American farmers are rapidly using artificial intelligence. The technology is as advanced as it is necessary.
A farmer stands in a lovely green field in the American Midwest, pointing his smartphone at one of his soybean plants. He takes a photo of a pest crawling on a leaf and then instructs an AI-powered system to identify the bug's species and whether it is a cause for alarm. This type of technology may appear to be innovative, yet it is necessary.
A labour shortage in agriculture is jeopardising the industry's viability, both financially and in terms of agricultural productivity. There just aren't enough hands to support the world's food systems.
This is particularly problematic in the United States, which produces the third-largest agricultural output after China and India.
One of the most pressing challenges is simple: farmers are getting older. Many people are unable to put in the long hours of manual effort required to run a farm successfully. And, while many of these businesses have been family-owned for decades, younger generations are no longer taking over from their elders, preferring to work in less labor-intensive, higher-paying industries. The hired workers that make up the remainder of the agricultural labour, primarily immigrants, are also following same patterns.
"Labour is the number one concern," says Emily Buckman, director of government affairs at the American Farm Bureau Federation, an industry trade association. "The average age of a farmer now is 60. Buckman herself grew up on a farm in Kentucky, where her 70-year-old father still works the soil, with only her brother to hlp him.
To address the issue, some US farmers are turning to new robots and AI tools, particularly as the labour pool is not only shrinking but also becoming more expensive, and agricultural yields are dropping. "We think about solutions to solving that problem, and we do think that advances in technology could help ease some of the labour load," Buckman said.
Artificial intelligence in agriculture is not a new concept: early implementations, such as auto-steering guidance systems for row crops like maize, have been in use for over two decades. However, AI adoption has been rapid in recent years; according to some estimates, 87% of enterprises in the US agricultural market were utilising AI in some form by late 2021.
The federal government is also accelerating the farm industry's transition to technology by offering financial incentives to speed up AI development and implementation across the country.
If the attempt to implement AI across over two million American farms is successful, the implications for the rest of the world might be significant. This is especially true as the global population grows and climate change threatens the agriculture ecosystems of some of the world's largest producers, including the United States, which exported more than $100 billion in products to China, Mexico, Canada, and Europe last year alone.
According to Buckman, the industry's goal is to create and deploy new technology on a large scale that is both affordable and accessible "so that farmers can feed the world". "The world's population is expected to grow by two billion by 2050, necessitating a 70% increase in food production. Innovative technology will assist us in accomplishing this goal."
There is a lot of pressure on the agricultural industry to provide solutions quickly. The US workforce crisis has already compelled some businesses to accomplish more with less. However, the urgency of the climate catastrophe is the tipping point. Erratic weather has made it more difficult to predict growing conditions while also reducing crop production.
In other words, hotter weather may result in less food, sooner than intended.
"All projections show major losses in crop yields due to climate change," says Patrick Schnable, a distinguished professor at Iowa State University who leads the Plant Sciences Institute. "A 10% or 20% reduction in maize yields would be catastrophic," he said. So, the question is, "Can we use AI to improve resilience?"
The AI Institute for Resilient Agriculture at Iowa State collaborates with partner institutions across the United States to develop AI-driven tools and technologies, and is funded by the National Science Foundation (NSF) and the United States Department of Agriculture (USDA).
"Our focus is looking at two broad problems," says Schnable. "One is sustainability identification – how do you design new activities that are related to agriculture and resilient to climate change," he says. "The second thing is, how can AI, robotics and sensing [tools] enable more profit for farmers, less utilisation of resources, energy, chemicals and water."
Baskar Ganapathysubramanian, director of the AI Institute for Resilient Agriculture and a professor in Iowa State University's mechanical engineering department, argues that addressing those two aims shows "a lot of promise, and some of it is already being implemented."
Buckman claims that drones and GPS technologies are currently the most widely used AI tools on the market. However, there are also additional options, such as self-driving tractors and combines, as well as quality sensors on those machines, that can assist farmers in determining which sections of their crops require more or less attention.
