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DataPlant

Datafusion in plantphenotyping for Cercospora control in sugarbeet

Runtime
1.3.2017 - 30.9.2019

In this project, data on Cercospora infected sugar beet plants, acquired by different sensor types, will be correlated. The project is aiming for an automated assessment of the degree of infection.

Healthy leafs are a key factor for successful crop production. For plant breeding, leaf diseases have to be detected and quantified to ensure a reliable detection of crop resistances. Additionally, knowledge on the degree of infection is important for counteracting the negative effects of diseases on crop yield effectively.

Cercospora, a pathogenic fungus, is the most important leaf disease of sugar beet in Europe, causing yield losses of up to 50% in case of strongly infected populations. In this project, data on Cercospora infected sugar beet plants, acquired by different sensor types will be correlated. FZ Jülich will provide phenotypical data on infected plants using spectral methods as well as chlorophyll fluorescence techniques. Ultimately, DataPlant is aiming for an automated assessment of the degree of infection of sugar beet plants with Cercospora.

 Cercospora infection on sugar beet


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