In the Midwest, it was once traditional for teenagers to detassel corn. It’s an extremely labor-intensive job, entailing walking through entire cornfields removing tassels by hand to prevent unwanted pollination. Now it’s mostly done by migrant workers, who can still barely keep up with the sheer volume of corn, even working long hours. But farms across the country are facing increasing labor shortages that have exacerbated their already thin profit margins. Farmers are looking for ways to make processes like detasseling more efficient. What if it could be partially automated? What if technology could make other aspects of agriculture faster and use fewer resources?
Automation in farming is helping us answer these questions with elegant solutions. PowerPollen, a farm tech company, has created a tool that removes the pollen from corn without needing to remove the tassel. They claim they can protect, preserve, and apply pollen at the optimal time to increase yield and minimize risks. This doesn’t only help with the labor issue – it makes the farm more profitable than it was before.
The most consistent problems of the agricultural industry are defined by variability and unpredictability. The dependence of crops on stable climates; year-to-year changes in yields based on environmental factors; crop disease; the cost of labor: farmers’ control over their livelihoods is often reduced, frustratingly, by factors that feel impossible to efficiently mitigate.
Modern issues have exacerbated many of those factors. It is a straining time to own a small to midsize farm in the United States. Increasingly dynamic weather patterns due to the impact of human life on the planet are causing droughts, floods, soil erosion, and loss of biodiversity. Addressing climate change in the agricultural field can be painful. It’s easy for some to deride inefficient watering or fossil fuel-powered irrigation as bad for the planet. But talking about agricultural practices in the abstract is different from depending on them for a livelihood. So how do we mitigate the environmental impacts of our agricultural industries in ways that work for farmers as well as they work for the planet?
The key concept is efficiency: helping farmers do more with less is in the interest of everyone.
Artificial Intelligence is growing rapidly in agriculture to address this need, particularly in precision farming, which offers ways to automatically provide insights that make agriculture much more efficient. AI vision systems are proving to have versatile uses for this. Light Detection and Ranging (or LiDAR) technology can provide three-dimensional field mapping, which helps farmers with terrain analysis and topographical evaluations.
AI vision can also identify plant diseases from photos, allowing farmers to quickly diagnose and treat issues. Tools like Agribot can use drones and data sets of photos of unhealthy and healthy plants to accurately catch diseases. Then they can notify farmers, or drones can apply herbicides to the specific crops that are affected. This enables farmers to be proactive against plant disease, and to do so efficiently. In many cases, the alternative to preventing plant disease is the indiscriminate spraying of pesticides. AI offers a method that is faster, saves resources, and reduces the use of harmful chemicals on crops.
AI can also simplify the process of crop management, especially for yield prediction and estimation, helping farmers get bigger yields with less waste. Small farms in Africa have begun using Virtual Agronomist, an AI-powered advisory system that provides advice for soil and crop management decisions through WhatsApp. After prompting farmers to georeference and verify the layouts of their plots on a map, the model generates target yields and nutrient management plans based on data from a soil property map of Africa and chatbot responses from other farmers.
Over 100,000 plots have been registered across several African countries already; Virtual Agronomist introduces a precision and bank of knowledge that was previously difficult to access for farmers. The Guardian shares the story of Sammy Selim, a coffee farmer whose Virtual Agronomist tool recommended using much less fertilizer than he had been planning, greatly reducing waste. When he began using it in 2022, he produced his highest yield ever. Virtual Agronomist has allowed Selim to operate with much more information, available much faster than usual, and has greatly reduced his waste while increasing his yield. And with more precision of information and less waste come benefits for everyone.
Developing apps can monitor the behavior of animals, sensing automatically when chickens on a farm are ill. Beyond increasing egg yields and efficiency, this is good for the animals. In the United Kingdom, AI tech to improve efficiency on egg farms has recently been awarded £2.6m in government funding. The “Facilitating Learning Opportunities, Cultivating Knowledge and Welfare through Integrated Sensing and Expertise” (Flockwise) system, developed by FAI Farms, is on a three-year trial to improve egg prices for British shoppers. Their BirdBox system uses AI to analyze a range of data, including the sounds hens make while nesting, to identify potential problems. Other applications of AI can similarly monitor cattle. Infrared cameras can autonomously identify inflamed udders, allowing infections like mastitis to be treated sooner.
We’re only scratching the surface here. The trend in AI adoption for agriculture is that it makes existing processes easier – streamlines parts of farming that are repetitive and labor-intensive, or automatically identifies elements that used to require minute observation.
Advancements in technology shouldn’t replace the connection that farmers feel to their land. But agriculture in the United States is facing a widespread labor shortage, in part because farms can not offer the same wages as other work that is often considered more desirable, and has year-round job security. The relative popularity of industries like construction, along with tariffs, administrative red tape around worker visas, and the low profit margins of farming in the first place have put strain on farmers.
Many of these issues are systemic and can not be fully addressed by working around the margins. But AI-powered tools undeniably have potential to provide relief for farmers who are struggling to muster manpower for repetitive, labor-intensive work like detasseling corn. And as they become more accessible they can make aspects of agriculture more egalitarian, like Virtual Agronomist is doing by giving African farmers easy access to key information.
By 2050, the world’s population is projected to reach 10 billion. Before then, we must make agriculture an efficient and desirable field. As AI tools for agriculture become more and more effective, we must support farmers in investing the up-front cost of new technology – for the health of their industry, and the sustenance of everyone.
