By Stephen DeAngelis
Nothing is more important for humankind’s future than food security. That future, however, is at risk. A U.S. government study, authored by U.S. Department of Agriculture (USDA) agricultural economists Jayson Beckman, Fengxia Dong, and Maros Ivanic, along with Columbia University climate scientist Jonas Jägermeyr and Kansas State University professor Nelson Villoria, concludes, “A rising global population — with changing diets and an increasing demand for animal-based products, along with a changing climate — puts pressure on both the existing and future global food supplies. A changing climate could lead to warming temperatures and an increased likelihood of extreme weather events such as droughts and floods, impacting agricultural productivity and crop yields. Reduced crop yields diminish agricultural productivity, affecting not only agricultural quantities but also food prices and ultimately food security.”[1] Journalist Marc Heller highlights another conclusion from the study, “Production of four major crops won’t keep up with global demand unless the U.S. and other countries boost research aimed at beating climate change.”[1]
Unfortunately, at least in the short-term, “beating climate change” is beyond reach. As my good friend Thomas P.M. Barnett, Principal Business Strategist at Throughline, Inc., wrote in an email, “The American people, businesses, and government all need to move past the ‘Oh my God!’ phase of the discussion and into the ‘What do we do now?’ portion. … The imperative to mitigate climate change is a given; but, frankly, that effort is more about the year 2100 than the journey from here to there, which will be all about adaptation to a world being pervasively transformed.” The question is: How can artificial intelligence (AI) help the agricultural sector adapt to climate change?
AI in Agriculture
Journalist Lauren Coffey observes, “Technology has always co-existed with agriculture, but, over the last few years, there has been a concerted cross-pollination.”[3] Jordan Jobe, a project manager at the AgAID Institute, told Coffey, “There’s fewer workers and less water, … so we will need to find ways to address the changing landscape. And AI is part of that.” In fact, Coffey reports, “A majority of agriculture industry players — 87 percent — are using AI, up from 84 percent in 2019, according to a report from RELX, a British information technology group.” The key term in that in that report is “industry players.” AI can be expensive. Too expensive for most smallholder farmers, from whom much of the world’s population obtains their food.
Nevertheless, freelance writer Sam Becker reports, “American farmers are rapidly ploughing ahead with adopting artificial intelligence. The technology is as sophisticated as it is essential.”[4] Discussions about the benefits of AI in agricultural focus on increased crop yields. Becker reports that aging farm owners and a reduced workforce are also reasons AI is becoming an imperative. He explains, “Across agriculture, a dearth of workers is threatening the viability of the industry, both in terms of profitably and crop yield. There simply are not enough hands to sustain the food systems that feed the world. This is particularly a problem in the US, which produces the third-largest agricultural output behind China and India.”
Of course, crop yields and climate change adaptation are also significant reasons to leverage AI. Analytics journalist S Akash explains, “As the world population burgeons and climate change poses ever more significant challenges to traditional farming practices, the agricultural sector is embracing technological advancements to meet the growing demand for food production sustainably. At the forefront of this revolution are Big Data and Artificial Intelligence, two powerful tools reshaping the landscape of modern farming. By harnessing the vast amounts of data generated across the agricultural ecosystem and employing AI-driven insights, farmers can optimize crop yields, minimize resource wastage, and enhance sustainability.”[5]
Some Examples of How AI is Being Used
When AI and other advanced technologies are adopted, they help create the smart farm (or cognitive agriculture). As an article in Analytics Insight observes, “Smart farms redefine traditional practices. They monitor soil health and predict weather impacts. This ushers in a new frontier of cognitive agriculture promising bountiful harvests.” Below are some of the current ways AI is being leveraged in the agricultural sector.
• Precision Farming. The Analytics Insight article notes, “Artificial Intelligence is the driving force behind precision farming, offering farmers advanced tools and technologies to optimize agricultural processes. Machine learning algorithms analyze complex datasets to identify patterns, predict crop yields, and optimize resource allocation. AI-powered solutions enable autonomous machinery and robotics to perform tasks with unprecedented accuracy and efficiency, reducing labor costs and improving operational efficiency.”
