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Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot

Botrytis bunch rot is one of the economically most important fungal diseases in viticulture (aside from powdery mildew and downy mildew). So far, no active defense mechanisms and resistance loci against the necrotrophic pathogen are known. Since long, breeders are mostly selecting phenotypically for...

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Autores principales: Herzog, Katja, Schwander, Florian, Kassemeyer, Hanns-Heinz, Bieler, Evi, Dürrenberger, Markus, Trapp, Oliver, Töpfer, Reinhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866247/
https://www.ncbi.nlm.nih.gov/pubmed/35222454
http://dx.doi.org/10.3389/fpls.2021.808365
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author Herzog, Katja
Schwander, Florian
Kassemeyer, Hanns-Heinz
Bieler, Evi
Dürrenberger, Markus
Trapp, Oliver
Töpfer, Reinhard
author_facet Herzog, Katja
Schwander, Florian
Kassemeyer, Hanns-Heinz
Bieler, Evi
Dürrenberger, Markus
Trapp, Oliver
Töpfer, Reinhard
author_sort Herzog, Katja
collection PubMed
description Botrytis bunch rot is one of the economically most important fungal diseases in viticulture (aside from powdery mildew and downy mildew). So far, no active defense mechanisms and resistance loci against the necrotrophic pathogen are known. Since long, breeders are mostly selecting phenotypically for loose grape bunches, which is recently the most evident trait to decrease the infection risk of Botrytis bunch rot. This study focused on plant phenomics of multiple traits by applying fast sensor technologies to measure berry impedance (Z(REL)), berry texture, and 3D bunch architecture. As references, microscopic determined cuticle thickness (MS(CT)) and infestation of grapes with Botrytis bunch rot were used. Z(REL) hereby is correlated to grape bunch density OIV204 (r = −0.6), cuticle thickness of berries (r = 0.61), mean berry diameter (r = −0.63), and Botrytis bunch rot (r = −0.7). However, no correlation between Z(REL) and berry maturity or berry texture was observed. In comparison to the category of traditional varieties (mostly susceptible), elite breeding lines show an impressive increased Z(REL) value (+317) and a 1-μm thicker berry cuticle. Quantitative trait loci (QTLs) on LGs 2, 6, 11, 15, and 16 were identified for Z(REL) and berry texture explaining a phenotypic variance of between 3 and 10.9%. These QTLs providing a starting point for the development of molecular markers. Modeling of Z(REL) and berry texture to predict Botrytis bunch rot resilience revealed McFadden R(2) = 0.99. Taken together, this study shows that in addition to loose grape bunch architecture, berry diameter, Z(REL), and berry texture values are probably additional parameters that could be used to identify and select Botrytis-resilient wine grape varieties. Furthermore, grapevine breeding will benefit from these reliable methodologies permitting high-throughput screening for additional resilience traits of mechanical and physical barriers to Botrytis bunch rot. The findings might also be applicable to table grapes and other fruit crops like tomato or blueberry.
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spelling pubmed-88662472022-02-25 Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot Herzog, Katja Schwander, Florian Kassemeyer, Hanns-Heinz Bieler, Evi Dürrenberger, Markus Trapp, Oliver Töpfer, Reinhard Front Plant Sci Plant Science Botrytis bunch rot is one of the economically most important fungal diseases in viticulture (aside from powdery mildew and downy mildew). So far, no active defense mechanisms and resistance loci against the necrotrophic pathogen are known. Since long, breeders are mostly selecting phenotypically for loose grape bunches, which is recently the most evident trait to decrease the infection risk of Botrytis bunch rot. This study focused on plant phenomics of multiple traits by applying fast sensor technologies to measure berry impedance (Z(REL)), berry texture, and 3D bunch architecture. As references, microscopic determined cuticle thickness (MS(CT)) and infestation of grapes with Botrytis bunch rot were used. Z(REL) hereby is correlated to grape bunch density OIV204 (r = −0.6), cuticle thickness of berries (r = 0.61), mean berry diameter (r = −0.63), and Botrytis bunch rot (r = −0.7). However, no correlation between Z(REL) and berry maturity or berry texture was observed. In comparison to the category of traditional varieties (mostly susceptible), elite breeding lines show an impressive increased Z(REL) value (+317) and a 1-μm thicker berry cuticle. Quantitative trait loci (QTLs) on LGs 2, 6, 11, 15, and 16 were identified for Z(REL) and berry texture explaining a phenotypic variance of between 3 and 10.9%. These QTLs providing a starting point for the development of molecular markers. Modeling of Z(REL) and berry texture to predict Botrytis bunch rot resilience revealed McFadden R(2) = 0.99. Taken together, this study shows that in addition to loose grape bunch architecture, berry diameter, Z(REL), and berry texture values are probably additional parameters that could be used to identify and select Botrytis-resilient wine grape varieties. Furthermore, grapevine breeding will benefit from these reliable methodologies permitting high-throughput screening for additional resilience traits of mechanical and physical barriers to Botrytis bunch rot. The findings might also be applicable to table grapes and other fruit crops like tomato or blueberry. Frontiers Media S.A. 2022-02-10 /pmc/articles/PMC8866247/ /pubmed/35222454 http://dx.doi.org/10.3389/fpls.2021.808365 Text en Copyright © 2022 Herzog, Schwander, Kassemeyer, Bieler, Dürrenberger, Trapp and Töpfer. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Herzog, Katja
Schwander, Florian
Kassemeyer, Hanns-Heinz
Bieler, Evi
Dürrenberger, Markus
Trapp, Oliver
Töpfer, Reinhard
Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot
title Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot
title_full Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot
title_fullStr Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot
title_full_unstemmed Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot
title_short Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot
title_sort towards sensor-based phenotyping of physical barriers of grapes to improve resilience to botrytis bunch rot
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866247/
https://www.ncbi.nlm.nih.gov/pubmed/35222454
http://dx.doi.org/10.3389/fpls.2021.808365
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