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Near Infrared Hyperspectral Imaging System for Root Phenotyping

机译：用于根表型分析的近红外高光谱成像系统

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This paper presents the development and application of a hyper-spectral imaging system for root phenotyping. For sustainable plant production root systems optimized for growing conditions in the field are required. Therefore, the presented system is used for the research in the field of plant drought resistance. The system is used to acquire spatially resolved near infrared (NIR) spectroscopy data of rhizoboxes. In contrast to using visible light (380 nm-780 nm) the NIR wavelength range (900 nm-1700 nm) allows to discriminate essential features for the root segmentation and water distribution mappings. The increased image contrast in the NIR range allows roots to be segmented from soil and additional information, e.g. basic root-architecture, to be extracted. In addition, the water absorption bands in the NIR wavelength range can be used to determine the water content and to estimate the age of the roots. In this paper the hardware setup of the hyper-spectral root imaging system, the data analysis, the soil water content estimations and the root segmentation using different methods to optimize separation between roots and soil, both constituting complex materials of variable properties, are presented.
机译：本文介绍了用于根表型的高光谱成像系统的开发和应用。为了实现可持续的植物生产，需要针对田间生长条件进行优化的根系。因此，该系统可用于植物抗旱性研究。该系统用于获取根瘤菌的空间分辨近红外（NIR）光谱数据。与使用可见光（380 nm-780 nm）相比，NIR波长范围（900 nm-1700 nm）可以区分根段分割和水分布图绘制的基本特征。在NIR范围内增加的图像对比度使根部可以从土壤和其他信息中分割出来，例如基本的根架构，将其提取出来。此外，NIR波长范围内的吸水带可用于确定水含量并估计根的年龄。本文介绍了高光谱根系成像系统的硬件设置，数据分析，土壤含水量估计和使用不同方法优化根与土壤分离的根系分割方法，这两种方法都构成了性质可变的复杂材料。

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