Artificial intelligence in agriculture

The collection and use of data offers extraordinary opportunities for businesses operating in agriculture. Data is pouring in, and nothing proves it better than the fact that you can't buy a modern machine without a data connection. To give an everyday example: the colour display capability of monitors, from 1 bit in the beginning, has now reached 32 bits (2 versus 4.3 billion colours), although the average person can only distinguish about a million colours.

This is what happens nowadays, with data as well. Tractors, implements, weather stations, satellites, sensors, fleets and drones collect and transmit countless data.

The lack of structure, inaccuracy and inadequate quality of current data can make their analysis and utilization difficult. Their quantity and diversity is a challenge for agricultural professionals.

At the same time, it is not enough to "clean" the data. In orded to utilize them, agricultural professionals must also improve their data analysis and processing skills. The value of data is determined by how it is used. Therefore, the farmers of the future must have the right knowledge and expert systems to interpret data and make the right decisions. Analysis and conclusions based on the correct data can help in achieving better crop quality, developing the correct action proposals, minimizing harmful environmental effects, developing sustainable agricultural practices and, last but not least, increasing profitability.

The challenge for the future in agriculture is to ensure accurate, reliable and relevant data easily accessible to farmers. In addition to data collection, analysis and interpretation are becoming increasingly urgent and important in today's and tomorrow's agriculture.

Perhaps this is where data processed by artificial intelligence will help us.

But where is the mechanical agronomist is lagging behind?

Stay tuned for the next part of this article!

Image for this article by DALL-E AI