OMAHA (DTN) -- While most in livestock production see AI and think artificial insemination, another AI might be changing how producers manage livestock. Researchers at the University of Illinois are beginning to study how artificial intelligence (AI) could make grazing more efficient.

By utilizing this technology, livestock producers could improve many aspects of grazing, including improved animal health, animal welfare, environmental sustainability and keeping grazing systems profitable.

PRECISION LIVESTOCK MANAGEMENT

In a webinar last week, Isabella Condotta, an assistant professor of animal science at the University of Illinois, discussed some of the research her team is doing in the realm of AI in livestock production (https://www.youtube.com/…). An increasing world population is pushing researchers to attempt to increase productivity as global animal product consumption increases.

The first step of precision management is monitoring, and this requires the use of many different sensors.

Both wearable and unwearable sensors allow researchers to see animal responses to their environment and these reactions create algorithms. Wearable sensors include collars, ear tags, nosebands, tail rings and leg straps. Unwearable sensors would be cameras and microphones.

"You can't manage what you can't measure," Condotta said.

Information about animal behavior as well as health and wellbeing of livestock can be valuable to producers. The data from the sensors need to be analyzed and this is where AI can help, she said.

AI HELPS GRAZING MANAGEMENT

Condotta said an example of their research is the precision grazing and feed intake predictions study they are currently working on. They have just begun to collect data in recent weeks. Animals are wearing sensors while cameras, microphones and even robots are being utilized to watch the livestock while they graze on forage.

The wearable sensors on the cattle will help researchers track their weight and body condition score (BCS), she said. They are looking at different animal behaviors while grazing, such as grazing with their heads up or down, how many bites and how much chewing they do.

In addition, a small robot will measure forage characteristics (mainly height) in the field.

These sensors will measure forage disappearance and rumen contents. AI will help determine quantity and quality of forages per animal and animal health and condition. This data could allow producers to utilize this technology to graze more efficiently, Condotta said.

"The goal is to enable computers to learn on their own," she said. "Algorithms that improve tasks through experience, and they have the ability to learn without continuous programming."

OTHER AI ADVANCEMENTS

Condotta discussed other aspects of AI technology that could provide useful knowledge to livestock producers. Images from cameras are especially useful, she said.

Among the projects they are working on is collecting images of cow faces to create a database. This along with cameras mounted above a working chute can aid AI in body weight and BCS, Condotta said.

Fixed cameras watching cattle walking and their behavior can provide valuable data. Cameras mounted near water observe health and walking patterns and AI can watch their gait to see if possible herd health issues are present.

Sounds like something from science fiction, cameras are even being fixed on robots and these "robot dogs" collect data as they walk amongst the livestock while grazing. This information could aid management decisions from AI in the future, Condotta said.

Condotta said how researchers handle this data collected will be an important step. In her presentation she used the quota "the biggest error technology innovators make is to be seduced by a technology's potential rather than being led by a customer's actual needs".

Customers could be livestock producers as well as other researchers in search of this type of data. Regardless of the customers, researchers need to find custom solutions, she said.

"We need to understand what is important with all of this data we collect," Condotta said.

Russ Quinn can be reached at Russ.Quinn@dtn.com

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