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

Kim DM, Zhang H, Zhou H, Du T, Wu Q, Mockler TC, Berezin MY - Sci Rep (2015)

Bottom Line: 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).

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110.

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.

No MeSH data available.


Related in: MedlinePlus

RWC of boxwood leaves at different post-turgid time points.2 h and 12 h post-detachment leaves correspond to an approximately 20 ± 2.4% difference in RWC levels. A trend-line (dotted) reflects polynomial decay (3-rd order) (R2 = 0.9999). Solid lines: RWC values at 2 h and 12 hours. Error bars correspond to standard error, n = 7 leaves.
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f1: RWC of boxwood leaves at different post-turgid time points.2 h and 12 h post-detachment leaves correspond to an approximately 20 ± 2.4% difference in RWC levels. A trend-line (dotted) reflects polynomial decay (3-rd order) (R2 = 0.9999). Solid lines: RWC values at 2 h and 12 hours. Error bars correspond to standard error, n = 7 leaves.

Mentions: Typical values of relative water content (RWC)20 in leaves range between 98% in turgid (saturated with water) and transpiring leaves to ~20–50%, a level that is equivalent to a moderate-to-strong stress2122, with the lost water content of 70% found in severely desiccated plants that cannot be recovered. To identify a model for moderate stress (equivalent to the loss of ca. 20% water in many species23) we used naturally desiccated boxwood leaves. The RWC values of leaves detached from the plant at different time points (2–50 hours post-detachment) served as a guide for stress level. Interpolation of the experimentally measured RWC data (Fig. 1) suggested that 12 h post-turgid leaves have a moisture content approximately 20 ± 2.4% lower than 2 h post-turgid leaves.


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

Kim DM, Zhang H, Zhou H, Du T, Wu Q, Mockler TC, Berezin MY - Sci Rep (2015)

RWC of boxwood leaves at different post-turgid time points.2 h and 12 h post-detachment leaves correspond to an approximately 20 ± 2.4% difference in RWC levels. A trend-line (dotted) reflects polynomial decay (3-rd order) (R2 = 0.9999). Solid lines: RWC values at 2 h and 12 hours. Error bars correspond to standard error, n = 7 leaves.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4632122&req=5

f1: RWC of boxwood leaves at different post-turgid time points.2 h and 12 h post-detachment leaves correspond to an approximately 20 ± 2.4% difference in RWC levels. A trend-line (dotted) reflects polynomial decay (3-rd order) (R2 = 0.9999). Solid lines: RWC values at 2 h and 12 hours. Error bars correspond to standard error, n = 7 leaves.
Mentions: Typical values of relative water content (RWC)20 in leaves range between 98% in turgid (saturated with water) and transpiring leaves to ~20–50%, a level that is equivalent to a moderate-to-strong stress2122, with the lost water content of 70% found in severely desiccated plants that cannot be recovered. To identify a model for moderate stress (equivalent to the loss of ca. 20% water in many species23) we used naturally desiccated boxwood leaves. The RWC values of leaves detached from the plant at different time points (2–50 hours post-detachment) served as a guide for stress level. Interpolation of the experimentally measured RWC data (Fig. 1) suggested that 12 h post-turgid leaves have a moisture content approximately 20 ± 2.4% lower than 2 h post-turgid leaves.

Bottom Line: 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).

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110.

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.

No MeSH data available.


Related in: MedlinePlus