Abstract
Sensor-based management is growing rapidly in dairy farming. Activity, behavior and rumination monitors and data from automated milking systems and calf feeders are established management tools and hold promise for earlier or more efficient detection of health problems. However, gaps remain in validation and especially in turning streams of data into actionable information. On average, dairy herds can achieve comparable reproductive performance with management emphasizing estrus detection by activity monitors or timed insemination programs, but herd-specific variables will affect relative performance. Sensor-based screening of fresh cows may be useful to save labor or reduce disruptions to cows’ routines, but more validation is needed before this can augment or offset skilled, rational detection of health problems.
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