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Wheat Farmers Can’t Afford to Ignore This New Study

Wheat diseases have quietly drained staggering sums from farmers’ pockets in recent years. A sweeping new study shows that between 2018 and 2021, crop diseases robbed wheat growers across 29 U.S. states and Ontario of an estimated 560 million bushels—worth US$2.9 billion in lost revenue. That equates to roughly $18.10 per acre disappearing from farmer bottom lines.

Published in Plant Health Progress, the study is the most comprehensive analysis of wheat-related losses ever conducted. Led by Andrew Friskop of North Dakota State University’s Department of Plant Pathology, the project drew on the expertise of dozens of university specialists and the Crop Protection Network. Together, they produced a detailed snapshot of the hidden economic impact wheat diseases exact on growers.

“Farming and food production are incredibly complex,” said Friskop. “This research helps us understand just one of the many invisible threats to crop productivity.”

The team compiled estimates from annual surveys completed by Extension specialists and plant pathologists embedded in wheat-growing regions. Nearly 30 different diseases were tracked, offering an unprecedented field-level perspective on how disease pressures shape yields year over year.

The losses weren’t evenly spread. Fusarium head blight, stripe rust, and leaf rust emerged as the top yield-killing culprits, with weather and local conditions determining the severity of outbreaks. In 2019 alone, wheat farmers lost 188 million bushels—the worst single year captured in the study.

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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.