From the field to the dinner table, AI in agriculture can create a resilient food system

The Fourth Industrial Revolution has inundated every industry with new technologies — and agriculture is no exception.

Growers have always been tech savvy, but autonomous tractors, robots tending to crops, and drones precisely dispersing inputs are a big leap forward from 20th-century farms.

While these innovations create public excitement about tech’s potential on the farm, they only scratch the surface of how technology can help to tackle pressing challenges, like climate change and food supply constraints.

With AgriTech investments at an all-time high, startups and major players alike must thoughtfully apply innovations like AI across the entire agricultural value chain. These emerging applications could shape the future of agriculture.

AI can improve the earliest phase of the agricultural lifecycle: creating better crop inputs before seeds are in the ground.

For example, gene editing technology CRISPR — another innovation developed in a different industry — could help to design more resilient, high-yield seeds. Companies are applying AI to improve its speed and efficacy. Because many crops are so genetically complex — corn has 32,000 genes compared to 20,000 in humans — AI is invaluable in helping researchers understand the effects of editing multiple genes.

Companies like Inari and Cibus are using these technologies to bump up crop yields while requiring less water and other inputs. Increasing yields of staple crops like corn, soy and wheat is critical as the global population grows and natural disasters like droughts, exacerbated by climate change, make farming more difficult.

Drought not only threatens crops directly, but also creates a welcoming environment for weeds like Palmer Amaranth — known as “the king of weeds.” To tackle this, researchers are using AI to unearth crop protection that is safer and more effective than what’s available on the market today. For example, Enko is combining DNA-encoded libraries and machine learning models to make our experiments smarter and identify new solutions faster to combat pest resistance.

These innovations could help to stabilize the global food supply when geopolitical events disrupt trade. We’re seeing this play out now: Russia and Ukraine provide more than a quarter of the global wheat supply, and the war in Ukraine is pushing up the cost of wheat and other crops. Tailored, resilient seeds and crop protection for the evolving growing needs of each region can create a more stable web of staple crops.

As climate change effects worsen, growers need detailed real-time data to determine exactly how and when to treat their crops. Over time, the goal is for AI models that capture this data to learn from it and become continuously smarter.

AI-driven field mapping technologies predict potential yields of different crops throughout the growing season, continuously incorporating new information like weather trends and pest pressure. Yield maps can also help growers assess land values for purchase or lease, or give them solid information to make decisions about growing a different crop.

Sensors are another valuable on-the-ground tool. They gather data pinpointing threats to a crop, like dehydration or disease, in a specific area – allowing a grower to apply crop protection, water or nutrients only in that area. Depending on farmers’ unique circumstances and needs, they can select other technologies to pair sensors with.

Connecting sensors with virtual reality, like CropX has done, can create crops’ “digital twins.” Growers can use these to access their fields from anywhere and make informed decisions based on rich, real-time data. And using sensor data to inform precision spraying of safe, effective crop protection can produce higher yields of healthier crops.

These kinds of tools are becoming more crucial for growers like those in the western U.S., which is facing its worst drought in 1,200 years. Luckily, the declining cost of sensors means more farmers can access them and learn from the data they gather.

During the COVID-19 pandemic, consumers have become more aware of food supply chain complexities. The agriculture industry can use that as an opportunity to apply new technologies to tackle those complexities and communicate more transparently about how food is grown and reaches the dining table.

For instance, consumer demand for plant-based meat alternatives has taken off during the pandemic – fueled in part by COVID-19’s disruption to meat supply chains. Companies are getting creative about how to meet this new demand, with some using AI to find new flavour combinations that imitate meat.

AI can also give suppliers and consumers the information they need to make more thoughtful decisions about food. Food waste startups, some of which use AI to gauge consumer demand for specific items with the goal of leaving less leftovers on grocery shelves, have recently received a fresh injection of capital. And AI can be paired with cutting-edge technologies like blockchain to track information that consumers care about through the value chain, like where food was grown and how far it traveled to reach them.

The agriculture industry and farmers have long applied technology from other industries to improve farming practices and provide safe, healthy and affordable food to a growing global population.

Despite of the global population doubling over the last 50 years and a finite supply of agricultural land, the proportion of people without access to sufficient healthy food has dropped in that same period.

But the challenge is not over: millions of people still lack food access, the threats that climate change pose to farming are intensifying, and two billion more people will be on the planet by 2050.

This is a critical moment for the agriculture industry to draw on emerging technologies to solve real-world problems — namely building a durable, resilient global food supply.