Russia Develops Digital Platform to Predict Plant Traits
Artificial intelligence outperforms traditional methods in analyzing large-scale data.
The Timiryazev Academy, one of Russia’s leading agricultural universities, has completed the first stage of developing a digital platform for predictive breeding, the institution’s press service said. The system uses artificial intelligence to forecast plant traits based on DNA data, delivering higher analytical efficiency than conventional statistical approaches.
Model development follows a phased process. Researchers first create genetically diverse training populations of agricultural crops. They then study plant traits across different agroclimatic conditions and conduct in-depth analysis of DNA nucleotide patterns and their interactions.
Predictive Breeding and Digital Technologies
Predictive breeding, which relies on forecasting plant phenotypes, makes it possible to identify the most genetically valuable specimens and focus field trials on the strongest candidates.
The platform allows researchers to select optimal cross-breeding combinations and identify the most suitable regions for cultivation. Applying digital tools in breeding is expected to shorten the time required to develop new crop varieties and hybrids.
The next step for the researchers is to build predictive models for complex plant traits. The platform could ultimately introduce a new type of genetic service to the Russian market, available to both private and public-sector organizations.
