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Enabling Breeding Selection for Biomass in Slash Pine Using UAV-Based Imaging.

Zhaoying Song1,2, Federico Tomasetto3, Xiaoyun Niu2

  • 1Research Institute of Subtropical Forestry, Chinese Academy of Forestry, No. 73, Daqiao Road, Fuyang, Hangzhou, 311400 Zhejiang Province, China.

Plant Phenomics (Washington, D.C.)
|May 11, 2022
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Summary
This summary is machine-generated.

Unmanned aerial vehicle (UAV) technology accurately estimates slash pine biomass and tree traits, offering a faster, cost-effective alternative to traditional methods for large-scale breeding plantations.

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Area of Science:

  • Forestry Science
  • Remote Sensing Applications
  • Quantitative Genetics

Background:

  • Traditional methods for monitoring slash pine biomass are labor-intensive and spatially limited.
  • Accurate biomass and trait estimation are crucial for effective forest management and breeding programs.

Purpose of the Study:

  • To assess the efficacy of Unmanned Aerial Vehicle Structure from Motion (UAV-SfM) for estimating aboveground biomass (AGB), belowground biomass (BGB), tree height, and crown area (CA) in slash pine.
  • To analyze the genetic variation and heritability (h²) of these traits using UAV-derived data.
  • To compare the potential for genetic gains using UAV data versus traditional ground measurements.

Main Methods:

  • UAV-SfM data acquisition at 70m flying height.
  • Marker-controlled watershed segmentation for tree crown area (CA) delineation.
  • Estimation of tree height, CA, AGB, and BGB.
  • Analysis of genetic variation and heritability (h²) across different plantation sites.

Main Results:

  • High correlation (R²: 0.58–0.85) between UAV-derived and ground-truth data for estimated traits.
  • Moderate heritability estimates (h²: 0.13–0.47) for all traits, with site-specific variations.
  • UAV-based and ground-truth data yielded similar genetic gains, confirming the viability of breeding selection.

Conclusions:

  • UAV-SfM provides a rapid, cost-effective, and accurate method for monitoring large-scale slash pine breeding plantations.
  • The technology supports efficient biomass and trait assessment, crucial for advancing genetic improvement programs.
  • Site conditions significantly influence heritability, highlighting the need for site-specific considerations in breeding strategies.