Light Drones for Basic In-Field Phenotyping and Precision Farming Applications: RGB Tools Based on Image Analysis.

Area of Science:

• Agricultural Science
• Remote Sensing
• Plant Science

Background:

• Accurate plant phenotyping is crucial for crop improvement and agricultural research.
• Existing methods for large-scale field data acquisition often require specialized, costly equipment.
• There is a need for accessible, high-resolution tools for temporal and spatial crop monitoring.

Purpose of the Study:

• To evaluate the feasibility of using low-cost drones for in-field plant phenotyping of cereal crops.
• To develop and apply a method for precise measurement of plant color and height using drone imagery.
• To assess the accuracy of the proposed phenotyping method on durum and soft wheat plots.

Main Methods:

• Utilized low-cost light drones equipped with sensors for aerial data acquisition.
• Implemented a color calibration algorithm (TPS-3D interpolating function) for accurate color measurement.
• Employed 3D ortho image reconstruction to derive plant height information for individual plots.

Main Results:

• Successfully obtained precise measurements of plant color and height for individual wheat plots.
• Achieved real color measurements with a low error rate (less than 12/256).
• Demonstrated the effectiveness of the drone-based method for detailed crop trait assessment.

Conclusions:

• Low-cost drones are a viable and effective tool for in-field plant phenotyping in cereal crops.
• The proposed method provides accurate and reproducible spatial and temporal data on crop traits.
• This approach offers a cost-effective solution for detailed monitoring of wheat plots.