How to determine field profitability
Yield monitors, and the massive amount of data they generate, have provided farmers with information on crop performance for decades, but a comprehensive analysis of the entire operation is needed to maximize profit.
While the yield maps created from that data offer insight on crop yield and characteristics such as moisture content, Terry Griffin says those maps are not enough.
“Rather than a yield map, farmers can convert that information to a profitability map, which gives site-specific information about which parts of a field are profitable,” says Griffin, a precision agriculture economist at Kansas State University. “The color-coded maps clearly indicate what parts of the field are making money, losing money, or breaking even.”
Accomplishing that means ensuring you record the true cost of every pass across a field. “Having that number is one of the first key steps in understanding if a field is profitable,” says Ryan Bergman, technical project specialist, Iowa State University. “There are many aspects of an operation we often take for granted and undervalue.”
For example, he says farmers usually underestimate the value of their time. They also “tend to underestimate the value of a machine hour because every hour that machine is on it has incrementally lesser value,” Bergman says.
In addition, sometimes a field must be replanted. “Because it takes time, fuel, tractor hours, and seed to replant wet spots, a farmer has to ensure those costs are calculated in,” he says. “Capturing all those numbers upfront is important.”
Whether you’re trying to understand profitability by the acre or by the bushel, Bergman says you also must realize it’s going to vary year to year. “You really need to look at multiple years and not just make decisions based on a single year,” he says.
However, if the technology is not set up correctly, it can’t fulfill its intended purpose.
“We have been an advocate of data accuracy for years,” Bergman says. “Making sure information is entered into the display correctly and data is clean and accurate goes a long way toward helping you understand your cost of production. When you get in that combine, it’s important you set the machine up right to record data.”
It starts with properly calibrating the yield monitor. “You also must remember that even after it is calibrated, a third of the observations in that data set are going to be bad because the combine is speeding up, slowing down, turning, all of which affect accuracy,” Griffin says, adding that all yield data from the combine has a lot of errors. “It’s just the nature of the beast. The data needs to be cleaned, and there are several options available to do that.”
For example, the USDA’s Yield Editor is a free tool that processes and cleans yield data. Griffin has also built a similar tool, the Automated Yield Monitor Data Cleaning Tool, which can be found at shiny.agmanager.info/yieldDev/.
Griffin often hears farmers complain about how difficult it can be to get data from a service provider hired to make a custom application.
“It’s a struggle to get that data layer,” he says. “If a farmer intends to create profitability maps, he may want to state in the contract that a service provider will be paid upon delivery of the as-applied data layer.”