US Farmers Face Plague Of Pests As Global Heating Raises Soil Temperatures

Sep 14, 2022

The corn earworm (Helicoverpa zea) is considered to be among the most common farm pests in the US, ravaging crops such as maize, cotton, soya and other vegetables. It spends winter underground and is not known to survive in states beyond a latitude of 40 degrees north (which runs from northern California through the midwest to New Jersey), but that is changing as soils warm and it spreads to new areas, according to research led by North Carolina State University.

The report follows research from the University of Washington in 2018 that found 2C (3.6F) of warming would boost the number and appetite of insects globally, causing them to destroy 50% more wheat and 30% more maize than they do now. Rising heat stress is already affecting yields, with harvests of staple crops in Europe down this year as a result of heatwaves and drought."

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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.