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Illinois Farmers Brace for Potential Impact of Tariffs on Crop Prices

By Jess Savage

Mark Tuttle farms in Somonauk, Illinois. He raises corn, soybeans and wheat on about 1,000 acres.

He finished planting early this year, thanks to good weather. But he doesn’t get to rest for long, because he’s got other things to worry about.

"So right now, farmers are busy on one thing, they’re trying to get this crop established," Tuttle said. "I wanna take care of my crops that I have now. In the back of my mind, I'm thinking about, okay, what am I [going to] sell that for?”

Tuttle is one of about 70,000 farmers in Illinois. Just like so many others, he’ll be checking on how Trump’s tariffs will affect commodity prices come harvest time in the summer and fall.

"The tariffs, you know, they come to light every day. but we're kind of getting used to it," he said. "We've talked about these tariffs for almost 90 days, and now it's like, well, what's going to happen next? So you kind of wait and see, instead of getting all flared up about it.”

Tariffs are taxes paid on foreign products. The importer, or the country that receives the product, pays the cost. It’s meant to make foreign goods more expensive and ultimately boost domestic products and markets.

But in agriculture, it means more expensive inputs like fertilizer, which is typically imported. A lot of Illinois ag products, including soybeans, will be harder to sell abroad. China is the biggest buyer of U.S. soybeans. It has since imposed retaliatory tariffs on the U.S.

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Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Video: Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Plant breeding has long been shaped by snapshots. A walk through a plot. A single set of notes. A yield check at the end of the season. But crops do not grow in moments. They change every day.

In this conversation, Gary Nijak of AerialPLOT explains how continuous crop modeling is changing the way breeders see, measure, and select plants by capturing growth, stress, and recovery across the entire season, not just at isolated points in time.

Nijak breaks down why point-in-time observations can miss critical performance signals, how repeated, season-long data collection removes the human bottleneck in breeding, and what becomes possible when every plot is treated as a living data set. He also explores how continuous modeling allows breeding programs to move beyond vague descriptors and toward measurable, repeatable insights that connect directly to on-farm outcomes.

This conversation explores:

• What continuous crop modeling is and how it works

• Why traditional field observations fall short over a full growing season

• How scale and repeated measurement change breeding decisions

• What “digital twins” of plots mean for selection and performance

• Why data, not hardware, is driving the next shift in breeding innovation As data-driven breeding moves from research into real-world programs, this discussion offers a clear look at how seeing the whole season is reshaping value for breeders, seed companies, and farmers, and why this may be only the beginning.