How Industrial AI Can Maximize the Potential of Agriculture’s Planting Season
I go to great lengths to speak with growers and meet with them in the field. For those of us in tech, having boots on the ground is essential to gaining firsthand industry knowledge and truly understanding the needs and wants of the people who are on the front lines.
I recently got the opportunity to do so during a key time of year for the agriculture industry: planting season. During this critical window, growers have approximately one week to get the job done and to get it done right.
With the equipment powered up and the machines rolling through the field, I studied how industrial artificial intelligence (AI) can help maximize growers’ potential.
What Boots on the Ground Look Like
I visited Pitstick Farms in northeast Illinois, a 2,500-acre corn and soybean operation. I rode along with Steve Pitstick, who’s owned and managed the family farm for more than 40 years and served as a research partner to the agrochemical company Monsanto.
Here’s how Steve summarized the importance of the planting season: “Of all the things I do in my field, if I mess up my planting, there is no amount of other activities I can do to get a stellar yield.”
It’s true. The number of factors that influence the success of a planting season is astounding. To give you an idea, here’s an abbreviated list of 10 things Steve is responsible for while operating machinery in the field:
- Setting auto-guidance for driving through the straights and manually handling each individual turn at the ends of rows.
- Communicating via teleconference with an international delegation of agriculture experts who are visiting the U.S. for a tour of Pitstick Farms.
- Fielding inbound calls to coordinate logistics on the fly.
- Managing the SeedSense tool to measure the accuracy of seed placement, confirm rows are planted cleanly, and view the status of the planted population.
- Managing the FieldView tool to gauge equipment downforce and make necessary tweaks.
- Managing the SmartFirmer tool to examine organic matter in the soil to help assess field soil health.
- Checking GPS auto-guidance with line-of-sight to make sure row planting doesn’t overlap with neighboring row borders.
- Inspecting the perimeter of equipment to ensure obstacles won’t be encountered and lifting planters at the ends of rows before executing turns.
- Calculating remaining nitrogen and seed, calling out for needed refills and monitoring fuel levels throughout.
- Monitoring the hydraulic lines and vacuum pressure of the planter.
My ride-along with Steve at Pitstick Farms demonstrates just how much growers have on their minds. They’re under constant pressure to produce. And in order to deliver, they must work as efficiently and effectively as possible in compressed periods of time throughout the year. Resource utilization, uptime, productivity and yield are paramount.
The Opportunity for Industrial AI in Agriculture
There are many ag tech products claiming to help growers. But today’s average grower has a tough time knowing where to start. First, it’s key to understand that true ag tech solutions solve problems of consequence by improving the grower life cycle. Products that target inconsequential issues or, worse, create new problems for growers to solve are simply not worth the time and investment.
All of this matters because more agriculture data is being produced than ever before. Growers should be harnessing it as a competitive advantage to improve their operations and profitability. This is where industrial AI comes in.
Industrial AI improves the grower life cycle by turning mountains of otherwise unused ag data into meaningful intelligence. It works at machine scale by synthesizing information from different ag data sources – assets, sensors, weather, satellites, and other systems – and surfacing insights, predictions and recommendations growers can act on.
Growers can use new intelligence gained from industrial AI seamlessly and autonomously in the context of their daily workflow to make smarter decisions. What do the outcomes look like? They’re able to keep their critical assets up and running. They can predict and prevent failures before they happen. They can count on their machines to produce when they need them most. And they can save time and money by running more efficient operations.
How effective have you been this growing season? Join the conversation on Twitter using the hashtag #grow18.