• Data Collection. Tech writer Brian Heater, writes, “Agricultural robotics are not a new phenomenon. We’ve seen systems that pick apples and berries, kill weeds, plant trees, transport produce and more. But while these functions are understood to be the core features of automated systems, the same thing is true here as it is across technology: It’s all about the data. A huge piece of any of these products’ value prop is the amount of actionable information their on-board sensors collect.”[6] One source of continuing tension between manufacturers and farmers is: Who owns the data?
• Plant Health and Improved Crop Yields. As the USDA report noted, crop yields must keep up with consumer demands if the world’s food security needs are going to be met. AI can help. Tech journalist Lisa Morgan explains, “[Some] AI systems involve computer vision to ‘see’ plant health and identify pests. In fact, networks of sensors collect data on temperature, soil, watering, etc. that are combined to provide a better picture of crop health so growers can maximize crop output and quality. That’s a lot of data — too much for humans to analyze effectively in a timely manner. Therefore, AI, IoT, 5G and alternative network connections (like satellites which extend cellular coverage) work together to monitor crops or automate previously manual processes.”[7]
• Off the Farm Assistance. There are some activities, like research and development, that take place off the farm but whose impacts are felt on the farm. For example, journalists Tasmiha Khan and Iman Adem report, “Researchers at the University of Florida are using artificial intelligence to determine which chemical compounds produce the best fruit flavors based on consumer preferences.”[8] AI can also help with crop selection so farmers grow the crops that bring them the most bang for their buck. AI can help farmers manage risks by monitoring things like weather and receiving messages from equipment manufacturers recommending preventive maintenance actions. AI can also be used for “what if” scenario planning to help farmers strategize how to deal with the effects of climate change.
Concluding Thoughts
Climate change has challenged, and will continue to challenge, farmers. AI can help them face those challenges with a greater degree of confidence than was possible in the past. It’s all about problem solving. John Gottula, director of crop science at SAS, explains, “AI will form an important basis for reducing labor costs and increasing productivity, but for many, the focus has shifted away from moonshot ambitions to problem-solving pragmatism.”[9] The Analytics Insight article believes AI will help usher in a new Green Revolution. It asserts, “In the evolving agriculture landscape, cognitive technologies and crop management synergize. This heralds a new era. It’s Green Revolution 2.0. Cognitive computing views our fields as intelligent ecosystems. They adapt and optimize at every stage. This transformative approach empowers farmers with real-time insights. It also provides predictive analytics and smart decision-making tools. Artificial intelligence and agriculture fuse from sowing to harvesting. The fusion cultivates a sustainable and efficient future. Green Revolution 2.0 marks a technological shift. It also promises increased yields and resource conservation. A thriving agricultural landscape will last for generations to come.” Let’s hope the article is correct.
Footnotes
[1] Jayson Beckman, Fengxia Dong, and Maros Ivanic, Jonas Jägermeyr, and Nelson Villoria, “Climate-Induced Yield Changes and TFP: How Much R&D Is Necessary To Maintain the Food Supply?” United State Department of Agriculture, July 2024.
[2] Marc Heller, “USDA predicts crop shortfalls without more climate research,” E&E News, 15 July 2024.
[3] Lauren Coffey, “AI Taking Root in Growing Number of Agriculture Programs,” Inside Higher Ed, 10 July 2024.
[4] Sam Becker, “US farms are making an urgent push into AI. It could help feed the world,” BBC, 25 March 2024.
[5] S Akash, “Future of Farming Innovation and Transformation with Big Data & AI,” Analytics Insight, 10 March 2024.
[6] Brian Heater, “‘Orchard vision system turns farm equipment into AI-powered data collectors,” TechCrunch, 27 March 2024.
[7] Lisa Morgan, “AI examples that can be used effectively in agriculture,” TechTarget, 27 December 2022.
[8] Tasmiha Khan and Iman Adem, “An AI taste ‘connoisseur’ could be the future of crop breeding,” Agriculture Dive, 20 November 2023.
[9] Morgan, op. cit.
