Abstract
The application of high-throughput phenotyping (HTP) techniques based on unmanned aerial vehicle (UAV) remote-sensing platforms to study large-scale population breeding opens the way to more efficient acquisition of dynamic phenotypic traits and provides new tools that should help close the gap between genotyping and traditional field-phenotyping methods. Toward this end we used a field UAV-HTP platform to deploy a RGB high-resolution camera to acquire time-series images. By using three-dimensional reconstructed point cloud models, we developed a repeatable processing workflow to extract plant height from time-series images. The plant height determined by the UAV-HTP platform correlated strongly with that measured manually. The plant heights estimated at various growth stages form temporal profiles that give insights into changes and trends in genotyping. Based on fuzzy c-means clustering analysis, we extract the typical dynamic patterns in phenotypic traits (i.e., plant height, average rate of growth of plant height, and rate of contribution of plant height) hidden in the temporal profiles. The fuzzy c-means clustering and set-intersection operation were first applied to analyze the temporal profile to identify how plant-height patterns change and to detect differences in phenotypic variability among the genotypes. The results revealed the capacity of UAV remote sensing to easily evaluate field traits on multiple timescales, for a few breeding plots or for 1000s of breeding plots.
Highlights
Maize (Zea mays L.) is one of the most important grain crops in China
High-throughput phenotyping (HTP) techniques based on unmanned aerial vehicles (UAV-HTPs) in field breeding programs have gradually become promising tools with which to acquire phenotype traits with high temporal and spatial resolution, affordable cost, and non-invasive remotesensing methods (Araus and Cairns, 2014)
The consequence is that the accumulated temperature for reproductive growth is insufficient to produce high grain yields (Hatfield and Prueger, 2015). These results suggested that the typical temporal profile of contribution rate of plant height (CRPH) could detect the difference of plant height increment among different genotypes of maize
Summary
According to a report by the National Bureau of Statistics in China, the planting area and grain yield of maize in 2017 were 35.45 million hectares and 21.58 million tons (National Bureau of Statistics of China, 2017), respectively, ranking it first among the major crops. New technologies to accelerate breeding through improving genotyping and phenotyping methods are currently in demand (Tester and Langridge, 2010). UAV-HTP can identify and access both simple and complex phenotypic traits, which are the key breeding targets for genetic breeding and include grain yield (Kefauver et al, 2017; Herrmann et al, 2019), above-ground biomass (Han et al, 2019), lodging resistance (Han et al, 2018a), senescence (Makanza et al, 2018), and plant height (Pugh et al, 2018; Wang et al, 2019)
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