Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping.

Area of Science:

• Agricultural Robotics
• Plant Science
• Computer Vision

Background:

• Traditional plant phenotyping methods are often labor-intensive and lack scalability.
• There is a growing need for automated, high-throughput phenotyping solutions in field conditions.
• Existing automated systems may involve expensive aerial or confined platforms.

Purpose of the Study:

• To introduce a new, cost-effective robotic architecture for advanced plant phenotyping.
• To enable continuous, day-and-night monitoring of large agricultural fields.
• To facilitate high-throughput data acquisition for both individual plants and entire crop populations.

Main Methods:

• Development of a dual-robot system: Vinobot (ground vehicle) and Vinoculer (observation tower).
• Implementation of algorithms for autonomous data collection and 3D image processing.
• Integration of data analysis comparing robotic and manual phenotyping data.

Main Results:

• The robotic architecture demonstrated capability for large-area field inspection and stress region identification.
• High-throughput, accurate data acquisition from groups and individual plants was achieved.
• Preliminary results confirmed the system's cost-effectiveness, reliability, and versatility.

Conclusions:

• The proposed Vinobot-Vinoculer system provides a versatile and extendable solution for field plant phenotyping.
• This robotic architecture significantly enhances the efficiency and accuracy of agricultural data collection.
• The system offers a practical alternative to expensive aerial or confined phenotyping platforms.