Lien Max R, Barker Richard J, Ye Zhiwei, Westphall Matthew H, Gao Ruohan, Singh Aditya, Gilroy Simon, Townsend Philip A
1Russell Labs, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706 USA.
2Birge Hall, University of Wisconsin-Madison, 430 Lincoln Drive, Madison, WI 53706 USA.
Plant Methods. 2019 Jan 28;15:6. doi: 10.1186/s13007-019-0392-1. eCollection 2019.
Remote monitoring of plants using hyperspectral imaging has become an important tool for the study of plant growth, development, and physiology. Many applications are oriented towards use in field environments to enable non-destructive analysis of crop responses due to factors such as drought, nutrient deficiency, and disease, e.g., using tram, drone, or airplane mounted instruments. The field setting introduces a wide range of uncontrolled environmental variables that make validation and interpretation of spectral responses challenging, and as such lab- and greenhouse-deployed systems for plant studies and phenotyping are of increasing interest. In this study, we have designed and developed an open-source, hyperspectral reflectance-based imaging system for lab-based plant experiments: the HyperScanner. The reliability and accuracy of HyperScanner were validated using drought and salt stress experiments with .
A robust, scalable, and reliable system was created. The system was built using open-sourced parts, and all custom parts, operational methods, and data have been made publicly available in order to maintain the open-source aim of HyperScanner. The gathered reflectance images showed changes in narrowband red and infrared reflectance spectra for each of the stress tests that was evident prior to other visual physiological responses and exhibited congruence with measurements using full-range contact spectrometers.
HyperScanner offers the potential for reliable and inexpensive laboratory hyperspectral imaging systems. HyperScanner was able to quickly collect accurate reflectance curves on a variety of plant stress experiments. The resulting images showed spectral differences in plants shortly after application of a treatment but before visual manifestation. HyperScanner increases the capacity for spectroscopic and imaging-based analytical tools by providing more access to hyperspectral analyses in the laboratory setting.
利用高光谱成像对植物进行远程监测已成为研究植物生长、发育和生理的重要工具。许多应用旨在用于田间环境，以便对干旱、养分缺乏和疾病等因素引起的作物反应进行无损分析，例如使用安装在有轨电车、无人机或飞机上的仪器。田间环境引入了各种不受控制的环境变量，这使得光谱响应的验证和解释具有挑战性，因此，用于植物研究和表型分析的实验室和温室部署系统越来越受到关注。在本研究中，我们设计并开发了一种用于基于实验室的植物实验的开源、基于高光谱反射率的成像系统：HyperScanner。通过对[具体植物]进行干旱和盐胁迫实验，验证了HyperScanner的可靠性和准确性。
创建了一个强大、可扩展且可靠的系统。该系统使用开源部件构建，所有定制部件、操作方法和数据均已公开，以保持HyperScanner的开源目标。收集到的反射率图像显示，在每次胁迫测试中，窄带红光和红外反射率光谱都发生了变化，这在其他视觉生理反应之前就很明显，并且与使用全范围接触光谱仪的测量结果一致。
HyperScanner为可靠且廉价的实验室高光谱成像系统提供了潜力。HyperScanner能够在各种植物胁迫实验中快速收集准确的反射率曲线。所得图像显示，在施加处理后不久但在视觉表现之前，植物存在光谱差异。HyperScanner通过在实验室环境中提供更多高光谱分析途径，提高了基于光谱和成像的分析工具的能力。
