Digital Tools for Advancing Russia’s Agricultural Sector
The 28th Golden Autumn 2026 Russian Agro-Industrial Exhibition showcased IT technologies that will shape the future of Russian agriculture.
Digital platforms that until recently existed only as research projects have become part of everyday life. Smart farming systems are now tools that make work easier for Russian farmers.
This year, Golden Autumn highlighted three major scientific and technological projects led by Russia’s Ministry of Agriculture: one focused on agricultural technologies, another on livestock farming, and a third on biotechnology. All three are being developed around IT technologies.
Pusk: Accelerating Crop Breeding
Crop production in Russia is set to become a more controllable process, with outcomes that can be predicted in advance. An integrated technological system combining genotyping, digital phenotyping, environmental analysis and artificial intelligence algorithms is set to transform how new, high-performance crop varieties are developed. One example of this approach is Pusk (Launch), a Russian accelerated breeding platform operating at the Timiryazev Genomic Center.
The digital system brings together information on the genomes of 16 economically significant crops, as well as their phenotypes, soils and climatic conditions. Sequencing of more than 2,000 additional crop genomes is also nearing completion. The platform makes it possible to assess the agronomic and commercial traits of prospective varieties before they are even developed. AI enables large datasets to be processed faster and more accurately than conventional statistical methods allow.
Research in this field involves 86 scientific teams across 37 Russian regions. Their findings are uploaded to the Pusk platform, where they will be used to train a neural network on precise agronomic data. Using digital analysis, researchers will be able to select specific plant crosses and significantly accelerate the breeding process. A process that currently takes 10 to 15 years could be completed in approximately two to three years. This would help advance a key goal of the Prodovolstvennaya bezopasnost (Food Security) program: achieving 75% self-sufficiency in seeds for major crops by 2030.
Genomic Evaluation of Livestock
The primary goal of livestock farming is to increase milk and meat production. To achieve this, scientists need to improve breeding, animal health and housing conditions. Another key challenge is managing genetic potential.
The Project Institute for Digital Transformation at the Russian State Agrarian University – Moscow Timiryazev Agricultural Academy and Bashkir State Agrarian University are developing digital phenotyping systems for cattle. The platform is designed to automatically assess an animal’s body conformation and other external characteristics needed to monitor health and support breeding programs. This will improve the accuracy of assessments of an animal’s breeding value and help breeders select suitable parent pairs.
At the Krasnodarskoye teaching farm of Kuban State Agrarian University, researchers are developing genomic technologies that can assess animals’ genetic potential before visible traits emerge. This accelerates breeding and improves predictions of the productive traits of future generations.
Scientists at the K. I. Skryabin Moscow State Academy of Veterinary Medicine are also working to accelerate cattle reproduction. They are developing an integrated embryo transfer platform that could produce 7 to 10 calves per year from a single high-productivity donor by using recipient animals. Conventional methods cannot achieve the same level of efficiency.
Other priorities include using digital technologies to assess animal health and analyzing big data to predict the risk of infectious disease outbreaks. These tools could help prevent epidemics on farms.
AI-Driven Production Optimization
Another important priority is to introduce AI technologies into both agricultural operations and business management systems. According to Russia’s Ministry of Agriculture, neural-network services can reduce resource use in crop production by up to 20% through targeted application of agrochemicals. In livestock farming, precision feeding systems can cut feed consumption by up to 4%. Overall, experts at the consulting firm Yakov and Partners estimate that broader adoption of smart algorithms across Russia’s agricultural sector could increase companies’ annual operating profits by more than $6 billion.
“Our main priority is the profitability of the enterprise. Profits must enable businesses to reinvest and move into a new investment cycle. At the same time, technological development must ensure that consumers have access to affordable, high-quality food,” emphasized Oksana Lut, Minister of Agriculture of the Russian Federation.
The agricultural sector is therefore emerging as one of the most important areas for the practical application of Russian IT technologies. Digitalization will not only strengthen the industry’s technological sovereignty but also increase food production. Russian exporters are positioned to expand their share of the steadily growing global food market, while Russia’s role in ensuring global food security could become even more significant. The export potential of integrated Russian IT systems for agriculture is also set to grow. These systems could help food-importing countries modernize their own agricultural production.
