Abstract
Phenotype describes the physical, physiological and biochemical characteristics of organisms that are determined or influenced by genes and environment. Accurate extraction of phenotypic data is a prerequisite for comprehensive forest phenotyping in order to improve the growth and development of forest plantations. Combined with the assessments of genetic characteristics, forest phenotyping will help to accelerate the breeding process, improve stress resistance and enhance the quality of the planted forest. In this study, we disposed our study in Eucalyptus trials within the Gaofeng forest farm (a typical Eucalyptus plantation site in southern China) for a high-throughput phenotypic traits extraction and genetic characteristics analysis based on high-density point clouds (acquired by a UAV-borne LiDAR sensor) and high-resolution RGB images (acquired by a UAV-borne camera), aiming at developing a high-resolution and high-throughput UAV-based phenotyping approach for tree breeding. First, we compared the effect of CHM-based Marker-Controlled Watershed Segmentation (MWS) and Point Cloud-based Cluster Segmentation (PCS) for extracting individual trees; Then, the phenotypic traits (i.e., tree height, diameter at breast height, crown width), the structural metrics (n = 19) and spectral indices (n = 9) of individual trees were extracted and assessed; Finally, a genetic characteristics analysis was carried out based on the above results, and we compared the differences between high-throughput phenotyping by UAV-based data and on manual measurements. Results showed that: in the relatively low stem density site of the trial (760 n/ha), the overall accuracy of MWS and PCS was similar, while in the higher stem density sites (982 n/ha, 1239 n/ha), the overall accuracy of MWS (F(2) = 0.93, F(3) = 0.86) was higher than PCS (F(2) = 0.84, F(3) = 0.74); With the increase of stem density, the difference between the overall accuracy of MWS and PCS gradually expanded. Both UAV–LiDAR extracted phenotypic traits and manual measurements were significantly different across the Eucalyptus clones (P < 0.05), as were most of the structural metrics (47/57) and spectral indices (26/27), revealing the genetic divergence between the clones. The rank of clones demonstrated that the pure clones (of E. urophylla), the hybrid clones (of E. urophylla as the female parent) and the hybrid clones (of E. wetarensis and E. grandis) have a higher fineness of growth. This study proved that UAV-based fine-resolution remote sensing could be an efficient, accurate and precise technology in phenotyping (used in genetic analysis) for tree breeding.
Highlights
Phenotype refers to the physical, physiological and biochemical characteristics such as morphology, structure, function of organisms under the combined action of genes and the environment [1,2]
The canopy boundaries depicted by Marker-controlled Watershed Segmentation (MWS) with better n/ha, n/ha, The canopy boundaries depicted
The high-throughput phenotyping combined with UAV-based data was applied to the genetic characteristic analysis of Eucalyptus clones aimed at exploring the effectiveness of the UAV technology for phenotypic analysis of forest trees
Summary
Phenotype refers to the physical, physiological and biochemical characteristics such as morphology, structure, function of organisms under the combined action of genes and the environment [1,2]. Forest tree phenotype describes the comprehensive expression of height, yield, color, wood properties, stress resistance and other traits in the process of Remote Sens. The analysis of phenotypes among forest trees can help accurately estimate the genetic characteristics, thereby improving our understanding of the adaptability of trees and their response to environmental changes, revealing the interaction between tree genes and the environment, as well as effectively correlating genotypes and phenotypes in forest trees for screening the target genes [8]. The development of precision silviculture and forest phenotyping requires the extraction and analysis of high-throughput, non-destructive and accurate data of forest phenotypic traits in order to quantify the genetic principles of specific phenotypes, accelerate forest tree breeding, improve the stress resistance of trees and systematically assess the internal relationship of “genotype–phenotype-environment” [10,11]. Eucalyptus are of great value for their contributions to industrial timber and pulpwood services in countries
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