Managing Stored Drought-Stressed Corn In Early Spring

Feb 07, 2013

If you had any amount of confirmed mycotoxins in your grain at harvest, it is safer to avoid storing the affected grain.

Ambient temperatures will be getting warmer and soon will be above 40°F, which is about the temperature where fungal (mold) spores begin to grow again in the spring. If the fungal organism is one that produces mycotoxins, the level of mycotoxins in the grain can increase, which will likely result in greater dock when the grain is sold.

The worst case would be if the grain were refused by the grain dealer or not approved for feeding to certain species or sizes of livestock.

Disinfecting Empty Bins and Harvest Equipment

It is important to thoroughly clean out bins once they are empty, including all grain and grain dust that could still contain molds and insects. When moldy grain has been removed from the bin, use a spray disinfectant on all interior surfaces to kill mold spores. A solution of 1 gallon of 5.25% household laundry bleach and 20 gallons of water should work well. Several days after applying the bleach, rinse it off so as not to corrode galvanized metal.

Source: Cropwatch.unl.edu

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.