6 minute read
AI + Drones = The New Frontier
By Joli A. Hohenstein
As farmers increasingly take to the skies for farm management, technology experts, ag economists, and agronomists have the special task of figuring out how effective this approach can be, both as pilots themselves and as instructors and advisors to the farmers.
DJI Agriculture recently released its Agriculture Drone Insight Report 2022/23, reporting that at the end of 2022, the global number of DJI drones exceeded 200,000 units. Their cumulative operating area had reached nearly 500 million acres, bringing the benefits of aerial technology to hundreds of millions of ag professionals--not to mention the many other drone companies whose products service additional acres.
The World Economic Forum named agricultural drones one of the top three innovations that could be key to producing more crops with less effort, more precise inputs, and less impact on the environment.
The DJI report notes farmers already are seeing the results: Drone use helped a large-scale Washington potato grower reduce insect damage by 80 percent, and a Japanese rice producer increase yield to earn an additional $2,224 per acre.
More and more growers and retailers are using drones for scouting fields, but they still must identify what they're seeing and link that with specific actions that can address real-time needs in the field.
Artificial intelligence (AI), innovators say, is the next frontier.
By combining drones and AI, farmers can reduce guesswork across fields. “If we have a field with questions, instead of a hula-hoop test, we’re actually able to obtain per-acre stand count,” says Clint Chaffer, Asgrow Brand Manager, whose family farms in northwestern Illinois near Seaton. “It’s incredibly beneficial to determine if we need to replant.”
Clint uses technology from Sentera, which captures aerial imagery from fields and plots to help understand performance, letting farmers cover more acres with fewer resources. The company calls it an “ag analytics platform powered by machine learning.”
The data the drone acquires also pairs well with the information coming from Clint's Climate FieldView digital platform. “I look at field health and see what parts of the field I need to take a closer look at, then go fly a drone and see,” he explains. “We utilize it for another dataset that pairs well with the yield map to see if that change actually impacted yield.”
Leaf-Level Data
Once farmers have the data, the next step is being able to act on it, and that’s another benefit AI is able to provide. It’s here in the form of leaf-level data that lets you immediately take steps in your fields, says Bryan McMurtrie, Regional Sales Manager for Taranis, which has created the largest library of leaf-level imagery.
Their technology uses satellite images and AI capabilities to generate a field health index, which identifies anomalies within the field. Then, using their leaf-level insights, farmers can easily ground truth these anomalies and determine their next steps.
At a time when farmers are going to have to grow twice as many bushels to feed the world and stay profitable, AI technology can identify factors that rob yield and help farmers address them.
“Multiple studies say that for every inch of weed, you’re going to see 4 to 5 bushels of loss,” says Bryan. “It’s only going to cost about 1 bushel of beans or 2 bushels of corn to monitor your crop with Taranis and prevent that. There is no real capital expenditure for the customer.”
Taranis technology identifies the main stressors on crops: weeds, grasses, nutrient deficiencies, insects and chewing damage, and gives farmers actionable insights they can use to help unlock more yield potential.
Ag Research Advancements
Actionable information from AI isn’t just for farmers. Ag corporations are also leveraging AI to improve and advance research into new crop protection and seed technologies.
Asgrow’s parent company, Bayer, utilizes AI for genetics research.
The company’s Precision Breeding platform uses AI technology to more quickly and accurately pinpoint genetic changes needed and analyze data far faster than humans ever could. Mathematical puzzles that take humans 4 seconds to solve take an AI robot only 0.38 seconds. Likewise, the company says, AI can analyze millions of potential genetic combinations and make recommendations to solve breeding puzzles faster.
In fact, Bayer says AI is increasing the number of unique genetic combinations they can analyze each year by tenfold, and they’re able to do it without using more energy, land or water. The result, they say, is new seed varieties tailored to specific field conditions years ahead of schedule.
Likewise, Syngenta is collaborating with Insilico Medicine, an AI and deep learning company, to discover new, more effective crop protection solutions that safeguard the world’s food against diseases, weeds and pests, while also protecting ecosystems. The company says Insilico’s small molecule generative chemistry technology will help invent molecules for active ingredients faster, but also actively design molecules that are more sustainable and environmentally friendly.
In addition, Syngenta says AI can help them be confident that new products protect biodiversity, including pollinators and beneficial insects, and help them design products that help keep soil healthy to capture carbon and reduce greenhouse gas emissions.
For both companies, AI delivers the power to analyze and leverage large datasets in a much shorter timeline than they could with traditional research processes. With the world population projected to grow at a rate of more than 1 percent annually and increase to 9.8 billion by 2050, speed is of the essence. AI can help them provide farmers with tools to add to their arsenal. Not only to do more with less, but to proactively utilize solutions that manage and address the many differences climate change is bringing to farms.
It is, says Taranis’ Bryan McMurtrie, a new day in data. “In the past, data went into the tractor, came out of the combine. There was never anything in between,” Bryan says. “This technology gives season-long data capture.”
As Forbes magazine says, “Each season of data builds the knowledge-base to allow even more sophisticated use of the technology in the future.”
Bryan likes to call it a “game tape – you can review it and see what changes you need to make next season.”
