Big Data Services Help Manage Nitrogen Use

Dec 31, 2014

By Gary Truitt

Nitrogen is a major factor in corn production and one of the most costly inputs a farmer will purchase. New data service technology is helping farmers do a better job of using just the right amount of nitrogen fertilizer to maximize yields. Dan Eppena, with Encirca from DuPont Pioneer, said field trials in Indiana in 2014 demonstrated just how god the technology can work, “We worked with several growers who used their traditional nitrogen formula on part of their field and our Encirca recommendation on the other part.” He said, in one example, the Encirca program recommended a higher rate of nitrogen because of the heavy rains, “Our recommendation was 130 units while the farmer used his traditional 100 units. At harvest, the part of the field with the 130 unites yielded 30 bpa more than the other part of the field.”

Eppena told HAT that, beginning in January, Encirca will add a module that will help growers determine not only the right amount of nitrogen but the right seeding population for a specific field, “Our research says if you really want to maximize nitrogen efficiency in a field you have to have the right plant population.” He added that it is not enough to just have the right nitrogen rate, but you must match it with the right seeding rate. The new Encirca system will give the grower that balance.

Click here to see more...

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.