Research Article | Open Access
Volume 2022 |Article ID 9783785 | https://doi.org/10.34133/2022/9783785

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

Zhaoying Song,1,2 Federico Tomasetto,3 Xiaoyun Niu,2 Wei Qi Yan,4 Jingmin Jiang,1 and Yanjie Li iD 1

1Research Institute of Subtropical Forestry, Chinese Academy of Forestry, No. 73, Daqiao Road, Fuyang, Hangzhou, 311400 Zhejiang Province, China
2College of Landscape and Travel, Agricultural University of Hebei, Baoding, China
3AgResearch Ltd., Christchurch 8140, New Zealand
4Auckland University of Technology, Auckland 1010, New Zealand

Received 
05 Oct 2021
Accepted 
17 Mar 2022
Published
22 Apr 2022

Abstract

Traditional methods used to monitor the aboveground biomass (AGB) and belowground biomass (BGB) of slash pine (Pinus elliottii) rely on on-ground measurements, which are time- and cost-consuming and suited only for small spatial scales. In this paper, we successfully applied unmanned aerial vehicle (UAV) integrated with structure from motion (UAV-SfM) data to estimate the tree height, crown area (CA), AGB, and BGB of slash pine for in slash pine breeding plantations sites. The CA of each tree was segmented by using marker-controlled watershed segmentation with a treetop and a set of minimum three meters heights. Moreover, the genetic variation of these traits has been analyzed and employed to estimate heritability (). The results showed a promising correlation between UAV and ground truth data with a range of  from 0.58 to 0.85 at 70 m flying heights and a moderate estimate of  for all traits ranges from 0.13 to 0.47, where site influenced the  value of slash pine trees, where  in site 1 ranged from 0.13~0.25 lower than that in site 2 (range: 0.38~0.47). Similar genetic gains were obtained with both UAV and ground truth data; thus, breeding selection is still possible. The method described in this paper provides faster, more high-throughput, and more cost-effective UAV-SfM surveys to monitor a larger area of breeding plantations than traditional ground surveys while maintaining data accuracy.

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