Sensor-equipped drones fly overhead gathering data on crop health or pest damage.Mention artificial intelligence and Tom Sawyer comes to mind, someone who wanted to work smarter, not harder, and was willing to hand the actual work over to someone — or now, something — else to get the job done.
AI and machine learning are becoming pervasive on, in, under, and above farmlands across the country where machines and humans either work alongside each other or the machines are programmed to take over a project.
AI is now making predictions on where seeds will grow best in what kinds of soils under controlled conditions for water/fertilizer/temperature. Sensor-equipped drones fly overhead gathering data on crop health or pest damage. Underground sensors watch over temperature and moisture control.
Weed and pest control has a machinery application like that found in John Deere’s See and Spray computer vision apparatus. Instead of a blanket spray, it picks off weeds one at a time.
When crops are ripe for picking and humans aren’t available to do so, autonomous pickers with gripper arms and vacuums fill the need.
There is even talk of a farmer’s home helper, some kind of electronic unit packed with algorithms and analytical information that can help analyze and solve field problems.
With that as background, the Southwest Ag Summit in Yuma on Feb. 25-27 chose the theme of “Tomorrow’s Tech, Today.”
Mellon practices what he preaches by operating a state-of-the-art growing effort over 6,000 acres maintained by GPS-driven tractors.
While there were a multitude of breakout sessions on some of the day-to-day difficulties ranging from integrated pest management, soil health, energy and water consumption, and food safety (as well as a Latino Farmer Symposium to reach under-served Hispanic farming communities), the keynote events revolved around high tech.
Economist and futurist Jay Lehr got top billing and the luncheon spotlight while a four-member panel of experts spoke to the issue of The Future of Precision Agriculture: Can the Use of Data and Technology Continue to Enhance Production Practices and the Bottom Line?
Lehr, Science Director at the Heartland Institute think tank, brought five decades of experience in agriculture to the podium where he divided new technology into technical trends, biotech, and data management.
“Pretty much everything coming on the scene in today’s agriculture is meant to improve things by reducing labor costs, saving money, and increasing profits,” he told Western Farm Press.
“Agriculture has been an early user of all kinds of technology — actually the first legal user of drones — and the real beginning of Big Data Analysis in agriculture when John Deere put GPS in all its machinery over 10 years ago to record everything going on in the field.
“I say ‘wow’ every day at these advancements because we’re currently in the phase of adopting what’s already here while making new discoveries like biotechnology that rearranges DNA and makes genes more productive — that’s the biggest thing we’re going to be seeing for many years to come, getting plants to become disease-resistant and exist with lower moisture and higher heat. That technology is going to be the most important overall phase of the next decade, the precision way we handle all aspects of farming.”
Lehr predicted the current and pending advances would contribute to a reduction in food waste, now estimated to be up to 40% of global crop yield lost to disease and pests, as well as a significant decrease in the 2 million tons of pesticides currently in use worldwide.
A four member panel spoke to the future of machine learning and the fact that new market research on AI in agriculture predicts substantial market growth over the next five years based on a myriad of factors and trends that will drive the market — everything from Farm Robots to Livestock Monitors and Drone Analytics.
One of the key players in that arena is John Deere, where Alexey Rostapshov, head of Deere’s new digital innovation lab in San Francisco, was one of the four panelists speaking to the future of precision agriculture.
“The complexity of agriculture adds up to a need for mega-data that needs to be cleaned up before it can be analyzed and tagged in useful form,” he said, acknowledging that John Deere was one of the largest users of cloud computing services in the world.
In remarks prepared for delivery, he added: “Innovation ensures we’re always looking towards the future and envisioning what could someday be using technology, changing the standard way of thinking to make farmers more productive and profitable using less input materials and safeguarding soil, air, and water.
“By adding additional technology capabilities like wireless connectivity, cameras, artificial intelligence and sensors, ag equipment increases its potential to deliver more precision in each job a farmer executes.”
Other panelists included Simon Belin of Naio Technologies; Hank Giclas, Science and Technology VP with Western Growers, and Murat Kacira, who runs the University of Arizona Controlled Environment Agriculture Center.
Giclas, whose job involves technology issues facing specialty crop agriculture in California and Arizona, said, “To me, precision means focus and that involves the key problems facing the industry — cost and availability of labor, cost of regulatory compliance, water cost and availability and the tools that can be brought to bear on these issues. I personally know of sixty startup companies currently working on solutions for some of these agricultural problems.
“Some of the recently introduced tools assist in identifying efficiencies in methodologies and how to optimize them while reducing costs, like the collection of data that demonstrates trends and weak points, data that collectively can be used to influence policy and push back on Draconian regulations. There’s power in shared data in the policy arena.”
His warning was ominous: “Some of the industry pressures are so immense that technological solutions must be found in order to survive. Western agriculture in general is extremely innovative and open to change and the introduction of new technology — and that’s the way forward.”
Kacira, whose concerns involved greenhouses rather than open fields, agreed about a data centric/plant centric focus “that will enable growers to have more meaningful information about their environment and how that data can improve both quality and yield.
“Precision agriculture has been at a maturity point in controlled environments because of sensor development. We now need to learn how to use all these new algorithms, processing this sensor data into modified control systems.