Farmers watch weather, trade war

May 29, 2025

Minnesota farmer Dan Glessing isn’t ready to be too upset about President Donald Trump’s trade wars.

Farm country voted heavily for Trump this past November. Now Glessing and many other farmers are taking a wait-and-see attitude toward the Republican president’s disputes with China and other international markets.

China normally would buy about one row out of every four of the Minnesota soybean crop – and took in almost $13 billion worth of soybeans from the United States as a whole in 2024. More than half of U.S. soybeans are exported internationally, with about half of those going to China – so it’s a critical market.

Trump in April increased U.S. tariffs on products from China to 145%, and China retaliated with 125%. But a later announcement of a 90-day truce between the two countries backed up the reluctance of many farmers to hit the panic button.

More good news came in an updated forecast from the U.S. Department of Agriculture that projected increased corn exports and only slightly reduced corn prices. The report also predicted somewhat-fewer soybean exports but increased domestic consumption, resulting in increased prices. Soybean futures surged.

Click here to see more...

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.