Robots can also perform automated sorting tasks that used to require a human eye. For example, some farms use AI technology to sort potatoes and hunt for certain flaws.
Others are utilising AI-enhanced cultivators to plant seeds and pull weeds from fields, effectively replacing dozens of human labourers.
Using AI to reduce resource use while increasing crop yields is part of a bigger strategy known as "precision agriculture" among specialists. Farmers are encouraged to embrace developing technologies, such as drones that evaluate a field's water or pesticide levels, to handle problem regions with surgical accuracy.
"Precision agriculture helps reduce water waste, be more efficient and do more with less," said Buckman. "US agriculture would've needed 100 million more acres 30 years ago to match today's production levels," she said. Precision agriculture tactics, together with AI, are largely responsible for the output advances.
Many of these improvements have been pioneered and scaled by key companies in the global agricultural industry. Among them is Illinois-based John Deere, which designs and manufactures tractors and other technological instruments for use in agricultural operations around the world.
"Our goal with AI and technology is to help farmers do their jobs better," says Sarah Schinckel, John Deere's director of emerging technologies in the Intelligent Solutions Group (ISG). AI tools are "changing farming, it's already here, and farmers are adopting it", she says. "We see a future where more and more farmers are using this technology."
According to Schnickel, John Deere has provided farmers with several AI technologies for decades, including Autotrac capabilities that enable hands-free combine steering. They will only improve as technology advances. In 2018, the business unveiled See & Spray technology, which "adds AI to the machines" and assists farmers in finding and removing weeds within crops, as well as applying herbicides just where necessary at an extremely granular level. According to Schnickel, this technology has allowed farmers to reduce their herbicide use by up to 66%, resulting in significant savings. "There's a clear ROI for a lot of this stuff," she said.
John Deere has also debuted fully autonomous tractors in the last few years. According to Schnickel, those tractors represent the next major step towards a bigger vision of farm autonomy, which should increase in the coming years. "We have goals by 2030 to bring autonomy to all production steps," she goes on to remark.
Lowering costs and boosting yields are obviously important for American farms and agricultural enterprises, but the benefits extend far beyond that and might have a global impact.
"Improved productivity in the fields means more profit for farmers, a more robust supply chain, and lower prices for consumers," says Steven Thomson, national programme leader of Agricultural and Biosystems Engineering at the USDA National Institute of Food and Agriculture (NIFA).
"More sustainable practices mean less degradation of natural resources and prevention of ecological damage to our planet," he said. This might involve employing AI to optimise crop and livestock management, which can help eliminate unhealthy animals or plants while increasing earnings and protecting the environment.
The US government recognises the promise of artificial intelligence in farming and has provided grants and investments in AI research centres dedicated to agriculture. According to Thomson, the major purpose of these programmes is to provide "easy-to-use, AI-aided decision support tools to help land stewards identify win-win choices across the environment, economy, and society".
Many modern techniques are quite complex, with an emphasis on precise resource distribution, soil surveillance, pathogen contact tracing to improve food safety, and harvesting robotics. However, investments are also driving simpler advancements.
According to Ganapathysubramanian, Iowa State researchers used AI to develop technologies like the pest-identifying smartphone app, which saved them hours of manual labour. The tools in development may also assist farmers in lowering expenditures, which is an important aspect of making agriculture financially sustainable, especially given the industry's already slim margins.
"AI provides a very natural and profitable tool for farmers to make more profound, localised decisions, hedge their bets and evaluate risks better," according to Schnable. Those instruments may be deployed at scale and worldwide with reasonable ease, resulting in a possible exponential rise in food yields in areas of the world where it is most needed, such as Southeast Asia. "The marginal cost to deliver [an AI tool] in India is next to zero," he said. "Once the tools are built, there's essentially no cost to deliver them."
Experts are cautiously enthusiastic about how these technologies, when placed in the hands of farmers on a big scale, would assist the agricultural business in dealing with evolving problems such as climate change, the precarious labour market, and others.
There is enormous potential, and there has never been a more pressing need.
