Darle Elkin used to man Air Force nuclear weapon guidance systems, so it's probably not surprising that his tractor cab looks like Houston Mission Control.
Since his days of launching missiles from bunkers in the 1970s, he's replaced his sextant and celestial navigation with GPS and databases. On his Webster City, IA, farm, his 14 years of field data are a treasure trove of cause and effect.
His agronomic records drive decisions such as corn hybrid selection, fertility programs, variable-rate plant populations, crop rotation, nitrogen stabilizer use, and where and when to use corn fungicides. He uses his data to select offensive and defensive soybean varieties, and plants each bean in the area of the field that it fits best.
Variable-rate planting as well as crop nutrient applications have been the norm on his farm for five years. Elkin doesn't like to make decisions based solely on intuition. “I have this data,” he says, “and I use it.
“Ben Rahe, our Premier Crop advisor, and I define A,B,C management zones on our farm based on GPS yield data, soil type, drainage, fertility, organic matter ? any of the factors we can measure that affect our profit potential,” Elkin says.
“The A zones are where we aggressively push plant populations, fertility and spend more money to make money. Our corn population there might be 36,000-38,000/acre. The B zones are the current field average values. We might plant corn there at 34,000. By contrast, the C zones are where we use inputs conservatively, not wasting money where there's a drainage problem or sandier soils. We free up inputs to put on the A zones, and preserve the profits across all zones,” he says.
THIS APPROACH OF variable-rate inputs is like knowing how many people are coming to dinner, so that you prepare enough food.
Elkin lives to experiment. His maps show him how variable-rate inputs and seeding rates affect his profits. This year he added nitrogen (N) stabilizers as another variable in the mix. He uses a 1-2-acre check within field zones to contrast his experimental seeding and fertility rates with “standard” practice.
“We use checks on almost all the fields, experimenting with populations from 28,000 to 40,000, and variable-rating the N,” he says.
All these variable-rate treatments make for a large number of map layers, each representing areas within fields with different soil characteristics, input treatments, seeding rates, hybrid placement and yield histories. “That's where Premier Crop's database helps me out,” Elkin adds. “Their system helps make studying my fields and using my information efficient.
“The first time that we put all these map overlays together, it was the ‘wow’ factor,” Elkin says.
One experiment that's attracted attention from the neighbors and ag journalists is his multiple soybean variety placement (see details in this video , narrated by Ben Rahe). He pulls an air cart behind his planter, enabling him to plant offensive varieties where conditions are favorable, and defensive varieties in tougher, high-pH soils.
“I have to be 5% ahead of everyone else to stay alive in today's economic environment,” Elkin says. “Farming is no different than a Nascar race. We all have the same gas, tires, shock absorbers; it's just how you combine and drive them that wins the race. We use our records to consistently finish among the top 10.”
Elkin's yield and soil sampling maps date back to 1995. “With that amount of yield data, we can sort out the weather extremes and really bank on the rest of it,” Rahe says.
“The data reduces the number of guesses we have to make by informing our decisions,” Elkin says. “We may not always know why a given part of a field is off by 10 bu., but we can narrow the cause to just a few factors.”
Elkin can cross-check and anonymously pool his farm results with his fellow Premier Crop Systems clients. Collectively, they represent 30,000-40,000 acres of local hybrid and agronomic data in a 60-mile radius.
“Using their data, our growers can rate hybrids and varieties by profit in their fields,” says Dan Frieberg, Premier Crop Systems co-owner. “Just as dairy producers use DHIA records to benchmark each cow's performance, our growers can base their decisions on real-world results.”
Below are the types of agronomic decisions that Darle Elkin, Webster City, IA, has been able to make with more confidence using his 14 years of agronomic data:
- I'm going to add 160 more acres of corn this year; which fields are best suited to corn?
- I need to spray my corn-on-corn fields for volunteer corn due to a windstorm last fall; where did I plant LibertyLink hybrids so that I can use glufosinate to kill the Roundup Ready volunteer corn from last year?
- Parts of this field have a pH of 8; how can I plant a defensive variety there while still optimizing yield on my better ground in that field?
- Which seed companies and hybrid families made me the most money over the long term, excluding years of extreme weather?
- Which plant population is best for this zone of this field?
- Did an extra 2,000 plants/acre make me money?
- Which fields do I need to monitor more closely for potassium (K) deficiency (where I used manure and K might be the limiting nutrient)? When do I need to apply more? Am I keeping up with what the crop is removing?
- This field is pattern-tiled, so why are yields down 10 bu. compared to the rest of my operation?
- Why is this check plot full of yellow beans? Now we know for sure that this type of variety won't hold across this alkalinity and soil type. Next year we need to plant a defensive variety here.