In the pig industry, artificial intelligence is the “other AI,” but the term is certainly around every corner, says Clint Schwab, vice president of technology and customer success at AcuFast Genetics, LLC.
“Our ability to unleash the capabilities of artificial intelligence (AI) is predicated on the availability of large amounts of quality data to develop such tools,” Schwab says. “As data management systems grow in sophistication and integrate information from periphery sources, I think we’ll start to see applications emerge in the near future.”
Justin Holl, senior product development director for PIC, says artificial intelligence is already impacting the path and progress of genetic progress today.
“The evolution of precision data capture that has been recently developed leans heavily on various forms of artificial intelligence to help continually refine and enhance the algorithms of measurement,” Holl explains. “In addition, we are actively utilizing various AI methods to continue to help refine the search for specific tools – either more precise traditional selection or targets for utilization with methods like gene editing, that will deliver breakthrough steps toward consistent and predictable genetic solutions to priorities of our industry.”
Many new phenotyping tools, such as sensors, use AI to generate alerts based on data received in real-time, says Jenelle Dunkelberger, global health and behavior platform lead for Topigs Norsvin.
“I anticipate we will expand our use of AI in animal breeding to improve predictions of the impact of a mutation (or set of mutations) on an animal’s phenotype, perhaps even combining non-genetic information with genetic information in making predictions,” she says.
AI Helps Make Industry Leaps
Other applications include developing models to evaluate certain selection decisions over time, or models to optimize selection indices.
The role of AI in interpreting complex phenotypes and relationships between them is exciting, says Tom Rathje, chief technical officer at DNA Genetics LLC. “Camera footage is an example of how AI can be applied to observe an animal and use those observations to classify animals and predict a reduction in culling for structure or locomotion.”
Another example is tying together the relationships between data describing the environment a pig is exposed to, gene expression, metabolome, gut microbiome and DNA sequence, Rathje says.
“We can measure all of these, but making sense of these data will be a task for which AI can be of great help,” Rathje adds.
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