Literature DB >> 28665761

Spectral Patterns Reveal Early Resistance Reactions of Barley Against Blumeria graminis f. sp. hordei.

Matheus Thomas Kuska1, Anna Brugger1, Stefan Thomas1, Mirwaes Wahabzada1, Kristian Kersting1, Erich-Christian Oerke1, Ulrike Steiner1, Anne-Katrin Mahlein1.   

Abstract

Differences in early plant-pathogen interactions are mainly characterized by using destructive methods. Optical sensors are advanced techniques for phenotyping host-pathogen interactions on different scales and for detecting subtle plant resistance responses against pathogens. A microscope with a hyperspectral camera was used to study interactions between Blumeria graminis f. sp. hordei and barley (Hordeum vulgare) genotypes with high susceptibility or resistance due to hypersensitive response (HR) and papilla formation. Qualitative and quantitative assessment of pathogen development was used to explain changes in hyperspectral signatures. Within 48 h after inoculation, genotype-specific changes in the green and red range (500 to 690 nm) and a blue shift of the red-edge inflection point were observed. Manual analysis indicated resistance-specific reflectance patterns from 1 to 3 days after inoculation. These changes could be linked to host plant modifications depending on individual host-pathogen interactions. Retrospective analysis of hyperspectral images revealed spectral characteristics of HR against B. graminis f. sp. hordei. For early HR detection, an advanced data mining approach localized HR spots before they became visible on the RGB images derived from hyperspectral imaging. The link among processes during pathogenesis and host resistance to changes in hyperspectral signatures provide evidence that sensor-based phenotyping is suitable to advance time-consuming and cost-expensive visual rating of plant disease resistances.

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Year:  2017        PMID: 28665761     DOI: 10.1094/PHYTO-04-17-0128-R

Source DB:  PubMed          Journal:  Phytopathology        ISSN: 0031-949X            Impact factor:   4.025


  6 in total

1.  Discovering coherency of specific gene expression and optical reflectance properties of barley genotypes differing for resistance reactions against powdery mildew.

Authors:  Matheus Thomas Kuska; Jan Behmann; Mahsa Namini; Erich-Christian Oerke; Ulrike Steiner; Anne-Katrin Mahlein
Journal:  PLoS One       Date:  2019-03-19       Impact factor: 3.240

2.  Plant disease identification using explainable 3D deep learning on hyperspectral images.

Authors:  Koushik Nagasubramanian; Sarah Jones; Asheesh K Singh; Soumik Sarkar; Arti Singh; Baskar Ganapathysubramanian
Journal:  Plant Methods       Date:  2019-08-21       Impact factor: 4.993

Review 3.  Turfgrass Disease Diagnosis: Past, Present, and Future.

Authors:  Tammy Stackhouse; Alfredo D Martinez-Espinoza; Md Emran Ali
Journal:  Plants (Basel)       Date:  2020-11-11

4.  Digital plant pathology: a foundation and guide to modern agriculture.

Authors:  Matheus Thomas Kuska; René H J Heim; Ina Geedicke; Kaitlin M Gold; Anna Brugger; Stefan Paulus
Journal:  J Plant Dis Prot (2006)       Date:  2022-04-28       Impact factor: 1.847

5.  Quantitative assessment of disease severity and rating of barley cultivars based on hyperspectral imaging in a non-invasive, automated phenotyping platform.

Authors:  Stefan Thomas; Jan Behmann; Angelina Steier; Thorsten Kraska; Onno Muller; Uwe Rascher; Anne-Katrin Mahlein
Journal:  Plant Methods       Date:  2018-06-08       Impact factor: 4.993

6.  Screening of Barley Resistance Against Powdery Mildew by Simultaneous High-Throughput Enzyme Activity Signature Profiling and Multispectral Imaging.

Authors:  Matheus T Kuska; Jan Behmann; Dominik K Großkinsky; Thomas Roitsch; Anne-Katrin Mahlein
Journal:  Front Plant Sci       Date:  2018-07-23       Impact factor: 5.753

  6 in total

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