13 Precision Livestock Farming Tools for Climate-Smart Feedyard Operations

• Published in: Journal of animal science 2023-11, Vol.101 (Supplement_3), p.326-327
• Main Authors: Tedeschi, Luis O, Mendes, Egleu D M
• Format: Article
• Language: English
• Subjects: Agricultural technology; Air quality; Air temperature; Animal behavior; Animal diseases; Animal products; Animal welfare; Animals; Antibiotics; Artificial intelligence; Contamination; Decisions; Deep learning; Economics; Efficiency; Emissions; Emissions control; Environmental impact; Environmental monitoring; Farm buildings; Farming; Feed additives; Feed efficiency; Feeding; Feeds; Greenhouse gases; Livestock; Livestock farming; Livestock feeds; Livestock industry; Machine learning; Management systems; Manures; Mathematical analysis; Monitoring systems; Nutrients; Odors; Optimization; Pharmaceuticals; Precision farming; Product safety; Recovery time; Sensors; Signs and symptoms; Soil contamination; Soil pollution; Waste management; Water pollution; Well being
• ISSN: 0021-8812; 1525-3163
• DOI: 10.1093/jas/skad281.390

Abstract Precision Livestock Farming (PLF) is a technology-driven approach comprising sensors, cameras, global positioning system tracking, and data analytics to collect real-time data on animal behavior, health, welfare, and performance that enables feedyard operations to make informed decisions and take proactive measures to ensure optimized management and the well-being of their livestock and production efficiency. PLF systems leverage advanced analytical tools and techniques, such as artificial intelligence (AI), including machine learning and deep learning, by integrating data provided by various sensors and software with related datasets and standard AI models to obtain unique data-driven decisions on a range of management practices. The most imminent benefits of PLF include reduced environmental impact and increased profitability. Current PLF tools for climate-smart feedyard operations include 1) feed management systems that use data from feed intake and animal behavior to optimize feed efficiency and minimize waste, which has the potential to decrease the amount of greenhouse gas (GHG) emissions linked to livestock feeding and feed production; 2) environmental monitoring systems to collect local temperature, humidity, and air quality to optimize the pen environment, which can reduce stress on animals, reduce diseases, such as the incidence of respiratory and foot infections, and improve their overall health; 3) feeding systems to use data from individual animals to provide individualized feed and nutrient programs, thus, helping to improve and select for feed efficiency and reduce the amount of feed wasted, assisting with mitigating GHG emissions associated with livestock feeding and feed production; 4) individual animal monitoring systems to access behavior, health and well-being of individual animals that, through early disease symptoms detection, can prevent and reduce recovery time, and reduce the amount of medication applied to animals, reducing GHG gas emissions associated with pharmaceutical products; and 5) waste management systems to help reduce GHG emissions associated with manure production by optimizing manure management and reducing the amount of waste, which can also help reduce unpleasant odors and improve the overall environment conditions in and around feedyards. Waste management systems could also measure the soil and water contamination with fugitive nutrients, feed additives, implants, antibiotics, and other pharmaceuticals admi