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The United Nations reports that about 1/3 of the food produced worldwide every year is lost or wasted, and I think that number is not that surprising. Those of us in the United States see evidence of waste every time we go out for dinner or do a weekly cleaning of refrigerators filled with ice. Apart from the waste, however, there is a bigger problem that many of us do not realize. Just as the amount of food wasted globally is rising, the worldwide demand for food is rising ironically enough.

With exploding populations, the greenhouse effect and less land available for cultivation, we are actually dealing with a Worldwide food shortage of epidemic proportions. How will we manage to feed and hold 9 billion people who are estimated to populate the earth in 2050? And how do we support the 59-98 percent increase in food consumption that the population probably needs? Like many other problems that people face today in the world, we see digital transformation in agriculture, especially in the form of artificial intelligence (AI).

Sensors and data

By far the largest development in agricultural technology (AgTech) comes in the form of connected sensors and the IoT. As you would expect, successful agricultural production in digital transformation becomes a number game. With the help of AgTech, affiliated farmers start sharing data and making improvements in input, efficiency and business processes, largely thanks to AI powered sensors. These sensors can be based on the ground, on the air or on machines and all have a huge potential for agricultural production.

On the ground, for example, sensors can monitor the quality of plants, soil, animal health and weather. They can determine the best place to plant for the highest yield and how much they need to plant to prevent waste. In the air drones and satellites can monitor the health of crops and diseases of pests, so that the surprise of a lost crop is not prevented during the harvest. Agricultural equipment can also collect data about the expected cultivation production. For example, high-speed planters & # 39; planted & # 39; give estimates of the crop yield and harvest output, enabling farmers to plan for sales forecasts, overflows and shortages. That is not all. Robotic harvesters can even use AI to pick ripe fruit and vegetables at the right time, saving time, manpower and waste. Talk about digital transformation in agriculture!

John Deere is just one company today doing "precision ag", developing technology to help affiliated farmers determine where they can best plant and when to harvest. They can even help farmers remotely manage equipment from a central control center, thus saving even more time. (It goes without saying that when it comes to digital transformation in agriculture, the companies that do well are the ones that go the most seamlessly from the tractor supplier to the technology supplier – a compliment to John Deere.)

Yet the benefits are not just for the farmers. Blue River Technologies, for example, shows that they can reduce the use of herbicides by 90 percent by moving from broadcast spraying to targeted spraying using data extracted from AI sensors. Less herbicides are good for all of us, both for people and earth. It is clear that digital transformation in agriculture is not only good for food production, but also for the health of the planet.

Research and development

Just as AI helps accelerate pharmaceutical trials by shortening the trial and error phases of development, it does the same for agriculture. The AI ​​teams at Monsanto, for example, discovered that algorithms could help them identify faster which hybrid plants best grew in real plant conditions, thereby saving huge amounts of product development time. In the past, for example, Monsanto would evaluate maize hybrids for years in the field before marketing them – a process that could take eight years, from discovery to commercialization. The breeding program would select about 500 breeds for testing – a process that was costly and time-consuming. Using an algorithm that has used molecular marker and field test information over the last 15 years, they have shaved off an entire year of the breeding process. That is an incredible leap, especially given the population growth that we will encounter in the coming decades. What is even better: connected farmers worldwide will in theory be able to share this kind of information, which will ensure greater and faster product development, not only on Monsanto farms, but worldwide.

Image recognition

Another exciting development: image recognition at AI. Google is working to train AI to recognize 5,000 species of plants and animals, which would improve the drone ability to detect pest and crop diseases. This progress is huge because it allows farmers to control their area much faster and more accurately than ever before, and to understand pest patterns in the course of time.

Harvesting digital transformation in agriculture: more numbers and bodies are needed

Despite the enormous potential in AgTech at the moment, there are also some concerns. Firstly, AgTech relies on data, as with every AI process. But in a market where data is produced annually, data collection can be slow and difficult. The agricultural field has also found it difficult to compete with other technically savvy industries in attracting young AI talents. I hope that a younger generation, who wants to find a goal in their work, will be attracted to this promising market. Because when it comes to digital transformation in agriculture, there is potential that not only affects the productivity of the farmer, but also billions of lives.

