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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

Histogram thresholding of 2 h and 12 h leaves on 1529 nm/1416 nm image.A threshold (red bar) is placed in between the two modes in the histogram, enabling visualization of either a (a) dry (left) or (b) fresh (right) leaf.
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f8: Histogram thresholding of 2 h and 12 h leaves on 1529 nm/1416 nm image.A threshold (red bar) is placed in between the two modes in the histogram, enabling visualization of either a (a) dry (left) or (b) fresh (right) leaf.

Mentions: The strong bimodality of 1529/1416 nm enabled efficient thresholding of the image for separating fresh from stressed leaves (Fig. 8). This technique has direct practical application in precision agriculture where plants with lower water content can be identified by selecting an appropriate threshold on the image histogram.


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)

Histogram thresholding of 2 h and 12 h leaves on 1529 nm/1416 nm image.A threshold (red bar) is placed in between the two modes in the histogram, enabling visualization of either a (a) dry (left) or (b) fresh (right) leaf.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f8: Histogram thresholding of 2 h and 12 h leaves on 1529 nm/1416 nm image.A threshold (red bar) is placed in between the two modes in the histogram, enabling visualization of either a (a) dry (left) or (b) fresh (right) leaf.
Mentions: The strong bimodality of 1529/1416 nm enabled efficient thresholding of the image for separating fresh from stressed leaves (Fig. 8). This technique has direct practical application in precision agriculture where plants with lower water content can be identified by selecting an appropriate threshold on the image histogram.

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