Heat Stress Detection in Dairy Cattle Using Intraruminal Bolus Sensors.

Heat stress represents one of the most economically and biologically consequential environmental challenges facing modern dairy production, with projected intensification under ongoing climate change. Intraruminal bolus sensors have emerged as a uniquely capable platform for heat stress surveillance in lactating dairy cows: once administered, they provide continuous, lifetime access to reticuloruminal temperature-a reliable indicator of core body thermal status-alongside behavioral parameters, in a configuration entirely shielded from external environmental interference. This review examines the scientific basis and practical capabilities of bolus-based heat stress monitoring and its potential to optimize dairy production systems. We describe the physiological rationale for reticuloruminal temperature as a heat stress indicator, the principal confounding factors including drinking-water effects and diurnal variation, and the evidence base for interpreting temperature signals in the context of breed, parity, milk yield, and the temperature-humidity index. We review controlled studies characterizing the determinants of reticuloruminal temperature across breeds and seasons, and a four-level machine-learning processing architecture for bolus data integration. Individual baseline calibration-rather than fixed population thresholds-is identified as a prerequisite for reliable detection, enabling targeted cooling interventions, improved reproductive management, and enhanced disease surveillance. We further review bolus developments extending sensing to heart-rate monitoring and low-power wide area network communication, and discuss machine-learning methodologies suited to bolus-derived time-series data. Methodological challenges-including drinking-water effects, sensor precision, communication reliability, and the absence of standardized crossbreed validation protocols-are critically appraised, and future research priorities are identified.