Low Wild Rice Production Continues in Northern Wisconsin; Some Harvesting Opportunities

Sep 01, 2025

The Wisconsin Department of Natural Resources (DNR) today announced that this year’s wild rice crop in northern Wisconsin remains low, continuing a pattern of low production in recent years.

Annual wild rice production across the region is strongly linked to climate and weather events over the previous year.

"The 2025 season has brought a mix of conditions, including several notable storm systems," said Kathy Smith, Ganawandang manoomin (she who takes care of wild rice) with the Great Lakes Indian Fish & Wildlife Commission. "A fast-moving windstorm in mid-June produced widespread wind damage and heavy rainfall across the upper Midwest. In late June, some areas saw 6-7 inches of rain in a short period, contributing to temporary high-water levels on seepage lakes."

Remote sensing using satellite imagery is a new tool for evaluating annual wild rice abundance across the region.

Source : wisconsin.gov

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.