension Service, Circular 712
Summary:
Heat stress and other climate concerns such as droughts are forecasted to increase in coming years, negatively impacting livestock grazing rangelands in both subtropic and temperate zones. Cattle must maintain a narrow range of core body temperature for optimal health. Extended exposure to high ambient air temperatures, relative humidity, and solar load can increase the risk of heat stress. The core body temperature of cattle experiencing heat stress will rise, often followed by behavioral changes such as increased water intake, reduced feed intake, and lower activity levels. If heat stress persists, negative effects on production, reproduction, and immune responses may occur.
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Development of a Novel Classification Approach for Cow Behavior Analysis Using Tracking Data and Unsupervised Machine Learning Techniques
Jiefei Liu, Derek W. Bailey, Huiping Cao, Tran Cao Son, and Colin T. Tobin
In: Sensors 2024 24(13), 4067
Summary:
Global Positioning Systems (GPSs) can collect tracking data to remotely monitor livestock well-being and pasture use. Supervised machine learning requires behavioral observations of monitored animals to identify changes in behavior, which is labor-intensive. Our goal was to identify animal behaviors automatically without using human observations. We designed a novel framework using unsupervised learning techniques. The framework contains two steps. The first step segments cattle tracking data using state-of-the-art time series segmentation algorithms, and the second step groups segments into clusters and then labels the clusters. To evaluate the applicability of our proposed framework, we utilized GPS tracking data collected from five cows in a 1096 ha rangeland pasture. Cow movement pathways were grouped into six behavior clusters based on velocity (m/min) and distance from water. Again, using velocity, these six clusters were classified into walking, grazing, and resting behaviors. The mean velocity for predicted walking and grazing and resting behavior was 44, 13 and 2 min/min, respectively, which is similar to other research. Predicted diurnal behavior patterns showed two primary grazing bouts during early morning and evening, like in other studies. Our study demonstrates that the proposed two-step framework can use unlabeled GPS tracking data to predict cattle behavior without human observations.
In: Sensors 2024 24(13), 4067
Summary:
Global Positioning Systems (GPSs) can collect tracking data to remotely monitor livestock well-being and pasture use. Supervised machine learning requires behavioral observations of monitored animals to identify changes in behavior, which is labor-intensive. Our goal was to identify animal behaviors automatically without using human observations. We designed a novel framework using unsupervised learning techniques. The framework contains two steps. The first step segments cattle tracking data using state-of-the-art time series segmentation algorithms, and the second step groups segments into clusters and then labels the clusters. To evaluate the applicability of our proposed framework, we utilized GPS tracking data collected from five cows in a 1096 ha rangeland pasture. Cow movement pathways were grouped into six behavior clusters based on velocity (m/min) and distance from water. Again, using velocity, these six clusters were classified into walking, grazing, and resting behaviors. The mean velocity for predicted walking and grazing and resting behavior was 44, 13 and 2 min/min, respectively, which is similar to other research. Predicted diurnal behavior patterns showed two primary grazing bouts during early morning and evening, like in other studies. Our study demonstrates that the proposed two-step framework can use unlabeled GPS tracking data to predict cattle behavior without human observations.
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Potential for applying precision livestock tools to utilization patterns
Kelsey Nelson, MS Thesis 2022
Summary:
Livestock grazing can disproportionately affect areas of the landscape that contain rugged terrain, preferred vegetation, or areas near water. Areas where livestock congregate, commonly referred to as ‘hot spots’, can create problems for land managers and are often detrimental to rangeland health and related ecosystem services. Technological advances are facilitating development of real-time livestock tracking, which could remotely monitor spatial movement patterns of livestock. The objective of this study was to determine if livestock movement patterns can be used to predict forage utilization patterns.
Summary:
Livestock grazing can disproportionately affect areas of the landscape that contain rugged terrain, preferred vegetation, or areas near water. Areas where livestock congregate, commonly referred to as ‘hot spots’, can create problems for land managers and are often detrimental to rangeland health and related ecosystem services. Technological advances are facilitating development of real-time livestock tracking, which could remotely monitor spatial movement patterns of livestock. The objective of this study was to determine if livestock movement patterns can be used to predict forage utilization patterns.
