Kazan Scientists Develop System to Predict Plant Diseases
Scientists at Kazan State Agrarian University have developed machine vision algorithms that identify plant disease hotspots using data collected by unmanned aerial vehicles.
According to Nuriyev, the same principle—reducing costs through greater precision—also underpins the automation of agricultural machinery. AI-based driver assistance systems help reduce production costs through precision seeding and lower fuel consumption.
Engineers at Kazan State Agrarian University, together with Innosta, have also developed the Kurant-1 autonomous harvester for picking currants, gooseberries, chokeberries, raspberries and rose hips. The first prototype is undergoing pilot operation in Tatarstan, and serial production is planned to begin in the coming months.
