Spectral signatures in the UV range can be combined with secondary plant metabolites by deep learning to characterize barley–powdery mildew interaction-Reference-Cited by-同舟云学术

Spectral signatures in the UV range can be combined with secondary plant metabolites by deep learning to characterize barley–powdery mildew interaction

Published:2021-08-07 Issue:7 Volume:70 Page:1572-1582
ISSN:0032-0862
Container-title:Plant Pathology
language:en
Short-container-title:Plant Pathol.

Author:

Brugger Anna¹^ORCID,Schramowski Patrick²,Paulus Stefan³,Steiner Ulrike¹,Kersting Kristian⁴,Mahlein Anne‐Katrin³

Affiliation:

1. University of Bonn Institute for Crop Science and Resource Conservation (INRES)—Plant Pathology Bonn Germany

2. Computer Science Department Technical University Darmstadt Darmstadt Germany

3. Institute of Sugar Beet Research Göttingen Germany

4. Computer Science Department and Centre for Cognitive Science Technical University Darmstadt Darmstadt Germany

Funder

Deutsche Forschungsgemeinschaft

Publisher

Wiley

Subject

Horticulture,Plant Science,Genetics,Agronomy and Crop Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ppa.13411

Reference55 articles.

1. The electronic absorption spectra of some coumarins. A molecular orbital treatment

2. Phenolic-storing cells: keys to programmed cell death and periderm formation in wilt disease resistance and in general defence responses in plants?

3. Gene Expression Profiles of Blumeria graminis Indicate Dynamic Changes to Primary Metabolism during Development of an Obligate Biotrophic Pathogen

4. Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range

5. Impact of compatible and incompatible barley ‐ Blumeria graminis f.sp. hordei interactions on chlorophyll fluorescence parameters;Brugger A.;Journal of Plant Diseases and Protection,2018

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