Smart spore collection and AI-powered analysis system for precision plant disease management

Overview

This solution addresses the critical challenge of plant disease management by connecting inoculum quantification with weather favorability data to determine optimal fungicide spray timing. The system consists of two complementary components: a standardized spore collection device that makes inoculum measurement accessible and quantifiable, and an AI-powered automated microscope for efficient slide analysis. Together, these tools enable the development of action thresholds that guide growers on precisely when to spray, reducing unnecessary fungicide applications while maintaining effective crop protection.

Validation across 195 farms demonstrated tangible benefits: farms using the spore trap system achieved an average yield of 61.7 compared to 60.4 under traditional management, while reducing average spray applications from 2.5 to 1.4. This reduction translates directly to lower input costs and decreased environmental impact from overspraying.

Technical specifications

Key features:

• Standardized spore collection device designed for ease of use and consistent air sampling across field locations
• Automated microscope system utilizing artificial intelligence for slide analysis and spore identification
• Integration of spore count data with weather parameters to calculate disease favorability indices
• Decision-support output providing clear spray timing recommendations for growers and consultants
• Scalable architecture enabling network deployment across multiple farms and regions

The system overcomes two major limitations in current disease management: the labor-intensive and error-prone nature of manual spore slide analysis, and the lack of standardized air collection protocols that previously prevented the creation of reliable action thresholds.

Technology readiness level

The spore trap component has been validated through five growing seasons in Brazil and tested across 195 farms with documented yield improvements and spray reduction. The AI-powered microscope analysis component is in development as the next phase of the solution. Future validation plans include establishing a network of spore collectors linked with consultants and growers to correlate spore counts with soybean rust occurrence and severity on sentinel plots, enabling development of weather-based favorability models and clear spray timing thresholds.