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| Hauptseite > Publikationsdatenbank > Observation of plant–pathogen interaction by simultaneous hyperspectral imaging reflection and transmission measurements |
| Hauptseite > Publikationsdatenbank > Observation of plant–pathogen interaction by simultaneous hyperspectral imaging reflection and transmission measurements |
| Journal Article | FZJ-2017-01496 |
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2017
CSIRO Publ.
Collingwood, Victoria
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Please use a persistent id in citations: doi:10.1071/FP16127
Abstract: Hyperspectral imaging sensors are valuable tools for plant disease detection and plant phenotyping. Reflectance properties are influenced by plant pathogens and resistance responses, but changes of transmission characteristics of plants are less described. In this study we used simultaneously recorded reflectance and transmittance imaging data of resistant and susceptible barley genotypes that were inoculated with Blumeria graminis f. sp. hordei to evaluate the added value of imaging transmission, reflection and absorption for characterisation of disease development. These datasets were statistically analysed using principal component analysis, and compared with visual and molecular disease estimation. Reflection measurement performed significantly better for early detection of powdery mildew infection, colonies could be detected 2 days before symptoms became visible in RGB images. Transmission data could be used to detect powdery mildew 2 days after symptoms becoming visible in reflection based RGB images. Additionally distinct transmission changes occurred at 580–650 nm for pixels containing disease symptoms. It could be shown that the additional information of the transmission data allows for a clearer spatial differentiation and localisation between powdery mildew symptoms and necrotic tissue on the leaf then purely reflectance based data. Thus the information of both measurement approaches are complementary: reflectance based measurements facilitate an early detection, and transmission measurements provide additional information to better understand and quantify the complex spatio-temporal dynamics of plant-pathogen interactions.
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