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

Marcus Jansen, Sergej Bergsträsser, Simone Schmittgen, Mark Müller-Linow and Uwe Rascher
Additional contact information
Marcus Jansen: Forschungszentrum Jülich GmbH, Institut für Bio- und Geowissenschaften, IBG-2, Pflanzenwissenschaften, Wilhelm-Johnen-Straße, Jülich 52425, Germany
Sergej Bergsträsser: Forschungszentrum Jülich GmbH, Institut für Bio- und Geowissenschaften, IBG-2, Pflanzenwissenschaften, Wilhelm-Johnen-Straße, Jülich 52425, Germany
Simone Schmittgen: Forschungszentrum Jülich GmbH, Institut für Bio- und Geowissenschaften, IBG-2, Pflanzenwissenschaften, Wilhelm-Johnen-Straße, Jülich 52425, Germany
Mark Müller-Linow: Forschungszentrum Jülich GmbH, Institut für Bio- und Geowissenschaften, IBG-2, Pflanzenwissenschaften, Wilhelm-Johnen-Straße, Jülich 52425, Germany
Uwe Rascher: Forschungszentrum Jülich GmbH, Institut für Bio- und Geowissenschaften, IBG-2, Pflanzenwissenschaften, Wilhelm-Johnen-Straße, Jülich 52425, Germany

Agriculture, 2014, vol. 4, issue 2, 1-12

Abstract: 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.

Keywords: phenotyping; vegetation index; disease scoring; Cercospora beticola; resistance breeding (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/4/2/147/pdf (application/pdf)
https://www.mdpi.com/2077-0472/4/2/147/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:4:y:2014:i:2:p:147-158:d:35893

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().