AI Diagnoses Plant Diseases from Photos: Russian Innovation Targets Smarter Farming
A new platform from R-Style Softlab, part of Rosselkhozbank Group, promises to help farmers fight crop diseases. By analyzing plant photos, it suggests treatment and prevention strategies, paving the way for more efficient and resilient agriculture.
Neural Networks for Plant Health
At the Russian Field 2025 breeders and seed producers forum, R-Style Softlab unveiled a digital tool that lets farmers diagnose crop diseases in just a few clicks. Farmers upload photos of leaves, fruits, or stems via a mobile app or web interface, and the platform analyzes them using a database of plant diseases. It then provides tailored treatment and prevention recommendations.
The RS-AgroStyle application runs on generative neural networks, which create predictions by learning from existing data. The service delivers highly accurate results, improving farmers’ ability to make informed decisions quickly.
AI Accelerates Breeding and Research
Beyond diagnosis, the platform identifies vegetative stages, a crucial function for effective crop management. At the forum, experts emphasized AI’s role in accelerating breeding through digitized labs, phenotyping, bioinformatics, and climate modeling. According to Dmitry Aveltsov, Acting Director of the Center for Agroanalytics, AI and digital tools will enable breeders to create new varieties in years rather than decades.
Integrating digital platforms into scientific and production centers will open access to genetic data analysis, yield modeling, climate risk management, and remote sensing. RS-AgroStyle could eventually become part of integrated farm management software in Russia.
Boosting Yields, Cutting Costs
The system demonstrates that machine learning can effectively serve agriculture. It will accelerate and simplify diagnostics, reduce crop losses, cut chemical use, and improve farm efficiency.
The app’s potential goes beyond immediate benefits. Experts forecast nationwide deployment across farms, agrarian colleges, and extension services. Future modules could integrate satellite monitoring and climate forecasting, while offline functionality would make the tool valuable in rural areas with limited internet access.
In addition to agriculture, RS-AgroStyle could be used for training programs, helping farm employees and students in specialized agricultural classes develop practical skills. Such expansion aligns with global trends—Germany, for example, uses Plantix, an app developed by Berlin-based PEAT GmbH, to identify plant diseases and nutrient deficiencies.
A study by Yakov & Partners, 'AI in Russian Agriculture: Temporary Trend or Real Money?', estimates that AI adoption in farming and livestock could increase operating profits by $2 to $2.9 billion. The economic case for RS-AgroStyle is strong.
