What is in this article?:
- Like it or not, big data is the new reality in farming.
- Data ultimately will take the guesswork out of farming.
Seven big data lessons
1. Big data will secure a considerably clearer farming picture.
Williamson, who farms more than 900 acres of cereal crops near Birmingham, England, is one of a growing number of producers around the world harnessing big data. He began yield mapping in 2007, convinced that mapping offered “the quickest way to get a lot of data in order to move forward.”
He followed this with targeted soil sampling to determine a correlation between soil nutrient variability and yields. He later began using a real-time sensor to apply in-crop nitrogen at varying rates based on the amounts of chlorophyll detected in the plants.
Williamson further enhanced this picture by measuring the soil electrical conductivity to build prescription maps — a picture he has recently enhanced with pest, weed and yield data.
Virk says that the kind of refined farming pictures Williamson and other farmers around the world are compiling on the basis of farming data are destined to become even clearer in the future — not only clearer but better integrated.
“The next step will be a cloud-based system that integrates all facets of farming on behalf of producers,” he says.
2. Along with clarity comes diversity.
“The farming picture will not only become more refined but also more diverse,” says Fulton, who draws a comparison with the different ways individual homeowners manage their landscapes.
To see and hear more comments from Fulton, click here.
“Homeowners manage their yards very differently, but they’re getting the job done and all the yards look good,” he says.
“A similar trend will play out in row-crop farming,” he says. “The more farmers learn from their individual data streams, the more their individual farming practices will diverge, whether in terms of variety selection, seeding rates or whatever.
“Like homeowners, though, they will be getting the job done.”
3. Big data should be viewed as stored knowledge for lean times.
As Williamson sees it, his job as a farmer is to “convert energy generated by the sun into profitable crops.”
In a sense, a farming data stream should be viewed much the same way: As stored knowledge that can provide farmers with a clear, comprehensive picture of their farming operations — an especially valuable asset during down cycles, he says.
“If the cycle dips, we need to be on our game to make sure we’re doing the best we can when it’s difficult to make the margin,” Williamson says.
4. Big data is no substitute for farmer’s intuition.
Despite the promise of Big Data, Fulton stresses that the “number 1 data set will always be a farmer’s intuition.”