A Digital Breeding Assistant Takes Shape in Russia’s Adygea Region
Adygea State University has launched work on a homegrown digital platform designed to automate plant breeding, promising faster development of resilient, high-yield crop varieties and greater seed sovereignty for Russia’s agricultural sector.
New Seeds for Russia
One of the most pressing challenges facing Russian plant breeders today is supplying farmers with new seed varieties that can both increase yields and withstand climate change. At the same time, the country aims to reduce its reliance on imported seed material. Under Russia’s Food Security Doctrine and the national project “Technological Support for Food Security,” domestically bred seeds are expected to account for at least 75% of the country’s core agricultural crops by 2030.
Digital technologies are increasingly seen as a practical way to meet these goals. At Adygea State University, a project has been launched to create a digital assistant for breeders that could dramatically accelerate the development of new seeds. The platform is positioned as Russia’s first fully domestic solution to automate all key stages of breeding work, from data collection to decision-making.
AI-Driven Breeding
The new platform is designed to take on a massive share of tasks that are still largely performed manually. One of its core functions will be collecting and processing phenotypic data – the observable traits of plants that allow breeders to accurately assess their characteristics. Using machine learning algorithms, the system will analyze these datasets to identify patterns and generate evidence-based forecasts.
The assistant will also be able to predict potential breeding outcomes based on historical data and current trends, automatically selecting the most promising parent combinations for crossing. This shift toward AI-assisted decision-making is expected to compress breeding timelines that traditionally span decades into much shorter cycles.
Deploying a digital breeding assistant could significantly speed up the creation of new plant varieties, which is particularly critical as climate change forces agriculture to adapt more rapidly. Productivity among researchers is also expected to rise. By handling routine and data-intensive tasks, the AI assistant would allow scientists to focus on more complex and creative aspects of breeding work.
As Dmitry Aveltsov, head of the Center for Agroanalytics, noted, digitized laboratories, digital phenotyping, and the broad application of bioinformatics and artificial intelligence make it possible to develop new varieties in years rather than decades.
Yield Growth and Predictive Efficiency
Another advantage of AI-supported breeding is improved seed quality. More precise evaluation of plant traits enables breeders to create more efficient and adaptive lines, hybrids, and varieties. Plant resilience is also expected to improve, as AI tools help identify mechanisms responsible for biotic resistance.
Together, these advances could make Russian-bred seeds foundational for the country’s agricultural sector while boosting overall yields. That directly supports the core objectives of Russia’s Food Security Doctrine.
In 2026, Adygea State University is set to receive 400 million rubles (approximately $4.8 million) to implement the project. Development is being carried out under the Priority 2030 program with financial backing from Russia’s Ministry of Science and Higher Education. A broad consortium of scientists and practitioners is involved, including the Russian State Agrarian University – Timiryazev Academy, the Vavilov All-Russian Institute of Plant Genetic Resources, and Kuban State Agrarian University. The strategic industrial partner is the breeding and seed company RUSEED.
Looking ahead, the platform’s evolution is expected to include deeper use of machine learning and large data matrices to forecast breeding efficiency, integration of genomic and phenomic data into predictive models, and connections to drones and IoT sensors to automate the collection of phenotypic parameters. A separate development track focuses on cloud-based services that would enable breeding centers across Russia to collaborate on new projects in real time.
Once fully adapted and deployed within Russia, the digital breeding assistant could also become an export product. The platform is expected to be attractive to countries with developing agricultural sectors, including Central Asia, the Middle East, and Africa, where there is strong demand for digital tools that can accelerate breeding work and help crops adapt to a changing climate.
