Dallas’ Precision Livestock Technologies Launches AI Solution That Makes Cattle Feed Recommendations

PLT said it developed its AI-based algorithms through machine learning techniques, based on "over 150,000 discrete pen days." According to the company, the newly launched system replicates the decisions of "highly observant, expert cattle feeding professionals."

Precision Livestock Technologies, a Dallas-based provider of software and hardware solutions for livestock feeding and health, said it has introduced the first system that uses artificial intelligence to predict cattle feed intake and make feeding recommendations.

PLT CEO Andrew McKenzie

“Developing this capability has always been a high-priority goal for the company, and it is extremely gratifying to see the system adding value for our customers,” CEO Andrew McKenzie said in a statement.

“Though we only released the system recently, customers have already confirmed that they are receiving valuable guidance,” he added. “We’re confident that the unique, objective data of our Bunk Management System can be harnessed to increase profits and improve animal health.”

The system generates daily quantitative feeding predictions based on hundreds of data points gathered from PLT’s machine vision Bunk Management System and external data sources, taking into account feeding rates, feeding times, feeding cycles, cattle behavior, ration type, weather, and other factors.

Algorithms based on ‘over 150,000 discrete pen days’

Founded in 2019, PLT said it developed its AI-based algorithms through machine learning techniques, based on over 150,000 discrete pen days.

According to PLT, the system replicates the decisions of “highly observant, expert cattle feeding professionals.”

By using the system, clients can both automate feeding decisions and give their employees an expert way to check assumptions and make corrections before costly mistakes are made, the company said. Rather than apply a “one size fits all” approach, the technology is configured to allow PLT to efficiently tune the output to match specific feeding protocols.

“Our team worked through many iterations and pilot rollouts to get the technology to this point, and we are very excited about its potential to overcome the factors that limit productivity in the cattle industry—having good data and the ability to use it to make well-informed, optimized decisions,” McKenzie said. “One powerful aspect of machine learning is that applications can continuously improve as more data is generated. As the company continues to add clients and expand system use to cover more cattle, the technology will continue to improve and generate higher returns for PLT customers.”

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