The crop-canopy sensor concept is intriguing: Establish a small reference plot with more than enough nitrogen (N) to produce a healthy green canopy, then scan the entire corn field. Wherever corn falls short of that ideal green, apply N.
In practice, it’s more complicated.
Sensors aren’t a cure-all, says Mark Lehenbauer, a Missouri farmer who’s used them for six years to determine variable-rate application rates, including three years on the family farm.
“If you have other problems in your agronomic practices, this won’t solve them. The sensors pick up stress but they can’t tell if it’s an N problem or something else.
“Because of our livestock, we use manure on a lot of our fields. That started my interest in sensors because the manure was so variable,” Lehenbauer explains.
Where he doesn’t apply manure, Lehenbauer puts down 60-100 lbs./acre of N at planting or just after, then sidedresses all his cornfields at the V6 stage.
Three sensors mounted on the sprayer’s 40-ft. boom scan the crop’s color at the V6 crop stage and vary the application rate based on the sensor data.
The process takes careful planning and preparation. “You have to put in a high-N reference strip in each field for the sensors to read, and you need about four weeks from when that strip goes in so the corn can respond, and you need to have it clearly marked,” he explains. He also believes high-clearance spraying equipment is essential to give a wider window for completing application.
“You have a limited window and you don’t know how limited it will be, so you need a back-up plan to go this route.” says Lehenbauer. “Urea is my last resort if I can’t get to all my acres. This is definitely not a perfected science.
“It’s something everyone should have on their radar screen if they are raising grass crops. I think we’re going to have to account for our N sooner or later, and the best way to reduce N loss is to shorten the time between when you apply it and when the crop needs it,” he says.
Leading researchers question whether the sensor technology is “ready for prime time,” raising some of the same issues Lehenbauer notes.
“I’m comfortable with the accuracy of the sensors,” says Robert Mullen, Ohio State University precision-ag specialist. “The challenge is to translate what they measure into a decision. When you purchase the technology, you’re not just buying the box, you’re buying the decision tool that uses the data. It’s the reliability of diagnosing what causes the difference that will dictate how good this technology is.”
Mullen and John Sawyer, an Iowa State agronomist, both raise concerns about variability in growing environments, equipment, even different hybrids.
“There has to be some specificity among regions,” says Mullen. “What we do in Ohio is probably different than Missouri. We need to build that into the models.
“That is why the models used to make the N-rate decisions in Missouri are different than what we use in Ohio. Producers need to be aware of which decision model is being used,” he says.
Sawyer explains, “As new sensors come on, we will need new calibration for the equipment. If you change the sensor, then the readings will be different. It’s a new management approach, and the manufacturers need to get it into a working system that farmers can manage.”
But Does It Pay?
There’s a lot of variability in how crop sensors pay off, according to Mark Lehenbauer, Hannibal, MO, who uses Ag Leader’s OptRx sensor technology.
“We already had the yield monitor and sidedress equipment, so our only cost was the sensors,” he says. “We probably saw that pay off within two to three years, but that’s going to vary depending on the growing season and how much nitrogen you lose.”
Sensors can pay off either from a yield bump where more N is applied or by saving on N costs when they cut back on use.
“There’s not a flat equation. In some fields, we’ve seen no benefit and in others we’ve had a yield bump of 60, 70, even 80 bu./acre,” Lehenbauer says.
He estimates that 400-500 acres of corn may be the breakeven point between contracting for variable application versus buying sensor technology.