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Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis.


ABSTRACT: 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.

SUBMITTER: Kim DM 

PROVIDER: S-EPMC4632122 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis.

Kim David M DM   Zhang Hairong H   Zhou Haiying H   Du Tommy T   Wu Qian Q   Mockler Todd C TC   Berezin Mikhail Y MY  

Scientific reports 20151104


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 ap  ...[more]

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