Body temperature monitoring in equines raised in inner areas using GPS tracking

Accurate monitoring of both physiological and environmental parameters is essential to understand animal adaptation potential and behavior. Global Positioning System (GPS) and Geographic Information System (GIS) collars were used to monitor location and external body temperature (sensor at neck level) of grazing equines raised for 27 days in winter in semi-extensive conditions in inner areas of Italian Apennines. The study was conducted at once in two pastures areas: area 1 in Capracotta (41°50′N 14°16′E, 1150-1500 m altitude), and area 2 in Capestrano (42°16’N 13°46’E, 350-400 m altitude). A total of 12 female equines, n= 10 pregnant mares in area 1 and n= 2 lactating jennies in area 2, were fitted with GPS collars (Digitanimal®, Spain). During the study period, precipitations and air temperatures were recorded. Jennies had an average (2416 observations) external body temperature of 26.8 (± 0.11 SEM) °C, ranging from 14.6 to 37.2 °C. Mares had an average (7881 observations) external body temperature of 24.9 (± 0.16) °C, ranging from 14.7 to 35.5 °C. In area 1, total precipitation included 21.9 cm of snow and 4 mm of rain, with 2.3 (± 0.39) °C average mean temperature, min-max from -3.3 to 8.5 °C. In area 2, total rainfall was 33.7 mm, with an average mean temperature of 6.5 (± 0.38) °C, with min and max from -4.3 to 17.7 °C. As expected, observed external body temperature was generally lower than the average internal body temperature reported in literature. During the study, variations in body temperature did not match variations of air temperatures and precipitations. These results suggest a further potential application of GPS-based monitoring systems to be included in the extensive equine production of inner areas. More studies are needed to boost data collection methodologies and enhance the accuracy of body temperature monitoring systems for equine applications. The survey was approved by the Bioethics Committee of the University of Molise. The research is supported by project PRIN 20224L4WSR, funded by Next Generation EU (CUP: H53D23005120).