SPOT: Scanning plant IoT facility for high-throughput plant phenotyping

Area of Science:

• Plant Science
• Agricultural Engineering
• Sensor Technology

Background:

• High costs and proprietary software limit access to advanced plant phenotyping platforms for smaller research institutions.
• There is a need for accessible, open-source tools for collecting high-quality, interoperable plant phenotypic data.

Purpose of the Study:

• To introduce the Scanning Plant IoT (SPOT) Facility as a novel, mobile, and open-source plant phenotyping platform.
• To demonstrate the capability of the SPOT Facility in autonomously differentiating plant cultivars using sensor data.

Main Methods:

• The SPOT Facility utilizes a mobile, laboratory-based system with hyperspectral, thermal, and LiDAR sensors.
• Sensors are mounted nadir and precisely positioned using computer numerical control (CNC) of stepper motors within a 10 ft x 10 ft scanning area.
• The platform's mobility allows deployment in diverse controlled environments like growth chambers and greenhouses.

Main Results:

• The SPOT Facility successfully collected real-time, high-quality phenotypic data.
• Preliminary experiments demonstrated the platform's ability to autonomously and non-destructively differentiate between plant cultivars using the gathered sensor data.

Conclusions:

• The SPOT Facility provides an accessible and versatile solution for plant phenotyping, overcoming cost and software barriers.
• The platform's sensor integration and data collection capabilities support advanced applications, including automated cultivar identification.