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Large-scale field phenotyping using backpack LiDAR and CropQuant-3D to measure structural variation in wheat
Yulei Zhu1, Gang Sun1, Guohui Ding1
1State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Engineering, College of Agriculture, Plant Phenomics Research Center, Academy for Advanced Interdisciplinary Studies, Jiangsu Collaborative Innovation Center for Modern Crop Production Co-sponsored by Province and Ministry, Nanjing Agricultural University, Nanjing 210095, China.
This study introduces a backpack Light Detection and Ranging (LiDAR) system and CropQuant-3D software for large-scale plant phenomics. The integrated solution offers a mobile, accurate, and scalable method for 3D crop trait analysis in wheat.
Area of Science:
- Agricultural Science
- Plant Biology
- Genomics
Background:
- Current field-based phenotyping methods face limitations in mobility, cost, throughput, accuracy, and scalability for analyzing big data.
- Plant phenomics is crucial for connecting agricultural traits with genomic information.
Purpose of the Study:
- To present a large-scale, mobile, and accurate phenotyping solution for 3D trait analysis in crops.
- To address the challenges of throughput, scalability, and big data analysis in current phenotyping approaches.
Main Methods:
- Combined a commercial backpack Light Detection and Ranging (LiDAR) device with custom analytic software, CropQuant-3D.
- Applied the system to phenotype wheat (Triticum aestivum) and perform 3D trait analysis.
- Utilized LiDAR to capture millions of 3D points representing crop spatial features and CropQuant-3D to extract traits from point clouds.
Main Results:
- Successfully differentiated genotype and treatment effects on wheat growth and canopy structure under varying nitrogen fertilization levels.
- Demonstrated strong correlations between system-derived traits and manual measurements.
- Showcased the system's ability to perform 3D trait analysis at a larger scale and faster than previous methods.
Conclusions:
- The combined LiDAR and CropQuant-3D system effectively addresses challenges in mobility, throughput, and scalability for plant phenomics.
- An open-source graphical user interface enhances usability for non-expert researchers, making it a reliable tool for multi-location phenotyping.
- The system holds potential for improved accuracy and affordability, contributing to resolving the phenotyping bottleneck and better utilizing genomic resources.
