This article is part of our ongoing Fast Forward series, which examines technological, economic, social and cultural shifts that happen as businesses evolve.
Of all the out-of-the-box products a Silicon Valley tech start-up could offer, Bear Flag Robotics may be delivering the most unexpected: plowed fields.
The company is developing autonomous tractors, a goal that equipment companies like Case IH, John Deere and Kubota are chasing as well. But the business model of Bear Flag, based in Sunnyvale, Calif., has a twist — it does not build the tractors. Instead, it adapts the sensors and actuators needed for driverless plowing to existing tractors produced by major manufacturers.
That step is not as sci-fi as it might seem. From equipment automation to data collection and analysis, the digital evolution of agriculture is already a fact of life on farms across the United States.
Auto-steer systems, which use GPS receivers to keep rows straight and avoid gaps or overlap, are available for equipment ranging from tractors to harvest combines to sprayers with 100-foot-wide booms. Precision seeders and fertilizer systems can be satellite guided to accuracy of an inch or less.
The difference: For the most part, those operations still depend on an operator at the controls.
“Autonomous operation will be a service in agriculture before it’s a product,” said Igino Cafiero, Bear Flag’s chief executive during a break from his work in a test field of cilantro about 60 miles southeast of the company’s headquarters. The company’s niche is providing secondary tillage, deploying its equipment after a harvest is complete to prepare the fields for the next planting.
The need for driverless farming equipment is intensifying, Mr. Cafiero said, because of a crushing labor shortage, which drives up wages and worker mobility. Tractors equipped with Bear Flag technology are able to work fields around the clock, without a driver, using sensors similar to those in autonomous road vehicles under development: lidar, radar and digital video.
The sensory devices provide more than what Mr. Cafiero calls situational awareness, vital for safe operation where workers and livestock may be nearby, also collecting data on the land to improve efficiency. While Bear Flag pursues expanding capabilities to tasks like planting and spraying that have long demanded human supervision, it also plans to expand to the labor-intensive harvest duties of crops including tree nuts and row crops.
The drive to increase productivity is urgent in all phases of agriculture. Feeding a world population expected to reach 9.7 billion by 2050 faces dire challenges, according to the summary of a United Nations report released in August. The effects of climate change — extreme weather, soil loss, migration pressures — will strain land and water resources, potentially disrupting food supplies.
Yet growing crops has historically been an uncertain enterprise, a livelihood that increasingly depends on forecasts of weather conditions, commodity prices and complex factors like maturity index and projected yield. Agriculture is seen as an industry ideally suited to large-scale data collection and analysis, and technology companies more closely associated with databases and computer hardware are seeing opportunities.
IBM, for example, made its move into the cloud — not the virtual data repository, but the puffy ones in the sky — in 2016 with the purchase of the Weather Company, bringing supercomputer prowess to what once depended on the centuries of record-keeping by trusted prediction tools like The Old Farmer’s Almanac.
Jeff Keiser, a manager for agribusiness solutions at the Weather Company, knows more than agriculture analytics. He also farms corn and soybeans in Indiana, where he has encountered many of the same conditions as the wide range of food producers who can make use of IBM’s Watson Decision Platform for Agriculture.
“With the cold spring followed by high temperatures and a lot of rain, it’s been a very challenging year,” Mr. Keiser said. “I got some planting done in April, but it wasn’t finished until June.”
The decision platform, which will mark its first anniversary in October, is designed to ingest data from satellite imagery and from sensors on farm equipment that monitor, among other things, seed counts, nutrient levels and fertilizer flow, said Cameron Clayton, the chief executive of the Weather Company. A sensor-equipped farm of 1,000 acres requires vast analysis and storage capabilities on the scale of what IBM can provide.
With more than two million acres of farmland around the world covered, the platform provides hyperlocal six-month weather predictions based on satellite and atmospheric data.
The system makes extensive use of IBM’s experience in artificial intelligence to build management models for corn, soybeans, wheat, barley and other crops. Each model takes IBM six months to a year to assemble and accounts for issues that include pest control and fertilizer requirements. It’s not a one-size-fits-all solution: The models are tailored to the specific crops, geared to produce longer potatoes for French fries or barley for malting in beer production.
Humans are not becoming obsolete on the farm by any means, a point that Mr. Cameron, raised on a New Zealand sheep farm, is sensitive to. “We make recommendations,” he said. “We don’t want to be in the business of full automation.”
IBM’s intent, rather, is to provide farmers with a dashboard of controls. A farmer inspecting field conditions can take an image from a smartphone or iPad, automatically uploaded to the decision platform, to diagnose crop health. The system provides a quick analysis and suggested remedy, sort of a WebMD service for crops. The longer-term goal is to deliver real-time growing advice; partnerships with equipment makers also hold the potential to make better use of sensors, equipment monitoring and drones to make remote inspections less labor-intensive.
The benefits of automation scale down to some smaller growers as well. Penny Gritt Goff, the third-generation operating manager of Gritt’s Midway Greenhouse in Red House, W.Va., takes advantage of computerized monitoring to keep tabs on temperature, humidity, nutrient levels and other conditions for three acres of hydroponic greenhouses where lettuce grows in flowing water and tomatoes are raised in a bed of coconut husks.
The computer system can send alarms when it gets too hot inside the greenhouses, but it also takes action on its own, spreading a shade cloth covering to cut down on sun exposure (or retain heat in the winter), open and close vents, and regulate irrigation.
“The automated controls narrow the chances of failure,” Ms. Goff said, and lessen the need for some aspects of the operation’s human monitoring. “We could add more advanced equipment, but at this size it’s not economically feasible.”
Will tomorrow’s digital farmers spend more of their long days at the keyboard than in the field or the barn? You might think things are headed that way, given that a recent convention of the National FFA Organization (what used to be called the Future Farmers of America) devoted display space to its FFA Blue 365 initiative, an online educational platform, and tech advances in areas that include beekeeping and autonomous vehicles.
A focus of the organization, which has 700,000 members of mainly high-school age, is to prepare them for the coming transformation in agriculture, according to Blaze Currie, a senior team leader for the FFA. But the goal is not so much to promote the changes as to teach the mechanisms to accomplish efficiency advances like remote monitoring of an irrigation system.
“When innovations are introduced on the farm, it’s often the younger generation of operator who gets handed the new technology,” Mr. Currie said, noting that when a sales representative arrives with a device like a field monitoring drone, he’s often directed to the family’s next generation of farmer, a digital native.
“Give him the drone,” the conversation typically ends.
