Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis.
Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis.
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DOI：
10.1038/srep15919
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发表时间：
2015-11-04
影响因子：
4.6
通讯作者：
Berezin MY
中科院分区：
文献类型：
--
作者：
Kim DM;Zhang H;Zhou H;Du T;Wu Q;Mockler TC;Berezin MY
叶片的光学信号是包括干旱在内的各种生物和非生物胁迫的重要监测和预测参数。从光谱测量得出的这些特征提供了植被指数--一种评估植物健康的量化方法。然而，常用的指标灵敏度较低。中度胁迫植物的水分含量变化相对较小，需要高对比度成像来区分受影响的植物。我们提出了一种新的方法，在800 nm到1600 nm的短波红外范围内使用高光谱成像来获得敏感指数。我们的方法基于高光谱分辨率(1.56 nm)仪器和图像处理算法(定量直方图分析)，使我们能够区分相当于20%相对含水量的中等水分胁迫。识别的图像衍生指数15XX nm/14XX nm(即1529 nm/1416 nm)优于常见的植被指数，如WBI、MSI和NDWI，具有明显更好的敏感性，使植物健康的早期诊断成为可能。
The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health.