"Why does it matter?" asked a Minnesota farmer and Ceres Imaging Remote Sensing scientist during his presentation at the Texas Plant Protection Association Conference at Bryan.
"I think we're often stuck in the mantra of data for the sake of data," says Kirk Stueve. "Growers don't care about that. Agronomists don't care about that. And so, with my work, the work we do at Ceres, we straddle the divide between science, tech, AI, and practical applications. What we do on the science and the AI side, the remote sensing side of the equation, none of that matters if we can't deliver tangible value to the grower."
As a fourth-generation farmer, both perspectives come naturally for Stueve, who produces soybeans and corn with his father and his aunt and uncle. He also admits he's part tech geek, with a Ph.D. in geography and an emphasis in remote sensing and GIS (Geographic Information System) from Texas A&M University. Along with being published in various academic journals, he teaches at the university level "for fun." He also likes to get his hands dirty, running the combine and the tractor.
"I get excited about straddling the divide between science and academics and practical applications in the field," he said. "When I started at Ceres three years ago, I didn't need a job. I was looking for a company that fit how I think about science, how I think about the farm, and that could introduce technology I use on the farm."
See, Smart machines make instant management decisions
Stueve often tests his ideas on his family. "My litmus test is if I can convince anybody else in the family to try some of this technology (on their farm), then I know we might have something. Because if they'll think about it, that's the hardest sell right there."
Remote sensing & AI
Stueve, who spent six years at Texas A&M learning about remote sensing and developing a background in the field, presented information at the conference about current and future remote sensing technology and its connection to artificial intelligence -- the conference's theme.
"When you look at production agriculture today, remote sensing has been a key part of driving AI and also precision agriculture up until now. Looking to the future, it will be a key part of continuing to drive adoption in the market," he says.
"Remote sensing fills one of the big data roles of allowing more information about our fields, about our production systems to be fed into machines where we can make decisions and applications in the field."
Best application
One of the best uses of remote sensing in an AI framework is variable rates or targeted management of diseases, where a grower can act and save money during the growing season, Stueve says.
"Certain diseases are much more likely where you have dense, thick canopy; those microclimate conditions are more conducive for that disease increasing in severity. And in some cases, where you have a weaker open canopy, the disease will not even occur. So, the growers are wasting money if they're spraying fungicide in those weaker, open locations. In-season imagery within an AI framework delivered up to a sprayer has the capacity to only target areas with fungicide where you'll see a return. And you can skip the areas where you're not going to see that return."
See, AI will improve on-farm decision-making
In the future, as remote sensing develops with AI, Stueve says, "AI is going to allow decisions to be made almost in an instant after imagery is delivered and then the grower will have that information. One of the most promising examples is using next-gen thermal imagery for early pest and disease detection where things that stress, those that we can't see in the field or most modern sensors can't see, these next-gen thermal sensors are picking it up. AI will be an important piece of that story and trying to disentangle where it's an actual disease or pest issue and where it's not and delivering that to the grower."
That technology is about two to three years out, Stueve says, but it's one area he's excited about.
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