Technology: AI can predict the potential yield of potato seeds before they are grown

• AI and microbiology: a new era in agriculture.
• Microbes in potatoes: determining growth and resistance.
• AI model: combines microbial DNA data and drone images.
• More precision: predict seed quality and optimize crops.
• Sustainable impact: less waste and less pesticides.

Smart farming: AI predicts potato growth potential

An innovative artificial intelligence (AI) system is able to predict the performance of potato seeds before they are planted. Developed by biologists at Utrecht University, in collaboration with Delft University of Technology and plant breeding experts, the breakthrough combines microbial genetic data and aerial images captured by drones to identify the key factors that determine plant growth.

Why do potato plants grow unevenly?

Despite being the same variety, potato plants can differ greatly in size, yield and resistance. Previous research suggested that microorganisms present on the surface of the seeds could influence this development. Now, a team of scientists has confirmed that these bacteria and fungi play a key role in crop quality.

An AI model to improve production

The team has developed an AI model capable of analysing and predicting the performance of potato seeds. To do this, the system combines genetic data from the microbes attached to the seeds with drone images of crop fields. By cross-referencing this information, the AI ​​can identify which microbial combinations favour growth and which hinder it.

Large-scale data for accurate prediction

To train the model, the researchers collected data from thousands of potato seed samples from 240 test fields. The seeds were analyzed for bacteria and fungi, and plant growth was monitored throughout the season using drones.

According to Yang Song, one of the developers of the model, this methodology has made it possible to identify with great precision the microbes that are most influential in potato yield.

Microbes that boost or slow growth

The study showed that the microbial composition in seeds has a direct impact on plant development. For example, certain Streptomyces species promote growth, while other microorganisms can slow down development. With this information, farmers can select seeds with the best microbial composition to obtain healthier and more productive crops.

Future applications: optimized and sustainable crops

This discovery marks the beginning of a new era in precision agriculture. The researchers plan to expand the model with more data to better understand how microbes interact with crops. In the future, this technology could make it possible to coat seeds with an ideal mix of beneficial microbes, or even genetically modify plants to attract specific microorganisms.

Less waste and less environmental impact

The ability to predict seed quality through their microbiome not only increases productivity, but also reduces crop losses and decreases the use of chemicals such as pesticides. This represents a major step forward in terms of sustainability, promoting more efficient and environmentally friendly agriculture.