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Why Machine Learning Is Agriculture’s New Best Friend

What if I told you that countryside farmers and nerdy programmers can be great colleagues?

You would be surprised to know the incredible contribution that IT is giving to the agricultural sector.

Wanna be surprised?

I know you want it. So, go on!

 

Data and… tractors

 

Today, thanks to the application of artificial intelligence and machine learning (ML), agriculture can count on a wider variety of data and analytics tools.

These data are provided by many different types of sensors that allow a better understanding of the environment (crops, weather conditions, soil …) and the agricultural operations (machine data).

By feeding machine learning systems with the collected data, farm management can be supported with real-time recommendations elaborated via artificial intelligence.

Data-intensive approaches allow better decision-making, greater efficiency, and reduced waste while minimizing negative effects for the environment. 

Tractor + green paint = John Deere

ai in agriculture

“Data-intensive approaches allow better decision-making, greater efficiency, and reduced waste while minimizing negative effects for the environment.”

 

What is Digital Agriculture?

This innovative approach, which encompasses machine learning, data s