(Source:www.bbc.com)
A farmer stands in a lovely green field in the American Midwest, pointing his smartphone at one of his soybean plants. He takes a photo of a pest crawling on a leaf and then instructs an AI-powered system to identify the bug's species and whether it is a cause for alarm. This type of technology may appear to be innovative, yet it is necessary.
A labour shortage in agriculture is jeopardising the industry's viability, both financially and in terms of agricultural productivity. There just aren't enough hands to support the world's food systems.
This is particularly problematic in the United States, which produces the third-largest agricultural output after China and India.
One of the most pressing challenges is simple: farmers are getting older. Many people are unable to put in the long hours of manual effort required to run a farm successfully. And, while many of these businesses have been family-owned for decades, younger generations are no longer taking over from their elders, preferring to work in less labor-intensive, higher-paying industries. The hired workers that make up the remainder of the agricultural labour, primarily immigrants, are also following same patterns.
"Labour is the number one concern," says Emily Buckman, director of government affairs at the American Farm Bureau Federation, an industry trade association. "The average age of a farmer now is 60. Buckman herself grew up on a farm in Kentucky, where her 70-year-old father still works the soil, with only her brother to hlp him.
To address the issue, some US farmers are turning to new robots and AI tools, particularly as the labour pool is not only shrinking but also becoming more expensive, and agricultural yields are dropping. "We think about solutions to solving that problem, and we do think that advances in technology could help ease some of the labour load," Buckman said.
Artificial intelligence in agriculture is not a new concept: early implementations, such as auto-steering guidance systems for row crops like maize, have been in use for over two decades. However, AI adoption has been rapid in recent years; according to some estimates, 87% of enterprises in the US agricultural market were utilising AI in some form by late 2021.
The federal government is also accelerating the farm industry's transition to technology by offering financial incentives to speed up AI development and implementation across the country.
If the attempt to implement AI across over two million American farms is successful, the implications for the rest of the world might be significant. This is especially true as the global population grows and climate change threatens the agriculture ecosystems of some of the world's largest producers, including the United States, which exported more than $100 billion in products to China, Mexico, Canada, and Europe last year alone.
According to Buckman, the industry's goal is to create and deploy new technology on a large scale that is both affordable and accessible "so that farmers can feed the world". "The world's population is expected to grow by two billion by 2050, necessitating a 70% increase in food production. Innovative technology will assist us in accomplishing this goal."
There is a lot of pressure on the agricultural industry to provide solutions quickly. The US workforce crisis has already compelled some businesses to accomplish more with less. However, the urgency of the climate catastrophe is the tipping point. Erratic weather has made it more difficult to predict growing conditions while also reducing crop production.
In other words, hotter weather may result in less food, sooner than intended.
"All projections show major losses in crop yields due to climate change," says Patrick Schnable, a distinguished professor at Iowa State University who leads the Plant Sciences Institute. "A 10% or 20% reduction in maize yields would be catastrophic," he said. So, the question is, "Can we use AI to improve resilience?"
The AI Institute for Resilient Agriculture at Iowa State collaborates with partner institutions across the United States to develop AI-driven tools and technologies, and is funded by the National Science Foundation (NSF) and the United States Department of Agriculture (USDA).
"Our focus is looking at two broad problems," says Schnable. "One is sustainability identification – how do you design new activities that are related to agriculture and resilient to climate change," he says. "The second thing is, how can AI, robotics and sensing [tools] enable more profit for farmers, less utilisation of resources, energy, chemicals and water."
Baskar Ganapathysubramanian, director of the AI Institute for Resilient Agriculture and a professor in Iowa State University's mechanical engineering department, argues that addressing those two aims shows "a lot of promise, and some of it is already being implemented."
Buckman claims that drones and GPS technologies are currently the most widely used AI tools on the market. However, there are also additional options, such as self-driving tractors and combines, as well as quality sensors on those machines, that can assist farmers in determining which sections of their crops require more or less attention.
