The secret messages of plants

Jan 04, 2023

Crop traits are being developed that will enable plants to signal when they’re exposed to specific stressors in a way that can be instantly detected by satellite or equipment-based cameras.

Shely Aronov, chief executive officer of InnerPlant, she said this new data layer these crop traits enable will help farmers to become more precise in how they fertilize and treat crops.

“It’s a trait embedded in crops, the first crop is soybean the second will be corn, that can tell us when there’s a fungal infestation. Later on, we’ll do insects and nitrogen deficiency,” Aronov said.

Plants have developed sophisticated systems of signals and responses they use when facing adversity, from insect or fungus attacks to inadequate nitrogen or water.

For instance, when some plants are being eaten by bugs, they produce compounds to make them taste bad. While other plants will put more energy into their root system to better extract nitrogen when they’re deficient in the nutrient.

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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.