Song Zhaoying, Tomasetto Federico, Niu Xiaoyun, Yan Wei Qi, Jiang Jingmin, Li Yanjie
Research Institute of Subtropical Forestry, Chinese Academy of Forestry, No. 73, Daqiao Road, Fuyang, Hangzhou, 311400 Zhejiang Province, China.
College of Landscape and Travel, Agricultural University of Hebei, Baoding, China.
Plant Phenomics. 2022 Apr 22;2022:9783785. doi: 10.34133/2022/9783785. eCollection 2022.
Traditional methods used to monitor the aboveground biomass (AGB) and belowground biomass (BGB) of slash pine () 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 0.130.25 lower than that in site 2 (range: 0.380.47). 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.
用于监测湿地松地上生物量（AGB）和地下生物量（BGB）的传统方法依赖于地面测量，这种方法既耗时又费钱，且仅适用于小空间尺度。在本文中，我们成功应用了集成运动结构（UAV-SfM）数据的无人机来估算湿地松人工林种植地中湿地松的树高、树冠面积（CA）、AGB和BGB。通过使用标记控制的分水岭分割法，以树顶和一组至少三米高的高度对每棵树的CA进行分割。此外，还分析了这些性状的遗传变异，并用于估计遗传力（ ）。结果表明，在70米飞行高度下，无人机与地面实测数据之间存在良好的相关性，相关系数范围为0.58至0.85，所有性状的遗传力估计值适中，范围为0.13至0.47，其中立地影响湿地松树的遗传力值，立地1的遗传力值比立地2低0.130.25（范围：0.380.47）。使用无人机和地面实测数据获得了相似的遗传增益；因此，育种选择仍然可行。本文所述方法提供了比传统地面调查更快、更高通量且更具成本效益的UAV-SfM调查，以监测更大面积的人工林种植地，同时保持数据准确性。
