When we think about agriculture, we tend to think about old-school farming. But although many of us might think that the agricultural community is behind the curve when it comes to implementing new technologies, there is lots of evidence that farmers are actually moving quite quickly to modernize almost everything about the farming process — they’re using artificial intelligence in new and amazing ways to bring the process of food cultivation into the future.

Sowing the Seeds

High-tech agriculture starts at the very second that the seed is first placed in the ground. Experts in the field are familiar with “variable rate planting equipment” that does more than just planting a seed down into the dirt somewhere.

As you’ll see later in this article, all sorts of artificial intelligence work is being done behind the scenes on predictions — where a seed will grow best, what soil conditions are likely to be, etc. The power of artificial intelligence is being applied to agricultural big data in order to make farming much more efficient — and that’s only the beginning. (Read also: Why Big Data Is Big Business in Agriculture.)


Jan Engwerda at Future Farming in November 2019, cites Wageningen University & Research (WUR) in the Netherlands, revealing more about how good AI can be at picking a seeding strategy:

“People without any knowledge can use artificial intelligence (AI) to produce more profitable cucumbers than the most experienced growers.”

Resources like a contemporary piece on SeedX technology at Successful Farming or this guide from Bayer show the value of having cutting-edge AI in place to figure out the best crop outcomes.

Simply speaking, all of those centuries of inspecting leaves and stems, and trying to guess which rotations will best increase yields, are obsolete in the face of hard data and automated insights.

Who’s Picking Your Food?

Perhaps a better question would be “What’s picking your food?” That’s right — companies are already producing robotic harvesting equipment, partially in response to labor gaps that have left farmers scrambling to harvest crops like fruits and berries.

This is a reality now. Driverless tractors are harvesting fruits and vegetables and food commodities routinely. Just check out resources from Harvest Croo, which has produced an autonomous strawberry picking machine, and Abundant Robotics, where a vacuum apparatus harvests mature apples from trees, to see how this innovation works—and works well.

Harvest technologies like the Harvest Croo berry picker operate on the basis of machine vision and sensor fusion to “see” where harvest fruits and berries are. They use sophisticated directed movements to pick precisely. This is the kind of functionality that is very much in the “artificial intelligence” field and mimics human cognition and directed action.

Agricultural robotics is filling a need as labor pools decrease. But it’s also saving humans from one of the most repetitive and difficult jobs in our economy.

Eye in the Sky

How are farms using artificial intelligence to direct crop planting, harvesting and more, and how are they getting that data in the first place?

Check out what’s happening now in agricultural research, and you can see unmanned aerial vehicles or drones being outfitted with precision sensors in order to run the fields and get the data that’s needed. These airborne surveillance engines can look for stunted crops, signs of pest or weed damage, dryness and many other variables that are part of the difficulty of farming in general. With all of this data in hand, farmers can enhance their production models and their strategies across the lay of the land to decrease risk, waste and liability.

“American Robotics’ Scout System, a fully-automated drone system, takes care of the mission planning, flight, charging, data processing, and data analysis, so their customers only need to focus on what to do with that information,” writes Hugo Claver at Future Farming in May of 2020, well into the coronavirus economic realities, in which many processes are being converted from hands-on implementation to virtual designs. Reports like this one illustrate how technologies are doing the groundwork that goes into crop maintenance, and the extent to which farmers rely on them.

Pest and Weed Control

Yesterday’s farmers were living in fear of the windstorm and the grasshopper — not anymore. Farmers are quickly adopting new high-tech ways of protecting plants against weeds and various kinds of pests outdoors. Another alternative is to grow in greenhouses, which is being done as well, but some of the most amazing farming technology is being deployed outside.

The “See and Spray” model acquired by John Deere recently is an excellent example of harnessing the power of artificial intelligence and computer vision.

“We welcome the opportunity to work with a Blue River Technology team that is highly skilled and intensely dedicated to rapidly advancing the implementation of machine learning in agriculture,” John May, president, and CEO at Deere, said in a press statement, weighing in on the potential of new technologies in farming. “As a leader in precision agriculture, John Deere recognizes the importance of technology to our customers. Machine learning is an important capability for Deere's future.”

(Read also: 5 Ways Companies May Want to Consider Using AI.)

We know that artificial intelligence excels at image processing — computers can now “see” almost as well as we can. So by deploying mobile technologies with AI and computer vision built-in, farmers can find weeds and eradicate them, instead of blanket spraying an entire crop. That makes the food cleaner, and it saves enormous amounts of money. It’s just another example of real new technologies that are having a dramatic impact on yields and everything else.

“The food generating sector is one of the leading occupations among the people in rural areas lacks due to underdeveloped methodologies or use of outdated know-how,” writes Vikram Singh Bisen at Medium.

“But now AI in agriculture is boosting this sector using the power computer vision technology, to train the machines for better productivity in agro and farming.”

See and spray is only the beginning – this detailed piece and others go over the many ways that drone footage can be fed into AI/ML programs to determine how to treat crops, from the first seed to the eventual harvest.

Deep learning for yield optimization? These types of programs are now very much in the mainstream, and the drones, outfitted with competitive image processing, are the farmer’s eyes.

AI Agriculture

Yield Boosting Algorithms

When we talk about machine learning and artificial intelligence, we often talk about algorithms. The mathematical models behind computer science are the fundamental basis for how we deal with big data to make decisions.

Companies are now quickly developing agricultural yield boosting algorithms that can show farmers what’s going to be best for a crop. Despite some concerns about the difficulty of doing this type of analysis in nature, farmers and others have been able to make quite a lot of headway in maximizing crop yield, simply by applying the algorithms and intelligence generators that we’ve built to help computers imitate our own cognitive abilities.

This functionality goes back to what we talked about in the last segment. The artificial intelligence work has supported the idea that machines can deliver deep insights to farmers, taking a lot of the human reasoning out of planning for crop outcomes.

The Farmer’s Alexa

There is one more very interesting groundbreaking technology that might also be one of the highlights in the modern farmer’s tech toolkit.

Imagine a tired farmer sitting down to dinner at the end of a workday, puzzling over some conundrum — how to keep the crows out of the corn, or whether to seed a rocky patch of earth.

Propping his head on his arms, he directs his question to the next room:

“Alexa?...”

Yes, companies are talking about creating chatbots for farmers, artificial intelligence personalities like the smart home helper “Alexa” that are able to converse with farmers to help them figure out tough problems.

We’re hoping that these specialized farming chatbots are a little more capable than Alexa, since the current consumer technology basically provides encyclopedic facts and figures and not much else.

However, if they’re packed with the right answers and analytics information, the farmer’s chatbot could be a real boon to busy farm managers who are doing all they can to expand and grow their businesses.

“A chatbot in Messenger can act as a virtual assistant for your business,” writes Mary Rybakova at ChatFuel, showing off the value of this technology to farmers.

“[Chatbots] use a conversational, relatable style to interact with customers, allowing agriculture companies to improve customer service, productivity, and operational efficiency.”

As shown, chatbots can also be useful to farm customers, for example, in showing visitors more about what’s on a farm, and how to buy. In fact, if you think about how this kind of “ag assistance” tech could work, you see that it’s not just planning that can benefit: the labor-intensive aspect of communicating with customers is something else that can be effectively “farmed out” (excuse the pun) to computers.

Conclusion

These are some of the best new technologies coming out to help farmers produce all the food that we need in a rapidly changing world. Population growth and climate change will be massive challenges, but artificial intelligence deployment can help blunt the impact of these and other challenges, and make smart farming much more resistant to the problems that farmers face.