Robots can also perform automated sorting tasks that used to require a human eye. For example, some farms use AI technology to sort potatoes and hunt for certain flaws.
Others are utilising AI-enhanced cultivators to plant seeds and pull weeds from fields, effectively replacing dozens of human labourers.
Using AI to reduce resource use while increasing crop yields is part of a bigger strategy known as "precision agriculture" among specialists. Farmers are encouraged to embrace developing technologies, such as drones that evaluate a field's water or pesticide levels, to handle problem regions with surgical accuracy.
"Precision agriculture helps reduce water waste, be more efficient and do more with less," said Buckman. "US agriculture would've needed 100 million more acres 30 years ago to match today's production levels," she said. Precision agriculture tactics, together with AI, are largely responsible for the output advances.
Many of these improvements have been pioneered and scaled by key companies in the global agricultural industry. Among them is Illinois-based John Deere, which designs and manufactures tractors and other technological instruments for use in agricultural operations around the world.
"Our goal with AI and technology is to help farmers do their jobs better," says Sarah Schinckel, John Deere's director of emerging technologies in the Intelligent Solutions Group (ISG). AI tools are "changing farming, it's already here, and farmers are adopting it", she says. "We see a future where more and more farmers are using this technology."
According to Schnickel, John Deere has provided farmers with several AI technologies for decades, including Autotrac capabilities that enable hands-free combine steering. They will only improve as technology advances. In 2018, the business unveiled See & Spray technology, which "adds AI to the machines" and assists farmers in finding and removing weeds within crops, as well as applying herbicides just where necessary at an extremely granular level. According to Schnickel, this technology has allowed farmers to reduce their herbicide use by up to 66%, resulting in significant savings. "There's a clear ROI for a lot of this stuff," she said.
John Deere has also debuted fully autonomous tractors in the last few years. According to Schnickel, those tractors represent the next major step towards a bigger vision of farm autonomy, which should increase in the coming years. "We have goals by 2030 to bring autonomy to all production steps," she goes on to remark.
Lowering costs and boosting yields are obviously important for American farms and agricultural enterprises, but the benefits extend far beyond that and might have a global impact.
"Improved productivity in the fields means more profit for farmers, a more robust supply chain, and lower prices for consumers," says Steven Thomson, national programme leader of Agricultural and Biosystems Engineering at the USDA National Institute of Food and Agriculture (NIFA).
"More sustainable practices mean less degradation of natural resources and prevention of ecological damage to our planet," he said. This might involve employing AI to optimise crop and livestock management, which can help eliminate unhealthy animals or plants while increasing earnings and protecting the environment.
The US government recognises the promise of artificial intelligence in farming and has provided grants and investments in AI research centres dedicated to agriculture. According to Thomson, the major purpose of these programmes is to provide "easy-to-use, AI-aided decision support tools to help land stewards identify win-win choices across the environment, economy, and society".
Many modern techniques are quite complex, with an emphasis on precise resource distribution, soil surveillance, pathogen contact tracing to improve food safety, and harvesting robotics. However, investments are also driving simpler advancements.
According to Ganapathysubramanian, Iowa State researchers used AI to develop technologies like the pest-identifying smartphone app, which saved them hours of manual labour. The tools in development may also assist farmers in lowering expenditures, which is an important aspect of making agriculture financially sustainable, especially given the industry's already slim margins.
"AI provides a very natural and profitable tool for farmers to make more profound, localised decisions, hedge their bets and evaluate risks better," according to Schnable. Those instruments may be deployed at scale and worldwide with reasonable ease, resulting in a possible exponential rise in food yields in areas of the world where it is most needed, such as Southeast Asia. "The marginal cost to deliver [an AI tool] in India is next to zero," he said. "Once the tools are built, there's essentially no cost to deliver them."
Experts are cautiously enthusiastic about how these technologies, when placed in the hands of farmers on a big scale, would assist the agricultural business in dealing with evolving problems such as climate change, the precarious labour market, and others.
There is enormous potential, and there has never been a more pressing need.
(Source:www.bbc.com)
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