K
Kathleen Martin
Guest
Feeding the world’s population is in crisis. The number of people on the edge of famine has jumped to 44 million from 27 million in 2019, the UN's World Food Program said this month.
We need to produce 50% more food in the next ten years to feed the growing population, and the challenge is to do it with less electricity, water and tillable land. We are also running out of farm labor, 50% less than ten years ago. Can AI play a role in addressing this looming crisis?
Here's one scenario for AI and agriculture: a drone intelligently scans the land looking for promising spots for planting. It carries the seeds contained in a shell of fertilizer and plants them. I've heard one company claim that the seedling sprouts into a plant 90% of the time. Such a system can handle up to six drones, at once and do the work of 20 people, and locates viable spots in remote areas.
Once the seedlings are planted, they need water and pesticide. AI systems can use computer vision and only dispense where required, potentially using 50% less water and 90% less pesticide. Soil health sensors could give the farmer 10-12 measurements of moisture, humidity, chemistry, etc., to increase the yield and the cash flow for the farmers.
Vertical farming is also possible. Because the environment is closely controlled, the AI models can constantly adjust the pertinent factors. The yields per “acre” (the vertical farm's footprint, with the help of AI, can produce 10x the yield.
Harvesting - some products could be harvested all at once, others daily based on ripeness. John Deere is at the forefront of bulk harvesting, which I’ll cover below. For the smaller harvest, like picking fruit, the machines are probably too costly to break even at this point. There are quite a few harvester robot models, but their deployment is, at the moment, minimal.
Storage optimization - 99% of all produce goes into some kind of storage before it arrives at the grocery store, restaurant or institution. Almost 45% of all produce is lost or spoiled in the storage and transport. But, an AI system can monitor produce and predict when it will spoil, often weeks in advance, providing the opportunity to get it moving before it does.
We also hear a lot about smart refrigerators, but this has nothing to do with the world food crisis.
But how do wheat and grains fit in?
I see one thing wrong with these proposals. They are producing fruit and produce, not the basic staples needed to feed the world, except for AI-powered devices to ease the labor shortage. Some of the devices do demonstrate the ability to raise yields with less water and far less pesticide.
The world doesn’t need perfectly ripened strawberries; it needs wheat, corn, soybeans. With 175 million acres of arable land in the Midwest, farmers primarily produce wheat, corn, and soybeans. Corn and soybeans are two key products for the Midwest. Last year, corn production was 15.1 billion bushels with a yield of 177.0 bushels per acre, 40% of which was exported.
Continue reading: https://diginomica.com/can-ai-help-address-looming-global-food-crisis
We need to produce 50% more food in the next ten years to feed the growing population, and the challenge is to do it with less electricity, water and tillable land. We are also running out of farm labor, 50% less than ten years ago. Can AI play a role in addressing this looming crisis?
Here's one scenario for AI and agriculture: a drone intelligently scans the land looking for promising spots for planting. It carries the seeds contained in a shell of fertilizer and plants them. I've heard one company claim that the seedling sprouts into a plant 90% of the time. Such a system can handle up to six drones, at once and do the work of 20 people, and locates viable spots in remote areas.
Once the seedlings are planted, they need water and pesticide. AI systems can use computer vision and only dispense where required, potentially using 50% less water and 90% less pesticide. Soil health sensors could give the farmer 10-12 measurements of moisture, humidity, chemistry, etc., to increase the yield and the cash flow for the farmers.
Vertical farming is also possible. Because the environment is closely controlled, the AI models can constantly adjust the pertinent factors. The yields per “acre” (the vertical farm's footprint, with the help of AI, can produce 10x the yield.
Harvesting - some products could be harvested all at once, others daily based on ripeness. John Deere is at the forefront of bulk harvesting, which I’ll cover below. For the smaller harvest, like picking fruit, the machines are probably too costly to break even at this point. There are quite a few harvester robot models, but their deployment is, at the moment, minimal.
Storage optimization - 99% of all produce goes into some kind of storage before it arrives at the grocery store, restaurant or institution. Almost 45% of all produce is lost or spoiled in the storage and transport. But, an AI system can monitor produce and predict when it will spoil, often weeks in advance, providing the opportunity to get it moving before it does.
We also hear a lot about smart refrigerators, but this has nothing to do with the world food crisis.
But how do wheat and grains fit in?
I see one thing wrong with these proposals. They are producing fruit and produce, not the basic staples needed to feed the world, except for AI-powered devices to ease the labor shortage. Some of the devices do demonstrate the ability to raise yields with less water and far less pesticide.
The world doesn’t need perfectly ripened strawberries; it needs wheat, corn, soybeans. With 175 million acres of arable land in the Midwest, farmers primarily produce wheat, corn, and soybeans. Corn and soybeans are two key products for the Midwest. Last year, corn production was 15.1 billion bushels with a yield of 177.0 bushels per acre, 40% of which was exported.
Continue reading: https://diginomica.com/can-ai-help-address-looming-global-food-crisis
