УДК 637.112
Authors:
Skvortsov E. A.,
Skvortsova E. G.
Summary Improving the reproductive performance of cows is a key objective for dairy farms and effective heat detection is critical to facilitate this. However, due to the intensive livestock management model, efficiency and detection rates remain relatively low. The most commonly used method for heat detection in dairy cows is visual observation. Its detection rate is below 50%, resulting in unclear economic benefits from its use. Dairy farming uses hormone-based estrus timing protocols that can induce ovulation and set the timing of artificial insemination without the need for estrus detection. However, they require multiple injections, professional training, additional consumables. In this regard, many automated devices have been developed to identify cows in heat. These include automated technologies that measure changes in locomotor activity, cow body temperature, and vocalization relative to estrus. The advantages of using automated technologies are that they do not require significant labor costs, provide real-time analysis and measure a wide range of parameters (behavioral and physiological), thereby increasing the accuracy of heat detection. The accuracy of automatic heat detection varies in the scientific literature from 50% to 90% depending on various factors. The large differences in the accuracy of automated estrus detection, in addition to the lack of information on cost-effectiveness, have meant that the overall adoption of these technologies in the dairy industry is low compared to traditional methods.
Keywords: cattle breeding, automated sensory systems, reproduction management, information technology, precision animal husbandry
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