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Active hyperspectral mid-infrared imaging based on a widely tunable quantum cascade laser for early detection of plant water stress
Optical Engineering ( IF 1.1 ) Pub Date : 2021-02-01 , DOI: 10.1117/1.oe.60.2.023106
Chaimae El Fakir 1 , Maroun Hjeij 1 , Ronan Le Page 1 , Luiz Poffo 1 , Bastien Billiot 2 , Pascal Besnard 1 , Jean-Marc Goujon 1
Affiliation  

Plant water stress has been extensively studied using hyperspectral visible- and near-infrared systems. Thermal imaging and the recent availability of widely tunable infrared quantum cascade laser (QCL) allow us to propose an active hyperspectral imaging system operating in the mid-infrared (MIR) band, where the system output consists of a series of narrowband subimages arranged across the reflectance spectrum of the sample, forming a hypercube data acquired by “staring” acquisition technique. To evaluate more precisely the capabilities of the active hyperspectral imaging, we propose a system composed of four powerful tunable QCL covering the 3.9- to 4.7-μm and 7.5- to 11-μm wavelengths ranges. Two cameras are used for detection: an InSb cooled camera ranging from 3 to 5 μm and a bolometer from 7.5 to 13 μm range. This system is validated by applying to growing plants for early water stress detection. Finally, we present and discuss results using partial least squares discriminant analysis classification technique to characterize water status of different plants, separated in two classes: control subjects were maintained at 80% of the amount of water to soil saturation ratio and stressed subjects at 20%. Initial discrimination results have shown the efficiency of the proposed system.

中文翻译:

基于可调谐量子级联激光的主动高光谱中红外成像技术,用于植物水分胁迫的早期检测

已经使用高光谱可见光和近红外系统对植物水分胁迫进行了广泛研究。热成像和广泛可调谐的红外量子级联激光器(QCL)的最新可用性使我们能够提出一个在中红外(MIR)波段运行的有源高光谱成像系统,该系统的输出由一系列窄带子图像组成,这些子图像跨样品的反射光谱,形成通过“凝视”采集技术采集的超立方体数据。为了更准确地评估有源高光谱成像的能力,我们提出了一个由四个功能强大的可调QCL组成的系统,该QCL覆盖3.9至4.7μm和7.5至11μm的波长范围。使用两个摄像头进行检测:InSb冷却的摄像头范围为3至5μm,辐射热计的范围为7.5至13μm。该系统已通过应用于生长中的植物进行早期水分胁迫检测而得到验证。最后,我们介绍和讨论使用偏最小二乘判别分析分类技术表征不同植物水分状况的结果,分为两个类别:控制对象保持在80%的水与土壤饱和度比率下,压力对象保持在20% 。初步的判别结果表明了所提出系统的效率。
更新日期:2021-02-25
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