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Open AccessArticle

Non-Invasive Spectral Phenotyping Methods can Improve and Accelerate Cercospora Disease Scoring in Sugar Beet Breeding

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Forschungszentrum Jülich GmbH, Institut für Bio- und Geowissenschaften, IBG-2, Pflanzenwissenschaften, Wilhelm-Johnen-Straße, Jülich 52425, Germany
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Rheinische Friedrich-Wilhelms-Universität Bonn, Regina-Pacis-Weg 3, Bonn 53113, Germany
*
Author to whom correspondence should be addressed.
Agriculture 2014, 4(2), 147-158; https://doi.org/10.3390/agriculture4020147
Received: 27 March 2014 / Revised: 25 April 2014 / Accepted: 29 April 2014 / Published: 8 May 2014
Breeding for Cercospora resistant sugar beet cultivars requires field experiments for testing resistance levels of candidate genotypes in conditions that are close to agricultural cultivation. Non-invasive spectral phenotyping methods can support and accelerate resistance rating and thereby speed up breeding process. In a case study, experimental field plots with strongly infected beet genotypes of different resistance levels were measured with two different spectrometers. Vegetation indices were calculated from measured wavelength signature to determine leaf physiological status, e.g., greenness with the Normalized Differenced Vegetation Index (NDVI), leaf water content with the Leaf Water Index (LWI) and Cercospora disease severity with the Cercospora Leaf Spot Index (CLSI). Indices values correlated significantly with visually scored disease severity, thus connecting the classical breeders’ scoring approach with advanced non-invasive technology. View Full-Text
Keywords: phenotyping; vegetation index; disease scoring; Cercospora beticola; resistance breeding phenotyping; vegetation index; disease scoring; Cercospora beticola; resistance breeding
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Jansen, M.; Bergsträsser, S.; Schmittgen, S.; Müller-Linow, M.; Rascher, U. Non-Invasive Spectral Phenotyping Methods can Improve and Accelerate Cercospora Disease Scoring in Sugar Beet Breeding. Agriculture 2014, 4, 147-158.

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