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Tackling Risk in Agriculture has Never Been Harder, Ag Expo Hears

The risks for today’s agricultural producers has never been higher — but that doesn’t mean the industry can’t adapt and thrive.

“Today’s farmers must navigate a complex web of interrelated challenges,” says Dr. Camille Ryan, Senior Business Partner in Industry Affairs and Sustainability at Bayer Crop Science Canada. “The industry’s resilience hinges on a comprehensive grasp of these risks and the relationships between them.”

Perhaps not surprising, economic turbulence was at the forefront of Ryan’s discussion.

“We’re looking at a lengthy list of economic risks that are always shifting,” she says, pointing to market fluctuations, changing commodity prices, rising input costs, and shifting trade laws as key factors complicating profitability for farmers. “These challenges make it increasingly difficult to maintain sustainable operations.”

Most notably, the looming threat of tariffs from the U.S. administration creates increased unpredictability and the potential to severely impact farmers’ bottom lines.

“A proposed 25% tariff could drive up costs and create logistical headaches for producers,” she says. “We need to stay informed about these developments and advocate for our interests.”

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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.