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Light Acquisition02:16

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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

Qinghua Guo1, Fangfang Wu2,3, Shuxin Pang2

  • 1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China. qguo@ibcas.ac.cn.

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Summary

A new high-throughput crop phenotyping platform, Crop 3D, uses Light Detection and Ranging (LiDAR) and other sensors to accelerate plant breeding. This technology provides detailed 3D crop data for improved crop genomics and biology analysis.

Keywords:
LiDARcrop breedingdata fusionhigh-throughputintegrated platformphenotypic traits

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Area of Science:

  • Agricultural Science
  • Remote Sensing Technology
  • Plant Biology

Background:

  • Increasing global population and decreasing arable land necessitate advancements in crop breeding for food security.
  • High-throughput phenotyping is crucial for accelerating crop breeding programs.
  • Light Detection and Ranging (LiDAR) offers accurate 3D data acquisition with significant potential for crop phenotyping.

Purpose of the Study:

  • To develop and describe a novel high-throughput crop phenotyping platform, Crop 3D, in China.
  • To integrate LiDAR technology with other remote sensing tools for comprehensive crop data collection.
  • To assess the platform's design, functions, and potential applications in plant biology and genomics.

Main Methods:

  • Development of the Crop 3D platform, integrating LiDAR, high-resolution camera, thermal camera, and hyperspectral imager.
  • Acquisition of multi-source phenotypic data throughout the entire crop growing period.
  • Extraction of key plant parameters including plant height, width, leaf dimensions, leaf area, and inclination angle.

Main Results:

  • The Crop 3D platform successfully acquired comprehensive 3D phenotypic data.
  • The platform demonstrated capability in extracting various plant traits crucial for biological and genomic studies.
  • Testing results validated the platform's design and functionality for high-throughput phenotyping.

Conclusions:

  • The Crop 3D platform enhances crop phenotyping capabilities by integrating diverse sensor technologies.
  • Platforms combining LiDAR with traditional remote sensing represent a significant future trend in high-throughput crop phenotyping.
  • This integrated approach accelerates plant breeding and supports agricultural research for food security.