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Tracking and sensor-based detection of livestock water system failure:
A case study simulation
Colin Tobin, Derek W. Bailey and Mark G. Trotter
In: Rangeland Ecology and Management 2021 77, 9-16
Summary
Water is an important nutrient, and its continuous provision is a critical welfare issue for cattle grazing arid and semiarid rangelands. Time and labor are needed to monitor water availability, and automated monitoring systems are a costly input on expansive rangeland pastures. The objective of this study was to evaluate the potential of detecting water system failures using Global Positioning System (GPS) tracking and accelerometers, assuming the data could be monitored in real or near-real time. Water system failure was simulated in a 1 096-ha pasture in Arizona by placing metal panels around the only drinker for 4 h (0800−1200) on three occasions in 2018 and two occasions in 2019. Randomly selected cows (10 in 2018 and 23 in 2019) of the 120 cows in the pasture were tracked with GPS collars, and 7 (2018) and 10 (2019) of the tracked cows were fitted with triaxial accelerometers. Movement intensity measured by accelerometers was greater (P = 0.03) on the day of simulated water failure than on control days with available water. During simulated water failure, cows remained closer to water (P = 0.01) after approaching the drinker (< 150 m) compared with the control period the day prior. Cows typically went to the drinker, drank, and then traveled away from the drinker and rested. On simulated water-failure days, cows remained near the drinker (< 150 m from the tank) until the panels were removed and they could drink. Real-time GPS tracking with or without accelerometer data has the potential to remotely detect water system failure, which could reduce the time for managers to repair the water system and improve cattle well-being.
In: Rangeland Ecology and Management 2021 77, 9-16
Summary
Water is an important nutrient, and its continuous provision is a critical welfare issue for cattle grazing arid and semiarid rangelands. Time and labor are needed to monitor water availability, and automated monitoring systems are a costly input on expansive rangeland pastures. The objective of this study was to evaluate the potential of detecting water system failures using Global Positioning System (GPS) tracking and accelerometers, assuming the data could be monitored in real or near-real time. Water system failure was simulated in a 1 096-ha pasture in Arizona by placing metal panels around the only drinker for 4 h (0800−1200) on three occasions in 2018 and two occasions in 2019. Randomly selected cows (10 in 2018 and 23 in 2019) of the 120 cows in the pasture were tracked with GPS collars, and 7 (2018) and 10 (2019) of the tracked cows were fitted with triaxial accelerometers. Movement intensity measured by accelerometers was greater (P = 0.03) on the day of simulated water failure than on control days with available water. During simulated water failure, cows remained closer to water (P = 0.01) after approaching the drinker (< 150 m) compared with the control period the day prior. Cows typically went to the drinker, drank, and then traveled away from the drinker and rested. On simulated water-failure days, cows remained near the drinker (< 150 m from the tank) until the panels were removed and they could drink. Real-time GPS tracking with or without accelerometer data has the potential to remotely detect water system failure, which could reduce the time for managers to repair the water system and improve cattle well-being.
