Crop protection assurance and compliance with Earthstream mobile app guidance

Technology
In development
Company

An AI-driven geospatial decision-support system integrated into the Earthstream mobile app that delivers real-time guidance on chemical usage, compatibility, and compliance to help growers manage pest and pathogen risks, reduce overspraying, prevent resistance, and improve crop production.

Overview

This solution addresses a critical gap in crop protection by replacing reactive, uncertainty-driven overspraying with a real-time geospatial decision-support system. Integrated into the existing Earthstream mobile app, the platform combines chemical usage, compatibility, and compliance data into actionable guidance and recommendations for growers. The goal is to address pest and pathogen risks proactively, prevent resistance development, minimize unnecessary chemical applications, and improve or maintain crop production with added product assurance.

Growers and their channel partners often rely on fragmented information sources for decisions about chemistry mixes, application rates, efficacy, and timing. By consolidating verified recommendations into a single mobile interface, the platform reduces uncertainty and helps growers make faster, more confident crop protection decisions even under time and supply pressures.

Technical specifications

Key features:

  • Real-time geospatial system of information integrating chemical usage, compatibility, and compliance data
  • Guidance and recommendations delivered through the existing Earthstream mobile app
  • Automated machine learning and AI-generated models for environmental risk analysis, including pest and pathogen forecasting
  • Forecasting capabilities designed to support proactive rather than reactive risk management
  • Model development and enhancement through collaborations with universities, grower-funded research organizations such as Cotton Inc., and enterprise agricultural partners
  • In-field verification processes used to test and validate models and recommendations
  • Evaluation of user engagement, data quality feedback, crop health status, and final production yield to measure recommendation effectiveness
  • Core modeling capabilities used to identify alternative factors and limitations in current recommendations
Technology readiness level

The system builds on mesur.io's existing Earthstream mobile app and its established AI and supply chain risk management capabilities. Validation is ongoing through collaborations with research partners and enterprise customers, with in-field verifications used to test and refine forecasting models. Product data for specific crops and risks currently depends on collaborator involvement and interest areas. Future validation will expand the guidance to the existing customer base and additional users from network partners, with effectiveness measured through crop health outcomes and yield differences.


About mesur.io

mesur.io is a technology company that provides AI-driven supply chain risk management, traceability, and compliance solutions. Its platform integrates diverse data sources with open-source intelligence to monitor global supply chains in real-time, focusing on transparency, ethical practices, and regulatory adherence. By utilizing advanced machine learning models and adhering to global interoperability standards, such as those defined by the W3C and IETF, the company provides organizations with predictive insights, risk scores, and secure data exchange capabilities across sectors including food, agriculture, textiles, and electronics.

The company’s solutions assist enterprises, government agencies, and policymakers in identifying risks—such as forced labor, supply chain disruptions, and environmental impact—before they occur. Mesur.io has demonstrated the efficacy of its technology through collaborations with organizations like the U.S. Customs and Border Protection and by receiving recognition as a top innovator in the World Economic Forum's Traceability for Circularity Challenge. Its work, including initiatives like the Food, Land, Water, Environmental Open-Source Risk Intelligence Synthesis Model, helps clients improve resilience, ensure material lifecycle visibility, and maintain market access in increasingly complex global environments.

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