The vast computational power of machine learning will allow farmers to be better alerted, resulting in earlier interventions and treatments that benefit animal health and welfare, providing a significant economic boost to the industry. bring. This is from Chloe Hazell, a biological scientist and principal researcher at Agxio, who explores the potential of data and AI in the beef and dairy industry.
Consumer demand for meat continues to grow around the world as the world’s population grows and the need for protein increases. The global beef and dairy industry will be valued at £394.21 billion and £388.22 billion in 2020, with respective markets at £564.8 billion by 2030 and £464.61 billion by 2027 predicted to reach.
This growing demand means increased pressure on farmers, especially in a tough economic environment. Farmers should therefore look to innovative techniques to reduce labor needs and costs while ensuring animal welfare is not compromised.
Precision technology paves the way
Efforts to automate simple but laborious tasks in livestock farming to reduce labor demand are becoming commonplace. Electronic ear tags are becoming increasingly popular to allow automatic reading and weighing of animals, reducing the need for human intervention.
This simple yet effective technology is complemented by on- and extra-animal sensors that assist farmers in many aspects of livestock management. These sensors collect valuable data that informs farmers of both the environment and health of the animals without the need for regular manual checks.
In addition to reducing labor costs, investment in monitoring technology not only improves observation of animal health-related behaviors and markers, but also provides economic benefits for farmers.
What technology already exists?
Recent advances have increased the use of the following in-animal and ex-animal sensors to enhance the economy, welfare and overall farm management of beef and dairy farmers around the world.
activity pattern recognition
The industry is increasingly recognizing the value of artificial intelligence in analyzing activity patterns inside cows. Data are collected on animal location, behavior and activity levels, locomotion quality, and feed intake, giving farmers greater insight into animal health.
Through artificial intelligence and modeling, farmers are alerted to behaviors that may indicate disease, such as changes in cow gait that may indicate lameness. The farmer can then locate the animal, implement the necessary interventions to solve the problem, improve the welfare of the animal, and consequently improve yields from that animal.
temperature recognition
Heat stress is a common problem for cows during the hot summer months. When the Temperature Humidity Index (THI) exceeds 72, cows begin to suffer, exhibiting increased respiratory rate, gasping, and progressive lethargic behavior. This interferes with animal health and welfare, reduces production efficiency, and has negative economic impacts.
Work has begun to implement integrated sensors and machine learning to collect real-time temperature data for livestock. This data can be used to model and predict when cows are likely to experience heat stress, and can also identify events that may be related to the problem.
When temperatures reach temperatures that indicate the occurrence of heat stress, farmers receive alerts and can take necessary interventions to remediate the problem. You can even take this a step further and allow farmers to automatically turn on fans or open vents when certain thresholds determined by AI are met.
reproduction and childbirth
Machine learning can also be applied to model and predict the onset of calving in cows, reducing the risk of stillbirth. Sensors mounted toward the base of the tail can be used to detect subtle behavioral changes such as tail lift that appear approximately 6 hours before parturition.
Therefore, the use of AI-embedded sensor technology can help detect births early and alert farmers so they can take immediate action if problems arise during birth. This helps reduce the frequency of stillbirths and improve cow welfare and production efficiency.
What is the future of AI?
By leveraging sensor technology, cameras, and other modes of data collection, the industry is beginning to collect massive amounts of data. This data is invaluable and, if analyzed correctly, can provide important insights that can help further improve current livestock systems, including calving.
These insights help optimize areas such as disease control, feeding regimes and environmental conditions. With the right application, farmers can support their animals by providing optimal conditions for growth and welfare, and benefit overall production efficiency.
Agxio’s Apollo engine can ingest data in multiple formats, such as strings and images, which are then processed and analyzed to provide informative data analysis to help improve farm management and reach optimal conditions. To do.
Recent research has demonstrated the range of Agxio’s machine learning platform, from image analysis to predict disease to sensor intelligence to aid in environmental control and optimization. Overall, the data collected on farms offer exciting prospects for the global beef and dairy industry, both in terms of animal health and welfare, and farm productivity.