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Temporal changes in association patterns of cattle grazing at two stocking densities in a central Arizona rangeland
Colin T. Tobin, Derek W. Bailey, Mitchell B. Stephenson and Mark G. Trotter
In: Animals 2021, 11(9), 2635
Summary
Monitoring changes in the utilization of forages across rangelands can be time consuming and difficult with untrained personnel. The use of real time positioning for cattle is becoming commercially available with the improvements in technology. The objective of this case study was to identify the changes in livestock social associations and spatial location at two stocking densities throughout a six-week grazing period. Both pastures used similar sized herds with 35 and 29 animals tracked with global positioning systems set at 30-min intervals. A half-weight index value was calculated for each pair of tracked cattle to determine the proportion of time that cattle were within 75 m and 500 m of each other. Throughout the study, forage utilization increased from 5 to 24% and from 10% to 20% and forage mass decreased from 2601 kg ha−1 to 1828 kg ha−1 and 2343 kg ha−1 to 1904 kg ha−1, in the high stocking density pasture and low stocking density pasture, respectively. Utilization of forages throughout the trial forced cattle to disperse and travel further from water sources to find new feeds. Real-time GPS tracking has the potential to remotely detect changes in animal spatial association, identify when cows disperse, and improve recognition for the need of pasture rotation to avoid rangeland degradation
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In: Animals 2021, 11(9), 2635
Summary
Monitoring changes in the utilization of forages across rangelands can be time consuming and difficult with untrained personnel. The use of real time positioning for cattle is becoming commercially available with the improvements in technology. The objective of this case study was to identify the changes in livestock social associations and spatial location at two stocking densities throughout a six-week grazing period. Both pastures used similar sized herds with 35 and 29 animals tracked with global positioning systems set at 30-min intervals. A half-weight index value was calculated for each pair of tracked cattle to determine the proportion of time that cattle were within 75 m and 500 m of each other. Throughout the study, forage utilization increased from 5 to 24% and from 10% to 20% and forage mass decreased from 2601 kg ha−1 to 1828 kg ha−1 and 2343 kg ha−1 to 1904 kg ha−1, in the high stocking density pasture and low stocking density pasture, respectively. Utilization of forages throughout the trial forced cattle to disperse and travel further from water sources to find new feeds. Real-time GPS tracking has the potential to remotely detect changes in animal spatial association, identify when cows disperse, and improve recognition for the need of pasture rotation to avoid rangeland degradation
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Opportunities to apply precision livestock management on rangelands
Derek W. Bailey, Mark G. Trotter, Colin Tobin and Milt G. Thomas
In: Frontiers in Sustainable Food Systems 2021 5(93), 611915
Summary
Precision livestock management has become a new field of study as the result of recent advancements in real-time global positioning system (GPS) tracking, accelerometer and other sensor technologies. Real-time tracking and accelerometer monitoring has the potential to remotely detect livestock disease, animal well-being and grazing distribution issues and notify ranchers and graziers so that they can respond as soon as possible. On-going research has shown that accelerometers can remotely monitor livestock behavior and detect activity changes that are associated with disease and parturition. GPS tracking can also detect parturition by monitoring the distance between a ewe and the remainder of the flock. Tracking also has the potential to detect water system failures. Combinations of GPS tracking and accelerometer monitoring may be more accurate than either device used by itself. Real-time GPS tracking can identify when livestock congregate in environmental sensitive areas which may allow managers the chance to respond before resource degradation occurs. Identification of genetic markers associated with terrain use, decreased cost of GPS tracking and novel tracking data processing should facilitate development of tools needed for genetic selection for cattle grazing distribution. Precision livestock management has potential to improve welfare of livestock grazing rangelands and forested lands, reduce labor costs and improve ranch profitability and improve the condition and sustainability of riparian areas and other environmental sensitive areas on grazing lands around the world.
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In: Frontiers in Sustainable Food Systems 2021 5(93), 611915
Summary
Precision livestock management has become a new field of study as the result of recent advancements in real-time global positioning system (GPS) tracking, accelerometer and other sensor technologies. Real-time tracking and accelerometer monitoring has the potential to remotely detect livestock disease, animal well-being and grazing distribution issues and notify ranchers and graziers so that they can respond as soon as possible. On-going research has shown that accelerometers can remotely monitor livestock behavior and detect activity changes that are associated with disease and parturition. GPS tracking can also detect parturition by monitoring the distance between a ewe and the remainder of the flock. Tracking also has the potential to detect water system failures. Combinations of GPS tracking and accelerometer monitoring may be more accurate than either device used by itself. Real-time GPS tracking can identify when livestock congregate in environmental sensitive areas which may allow managers the chance to respond before resource degradation occurs. Identification of genetic markers associated with terrain use, decreased cost of GPS tracking and novel tracking data processing should facilitate development of tools needed for genetic selection for cattle grazing distribution. Precision livestock management has potential to improve welfare of livestock grazing rangelands and forested lands, reduce labor costs and improve ranch profitability and improve the condition and sustainability of riparian areas and other environmental sensitive areas on grazing lands around the world.
