The code and user manual of D3P is freely available on GitHub ( https://github.com/lsymuyu/Digital-Plant-Phenotyping-Platform ). D3P is distributed under the free software open-source MIT license.
Open resource ↗https://github.com/lsymuyu/Digital-Plant-Phenotyping-Platform · lines:191-201Unverified paper record
Estimation of Plant and Canopy Architectural Traits Using the Digital Plant Phenotyping Platform
Plant Physiology · 16 Aug 2019 · 10.1104/pp.19.00554
Abstract
The extraction of desirable heritable traits for crop improvement from high-throughput phenotyping (HTP) observations remains challenging. We developed a modeling workflow named “Digital Plant Phenotyping Platform” (D3P), to access crop architectural traits from HTP observations. D3P couples the Architectural model of DEvelopment based on L-systems (ADEL) wheat (Triticum aestivum) model (ADEL-Wheat), which describes the time course of the three-dimensional architecture of wheat crops, with simulators of images acquired with HTP sensors. We demonstrated that a sequential assimilation of the green fraction derived from Red–Green–Blue images of the crop into D3P provides accurate estimates of five key parameters (phyllochron, lamina length of the first leaf, rate of elongation of leaf lamina, number of green leaves at the start of leaf senescence, and minimum number of green leaves) of the ADEL-Wheat model that drive the time course of green area index and the number of axes with more than three leaves at the end of the tillering period. However, leaf and tiller orientation and inclination characteristics were poorly estimated. D3P was also used to optimize the observational configuration. The results, obtained from in silico experiments conducted on wheat crops at several vegetative stages, showed that the accessible traits could be estimated accurately with observations made at 0° and 60° zenith view inclination with a temporal frequency of 100 °Cd (degree day). This illustrates the potential of the proposed holistic approach that integrates all the available information into a consistent system for interpretation. The potential benefits and limitations of the approach are further discussed.
Plant phenotyping relevance
HTP画像から作物の建築形質を推定するD3Pワークフローを開発し、推定精度と観測配置を評価しており、フェノタイピング手法が研究の中心である。
abstractWe developed a modeling workflow named “Digital Plant Phenotyping Platform” (D3P), to access crop architectural traits from HTP observations.
abstractD3P was also used to optimize the observational configuration.
abstractThe potential benefits and limitations of the approach are further discussed.
Code and data availability
The paper's D3P phenotyping platform code (coupling ADEL-Wheat with POV-Ray/PyProSAIL simulators used for the GF assimilation experiments) is explicitly stated to be freely available on GitHub under an MIT license. Other URLs (POV-Ray, OpenAlea, PyProSAIL, Python) are generic third-party dependencies, not paper assets.
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