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The United Nations reports that about 1/3 of the food produced worldwide every year is lost or wasted, and I think that number is not that surprising. Those of us in the United States see evidence of waste every time we go out for dinner or do a weekly cleaning of refrigerators filled with ice. Apart from the waste, however, there is a bigger problem that many of us do not realize. Just as the amount of food wasted globally is rising, the worldwide demand for food is rising ironically enough.

With exploding populations, the greenhouse effect and less land available for cultivation, we are actually dealing with a Worldwide food shortage of epidemic proportions. How will we manage to feed and hold 9 billion people who are estimated to populate the earth in 2050? And how do we support the 59-98 percent increase in food consumption that the population probably needs? Like many other problems that people face today in the world, we see digital transformation in agriculture, especially in the form of artificial intelligence (AI).

Sensors and data

By far the largest development in agricultural technology (AgTech) comes in the form of connected sensors and the IoT. As you would expect, successful agricultural production in digital transformation becomes a number game. With the help of AgTech, affiliated farmers start sharing data and making improvements in input, efficiency and business processes, largely thanks to AI powered sensors. These sensors can be based on the ground, on the air or on machines and all have a huge potential for agricultural production.

On the ground, for example, sensors can monitor the quality of plants, soil, animal health and weather. They can determine the best place to plant for the highest yield and how much they need to plant to prevent waste. In the air drones and satellites can monitor the health of crops and diseases of pests, so that the surprise of a lost crop is not prevented during the harvest. Agricultural equipment can also collect data about the expected cultivation production. For example, high-speed planters & # 39; planted & # 39; give estimates of the crop yield and harvest output, enabling farmers to plan for sales forecasts, overflows and shortages. That is not all. Robotic harvesters can even use AI to pick ripe fruit and vegetables at the right time, saving time, manpower and waste. Talk about digital transformation in agriculture!

John Deere is just one company today doing "precision ag", developing technology to help affiliated farmers determine where they can best plant and when to harvest. They can even help farmers remotely manage equipment from a central control center, thus saving even more time. (It goes without saying that when it comes to digital transformation in agriculture, the companies that do well are the ones that go the most seamlessly from the tractor supplier to the technology supplier – a compliment to John Deere.)

Yet the benefits are not just for the farmers. Blue River Technologies, for example, shows that they can reduce the use of herbicides by 90 percent by moving from broadcast spraying to targeted spraying using data extracted from AI sensors. Less herbicides are good for all of us, both for people and earth. It is clear that digital transformation in agriculture is not only good for food production, but also for the health of the planet.

Research and development

Just as AI helps accelerate pharmaceutical trials by shortening the trial and error phases of development, it does the same for agriculture. The AI ​​teams at Monsanto, for example, discovered that algorithms could help them identify faster which hybrid plants best grew in real plant conditions, thereby saving huge amounts of product development time. In the past, for example, Monsanto would evaluate maize hybrids for years in the field before marketing them – a process that could take eight years, from discovery to commercialization. The breeding program would select about 500 breeds for testing – a process that was costly and time-consuming. Using an algorithm that has used molecular marker and field test information over the last 15 years, they have shaved off an entire year of the breeding process. That is an incredible leap, especially given the population growth that we will encounter in the coming decades. What is even better: connected farmers worldwide will in theory be able to share this kind of information, which will ensure greater and faster product development, not only on Monsanto farms, but worldwide.

Image recognition

Another exciting development: image recognition at AI. Google is working to train AI to recognize 5,000 species of plants and animals, which would improve the drone ability to detect pest and crop diseases. This progress is huge because it allows farmers to control their area much faster and more accurately than ever before, and to understand pest patterns in the course of time.

Harvesting digital transformation in agriculture: more numbers and bodies are needed

Despite the enormous potential in AgTech at the moment, there are also some concerns. Firstly, AgTech relies on data, as with every AI process. But in a market where data is produced annually, data collection can be slow and difficult. The agricultural field has also found it difficult to compete with other technically savvy industries in attracting young AI talents. I hope that a younger generation, who wants to find a goal in their work, will be attracted to this promising market. Because when it comes to digital transformation in agriculture, there is potential that not only affects the productivity of the farmer, but also billions of lives.