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Potential for Precision Livestock Management Applications on Cattle Ranches
Colin Tobin, PhD Dissertation 2020
Summary:
The objectives of the research within this dissertation were to evaluate the potential applications of Precision Livestock Management (PLM) using store-on-board accelerometer and global positioning system (GPS) tracking to observe changes in animal welfare due to 1) the onset of disease 2) failure of water infrastructure and 3) reduction in available forages and how the tracking and sensors could be used in real-time systems as alerts to managers and caretakers. Accelerometers are effective tools in determining behavior changes due to the onset of Bovine Ephemeral Fever (BEF). A reduction in movement intensity, likely due to symptoms such as listlessness, lameness and soreness, was determined nearly 15 hours prior to observation by the caretaker using accelerometers attached to neck collars. Movement intensity of diagnosed heifers was lower (P ≤ 0.01) during the 24-hours before the symptoms were observed compared control heifers and levels observed 2 days before diagnosis. Differences in movement intensity were detected from normal behavior of infected cattle and other cattle within the paddock. Accelerometers also determined increased movement intensity during simulated water failures while attached to ear tags while GPS determined changes from normal animal behavior. During simulated water failure, cows remained closer to water (P = 0.01) after approaching the drinker (< 150 m) compared to the control period the day prior. Cows typically went to the drinker, drank and then traveled away from the drinker and rested. On simulated water failure days, cows remained near the drinker (< 150 m from the tank) until the panels were removed and they could drink. GPS-tracked cattle subgroups separated in likely search for forages during the later portions of a 6-week study in two differing stocking density scenarios (0.417 AU ha -1 and 0.123 AU ha -1). Mean forage utilization in the higher stocking density pasture was 24%, while only x 20% in the lower stocking density pasture. Although standing biomass during the 6 weeks both pastures declined and cows dispersed, cows moved independently using a metric from the literature. During the entire study all pairs of traced cows (dyads) were greater than 500 m from each other for over 50% of the time that cattle were tracked (excluding times when cows were within 200 m from water).
Summary:
The objectives of the research within this dissertation were to evaluate the potential applications of Precision Livestock Management (PLM) using store-on-board accelerometer and global positioning system (GPS) tracking to observe changes in animal welfare due to 1) the onset of disease 2) failure of water infrastructure and 3) reduction in available forages and how the tracking and sensors could be used in real-time systems as alerts to managers and caretakers. Accelerometers are effective tools in determining behavior changes due to the onset of Bovine Ephemeral Fever (BEF). A reduction in movement intensity, likely due to symptoms such as listlessness, lameness and soreness, was determined nearly 15 hours prior to observation by the caretaker using accelerometers attached to neck collars. Movement intensity of diagnosed heifers was lower (P ≤ 0.01) during the 24-hours before the symptoms were observed compared control heifers and levels observed 2 days before diagnosis. Differences in movement intensity were detected from normal behavior of infected cattle and other cattle within the paddock. Accelerometers also determined increased movement intensity during simulated water failures while attached to ear tags while GPS determined changes from normal animal behavior. During simulated water failure, cows remained closer to water (P = 0.01) after approaching the drinker (< 150 m) compared to the control period the day prior. Cows typically went to the drinker, drank and then traveled away from the drinker and rested. On simulated water failure days, cows remained near the drinker (< 150 m from the tank) until the panels were removed and they could drink. GPS-tracked cattle subgroups separated in likely search for forages during the later portions of a 6-week study in two differing stocking density scenarios (0.417 AU ha -1 and 0.123 AU ha -1). Mean forage utilization in the higher stocking density pasture was 24%, while only x 20% in the lower stocking density pasture. Although standing biomass during the 6 weeks both pastures declined and cows dispersed, cows moved independently using a metric from the literature. During the entire study all pairs of traced cows (dyads) were greater than 500 m from each other for over 50% of the time that cattle were tracked (excluding times when cows were within 200 m from water).
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