Precision agriculture is just one of the pillars of the new world of high-tech farming. By Jason Jenkins
While capturing and using site-specific data is a powerful management tool for growers, John Fulton sees the future of high-tech farming as much broader than precision agriculture.
“We can eliminate the term ‘precision’ and just talk about agriculture,” says Fulton, associate professor of food, agricultural and biological engineering at The Ohio State University. “Technology is embedded in machinery today. I buy a combine and it has a yield monitor. Tractors and other equipment come with guidance systems. It’s changed. We talk more today about ‘digital agriculture.’”
When explaining this term to growers, Fulton describes four pillars of digital agriculture: precision agriculture, prescriptive agriculture, enterprise agriculture and big data. Combined, these pillars allow producers to be efficient, productive and profitable in their operations.
Precision agriculture is the technology piece of the puzzle. It includes the hardware and software that allow growers to implement zone-specific work.
The second pillar, prescriptive agriculture, is the use of data layers to create recommendations for zones within fields. “This is where we’re really seeing a lot of growth currently,” Fulton says. “When we talk about multi-variety planting or variable-rate seeding today, there’s got to be some data behind those prescriptions to bring a grower value.”
Enterprise agriculture as the third pillar, according to Fulton, adds business logistics into on-farm decision-making. By analyzing variable costs on a field-to-field basis and accounting for movement of equipment, location of assets such as grain bins and other variables, a grower can fine-tune management and business decisions.
The final pillar is something he refers to as big data. He believes the ag industry hasn’t yet tapped into this area in the way industries such as online and brick-and-mortar retailers have. They use data to predict not only what products their customers are likely to buy, but also when and where they might buy them. Large data sets could allow growers to be more predictive and proactive, allowing for better management of infestations, for example.
“You put the first three in combination and you get big data,” Fulton says. “Something like $10 billion has been invested in the tech area of agriculture in the past three years. That shows you that people want to be the Google or Amazon of agriculture.”