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Optical structure modeling of plants for testing optical sensor technology in their near field

Optical structure modeling of plants for testing optical sensor technology in their near field
用于在近场测试光学传感器技术的植物光学结构建模
批准号:
516682649
负责人:
Professor Dr.-Ing. Tran Quoc Khanh
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:

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中文摘要
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英文摘要
To improve the light simulation in the near field of crop plants, their optical modeling is required. For this simulation, model building is done in two parts: (1) creation of a structural model of the plants (2) creation of an optical model of the plant components. Gaps in the literature have so far been found mainly in light simulation in the near field of crop plants; in particular, very little is known about the accuracy of such simulations. Optical properties of trees and arable crops have already been studied - but not those of crops typically grown under shelter. The present research project will create an optical structure model of young cucumber plants, which will subsequently be used as an example for virtual testing of optical sensor technology. The field of application of virtual plants is thus extended - from the systematic use of virtual plants for a better understanding of plant physiological relationships to the use of virtual plants to virtually test sensor technology and to virtually analyze relationships between metrics and plant properties. Phenotyping represents an exemplary application area here. A sensor response of certain traits can be simulated in advance - without this type having to exist in real life. To the knowledge of the applicant, this approach has not yet been implemented. This project can only be realized by an exact spectral characterization of the optical elements, which is why the acquisition of these data takes up a large part of the research project. In addition to the engineering sciences, which are the main focus of this research project, those disciplines that generally deal with virtual plants will benefit in particular. Here, the data situation is significantly improved by the targeted modeling of a model plant, the publication of the model and the associated data.
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