From Fields to Algorithms: How is AI Revolutionizing Russian Agriculture?
18:07 18.05.2025 (Updated: 16:50 19.05.2025)
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From Fields to Algorithms: How is AI Revolutionizing Russian Agriculture?
Digital transformation is not replacing farmers — it's helping them work smarter, Anastasia Grechenyeva, head of the AI laboratory at Moscow Timiryazev Agricultural Academy (MTAA), told Sputnik Africa.
Key advantages of using AI in agriculture:
AI allows to make decisions based on diverse data — something humans often find difficult.
It helps automate repetitive tasks like counting livestock and tracking plant growth.
Systems can now monitor farm workers — ensuring hygiene and offering health recommendations.
All MTAA's projects are based on real business needs to solve real issues — not "lab fantasies."
"We must not only develop, but also educate the population: explain that such systems are trustworthy, that such systems are already effectively used," Grechenyeva emphasized.
Here are some of the "digital helpers" developed by the MTAA:
⦁ AI-based milking process monitoring system to ensure compliance with hygiene and work standards;
⦁ quality analyzer robot, powered by custom neural networks, to sort fruits, such as apples;
⦁ robotic dog to determine fertilizer needs and detect pests in fields;
⦁ AI logistics and shelf-life predictor to estimate how long products stay market-ready.
Digital transformation is not replacing farmers — it's helping them work smarter, Anastasia Grechenyeva, head of the AI laboratory at Moscow Timiryazev Agricultural Academy (MTAA), told Sputnik Africa.
Key advantages of using AI in agriculture:
AI allows to make decisions based on diverse data — something humans often find difficult.
It helps automate repetitive tasks like counting livestock and tracking plant growth.
Systems can now monitor farm workers — ensuring hygiene and offering health recommendations.
All MTAA's projects are based on real business needs to solve real issues — not "lab fantasies."
"We must not only develop, but also educate the population: explain that such systems are trustworthy, that such systems are already effectively used," Grechenyeva emphasized.
Here are some of the "digital helpers" developed by the MTAA:
⦁ AI-based milking process monitoring system to ensure compliance with hygiene and work standards;
⦁ quality analyzer robot, powered by custom neural networks, to sort fruits, such as apples;
⦁ robotic dog to determine fertilizer needs and detect pests in fields;
⦁ AI logistics and shelf-life predictor to estimate how long products stay market-ready.
