INCREASING THE COMPETITIVENESS OF LIVESTOCK PRODUCTS IN THE DIGITAL ECONOMY
DOI:
https://doi.org/10.32689/2523-4536/68-3Keywords:
competitiveness, animal husbandry, livestock enterprises, digital technologies, Precision Livestock FarmingAbstract
The output per unit animal is decreasing due to reasons such as traditional practices, climate change, mixing of socio-economic and environmental phenomena in farming conditions. Animal welfare also has a significant impact on productivity and animals must be constantly monitored and controlled to monitor their welfare status. Welfare assessment has traditionally been carried out in the past by direct observation by humans and providing information only at selected points in time. There has been an increase in the demand for animal protein due to factors such as population growth and rising incomes worldwide. Intelligent sensing tools and various sensors, which are one of the effective methods to meet the animal protein needs, information and communication technologies with large amounts of data obtained from platforms, and sensitive livestock applications will have the potential to significantly increase the capabilities of individual animal analysis and improve farm efficiency by providing advanced on-farm management. Animal welfare also has a significant impact on productivity, and animals must be constantly monitored and controlled to track their welfare status. Welfare assessments have traditionally been carried out in the past by direct observation by humans and providing information only at selected points in time. As Precision Livestock technologies can provide more valid, reliable and applicable data in real time on an individual scale, they serve as early welfare monitoring systems for animals, which has led to increased interest in this assessment method recently. The purpose of the article is to investigate the existing modern information tools to improve the competitiveness of livestock enterprises and biological assets management. Large-scale livestock farming must have automated and cost-effective animal identification systems for farmers as a prerequisite for linking animal data with precision livestock systems. Currently, radio frequency identification, optical character recognition and facial recognition systems are widely used in the pig and other animal industry or among the individual identification methods used in research.
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