Cargando…

“Macrobot”: An Automated Segmentation-Based System for Powdery Mildew Disease Quantification

Managing plant diseases is increasingly difficult due to reasons such as intensifying the field production, climatic change-driven expansion of pests, redraw and loss of effectiveness of pesticides, rapid breakdown of the disease resistance in the field, and other factors. The substantial progress i...

Descripción completa

Detalles Bibliográficos
Autores principales: Lück, Stefanie, Strickert, Marc, Lorbeer, Maximilian, Melchert, Friedrich, Backhaus, Andreas, Kilias, David, Seiffert, Udo, Douchkov, Dimitar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706317/
https://www.ncbi.nlm.nih.gov/pubmed/33313559
http://dx.doi.org/10.34133/2020/5839856
_version_ 1783617129156706304
author Lück, Stefanie
Strickert, Marc
Lorbeer, Maximilian
Melchert, Friedrich
Backhaus, Andreas
Kilias, David
Seiffert, Udo
Douchkov, Dimitar
author_facet Lück, Stefanie
Strickert, Marc
Lorbeer, Maximilian
Melchert, Friedrich
Backhaus, Andreas
Kilias, David
Seiffert, Udo
Douchkov, Dimitar
author_sort Lück, Stefanie
collection PubMed
description Managing plant diseases is increasingly difficult due to reasons such as intensifying the field production, climatic change-driven expansion of pests, redraw and loss of effectiveness of pesticides, rapid breakdown of the disease resistance in the field, and other factors. The substantial progress in genomics of both plants and pathogens, achieved in the last decades, has the potential to counteract this negative trend, however, only when the genomic data is supported by relevant phenotypic data that allows linking the genomic information to specific traits. We have developed a set of methods and equipment and combined them into a “Macrophenomics facility.” The pipeline has been optimized for the quantification of powdery mildew infection symptoms on wheat and barley, but it can be adapted to other diseases and host plants. The Macrophenomics pipeline scores the visible powdery mildew disease symptoms, typically 5-7 days after inoculation (dai), in a highly automated manner. The system can precisely and reproducibly quantify the percentage of the infected leaf area with a theoretical throughput of up to 10000 individual samples per day, making it appropriate for phenotyping of large germplasm collections and crossing populations.
format Online
Article
Text
id pubmed-7706317
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher AAAS
record_format MEDLINE/PubMed
spelling pubmed-77063172020-12-10 “Macrobot”: An Automated Segmentation-Based System for Powdery Mildew Disease Quantification Lück, Stefanie Strickert, Marc Lorbeer, Maximilian Melchert, Friedrich Backhaus, Andreas Kilias, David Seiffert, Udo Douchkov, Dimitar Plant Phenomics Research Article Managing plant diseases is increasingly difficult due to reasons such as intensifying the field production, climatic change-driven expansion of pests, redraw and loss of effectiveness of pesticides, rapid breakdown of the disease resistance in the field, and other factors. The substantial progress in genomics of both plants and pathogens, achieved in the last decades, has the potential to counteract this negative trend, however, only when the genomic data is supported by relevant phenotypic data that allows linking the genomic information to specific traits. We have developed a set of methods and equipment and combined them into a “Macrophenomics facility.” The pipeline has been optimized for the quantification of powdery mildew infection symptoms on wheat and barley, but it can be adapted to other diseases and host plants. The Macrophenomics pipeline scores the visible powdery mildew disease symptoms, typically 5-7 days after inoculation (dai), in a highly automated manner. The system can precisely and reproducibly quantify the percentage of the infected leaf area with a theoretical throughput of up to 10000 individual samples per day, making it appropriate for phenotyping of large germplasm collections and crossing populations. AAAS 2020-11-05 /pmc/articles/PMC7706317/ /pubmed/33313559 http://dx.doi.org/10.34133/2020/5839856 Text en Copyright © 2020 Stefanie Lück et al. https://creativecommons.org/licenses/by/4.0/ Exclusive Licensee Nanjing Agricultural University. Distributed under a Creative Commons Attribution License (CC BY 4.0).
spellingShingle Research Article
Lück, Stefanie
Strickert, Marc
Lorbeer, Maximilian
Melchert, Friedrich
Backhaus, Andreas
Kilias, David
Seiffert, Udo
Douchkov, Dimitar
“Macrobot”: An Automated Segmentation-Based System for Powdery Mildew Disease Quantification
title “Macrobot”: An Automated Segmentation-Based System for Powdery Mildew Disease Quantification
title_full “Macrobot”: An Automated Segmentation-Based System for Powdery Mildew Disease Quantification
title_fullStr “Macrobot”: An Automated Segmentation-Based System for Powdery Mildew Disease Quantification
title_full_unstemmed “Macrobot”: An Automated Segmentation-Based System for Powdery Mildew Disease Quantification
title_short “Macrobot”: An Automated Segmentation-Based System for Powdery Mildew Disease Quantification
title_sort “macrobot”: an automated segmentation-based system for powdery mildew disease quantification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706317/
https://www.ncbi.nlm.nih.gov/pubmed/33313559
http://dx.doi.org/10.34133/2020/5839856
work_keys_str_mv AT luckstefanie macrobotanautomatedsegmentationbasedsystemforpowderymildewdiseasequantification
AT strickertmarc macrobotanautomatedsegmentationbasedsystemforpowderymildewdiseasequantification
AT lorbeermaximilian macrobotanautomatedsegmentationbasedsystemforpowderymildewdiseasequantification
AT melchertfriedrich macrobotanautomatedsegmentationbasedsystemforpowderymildewdiseasequantification
AT backhausandreas macrobotanautomatedsegmentationbasedsystemforpowderymildewdiseasequantification
AT kiliasdavid macrobotanautomatedsegmentationbasedsystemforpowderymildewdiseasequantification
AT seiffertudo macrobotanautomatedsegmentationbasedsystemforpowderymildewdiseasequantification
AT douchkovdimitar macrobotanautomatedsegmentationbasedsystemforpowderymildewdiseasequantification