Abstract
The estimation of plant growth is a challenging but key issue that may help us to understand crop vs. environment interactions. To perform precise and high-throughput analysis of plant growth in field conditions, remote sensing using LiDAR and unmanned aerial vehicles (UAV) has been developed, in addition to other approaches. Although there are software tools for the processing of LiDAR data in general, there are no specialized tools for the automatic extraction of experimental field blocks with crops that represent specific “points of interest”. Our tool aims to detect precisely individual field plots, small experimental plots (in our case 10 m2) which in agricultural research represent the treatment of a single plant or one genotype in a breeding trial. Cutting out points belonging to the specific field plots allows the user to measure automatically their growth characteristics, such as plant height or plot biomass. For this purpose, new method of edge detection was combined with Fourier transformation to find individual field plots. In our case study with winter wheat, two UAV flight levels (20 and 40 m above ground) and two canopy surface modelling methods (raw points and B-spline) were tested. At a flight level of 20 m, our algorithm reached a 0.78 to 0.79 correlation with LiDAR measurement with manual validation (RMSE = 0.19) for both methods. The algorithm, in the Python 3 programming language, is designed as open-source and is freely available publicly, including the latest updates.
Highlights
Plant growth and development analysis is a key prerequisite for the successful breeding of new varieties and crop research
Two files correspond to different unmanned air vehicles (UAV) flight levels that we performed to see how the results of scanning are influenced by flight level
The input las file is cropped to the region of interest (ROI) containing experimental field-blocks with field-plots which growth parameters we wanted to analyze
Summary
Plant growth and development analysis is a key prerequisite for the successful breeding of new varieties and crop research. Measuring the growth of above-ground plant organs using a “ruler” represents a laborious and rather subjective process as the person performing the measurements cannot measure all the plants in an experimental field plot This can introduce important bias into the results of the experiment. In the plant research community “light detection and ranging” LiDAR sensors are being used more and more for what is termed plant phenotyping [1]—a rapidly developing field of plant research technologies aiming at high-throughput and automatic analysis of various parameters of plant growth and physiology. This includes the application of various sensors, but LiDAR has become the most popular one for the precise estimation of plant height and biomass in field conditions. LiDAR sensors can be mounted on a tractor-carrier, independent carrying-wheel platform or unmanned air vehicles (UAV) that
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