A Robot From Russia’s Stavropol Region Will Check Plant Health
Researchers at Stavropol State Agrarian University are developing a robotic platform designed for early diagnostics of greenhouse crops, aiming to reduce losses and improve productivity in controlled-environment agriculture.
Tackling Greenhouse Challenges
One of the most persistent challenges in greenhouse production is plant disease control. When infections are detected too late, growers can suffer significant losses. This is typically driven by the large scale of greenhouse operations, staff shortages, and, as a result, insufficient monitoring frequency and accuracy. Delays in data collection slow decision-making and reduce the effectiveness of corrective actions.
Information systems and automated plant inspection technologies offer a practical solution to this problem. In other words, the sector needs robots.
A prototype robotic system for diagnosing plant diseases has been unveiled by Stavropol State Agrarian University. Industrial trials were conducted for the first time in December 2025 at a facility operated by the Eco-Culture agroholding – Solnechny Dar LLC. The prototype was later presented in January 2026 at the Ulyanovsk greenhouse complex operated by AO Teplichnoye, one of Russia’s ten largest greenhouse producers.
The project was presented by Maksim Mastepanenko, Director of the Institute of Mechanics and Energy, and Igor Devederkin, Senior Researcher at the Center for Digital Crop Production. The prototype was reviewed by Alexander Vedyakhin, First Deputy Chairman of the Management Board of Sberbank of Russia.
A Russian Neural Network for Russian Tomatoes
The system enables automated detection of deviations in greenhouse crop development. The robotic platform moves through the greenhouse along a predefined route, capturing images of plants to identify early signs of disease or abnormal growth. These images are then uploaded to a digital platform, where an embedded neural network analyzes the data, performs diagnostics, and generates conclusions.
A key advantage of the project lies in its reliance on domestic data assessment and analytics systems. The neural network was developed jointly by Stavropol State Agrarian University and Agropromtsifra. Continuous collaboration between developers and growers improves diagnostic accuracy and speeds up responses to emerging risks. It also ensures technological independence from foreign solutions, allows algorithms to be trained on Russian plant varieties, and supports rapid adaptation to the specific conditions of individual greenhouse operations.
Following the prototype presentation, the team decided to secure a production base for expanding datasets and collecting nutrition and microclimate parameters for work with the Russian tomato hybrid F1 Berezina. Further customization of the robotic system will continue to align it with the operational specifics of AO Teplichnoye.
Expanding Greenhouse Robotics
Greenhouse robotics is developing rapidly across Russia. Graduates of the Russian State Agrarian University – Timiryazev Agricultural Academy have created an agricultural robot designed to diagnose diseases in greenhouse crops. The project, named Vavilov in honor of the renowned Russian scientist, operates five times faster than a human inspector.
Another agri-IT initiative is being implemented by the Institute of Environmental and Agricultural Biology (X-BIO) at Tyumen State University. There, researchers are developing a robotic system for monitoring plant health in industrial greenhouses. The ultimate goal is full automation of early detection of plant diseases and pests.
Early-stage disease detection remains a critical task for Russian producers of greenhouse vegetables and fruit. It reduces crop losses and lowers phytosanitary control costs.
In the near future, such systems are expected to become a standard component of agriculture, much like drip irrigation or automated thermal screens. Over time, they will be integrated into comprehensive agri-robotic complexes that include automated treatment via robotic sprayers, climate control systems, and automated harvesting. These integrated solutions represent the practical implementation of smart farming.
Such technologies also carry export potential, particularly in countries that are actively expanding greenhouse-based fruit and vegetable production.
