Results from the trap nurseries Isaac K. Abuley & Jens G ...
Transcript of Results from the trap nurseries Isaac K. Abuley & Jens G ...
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Results from the trap nurseriesIsaac K. Abuley & Jens G. Hansen, Aarhus Universitet
EUROBLIGHT Conference, 2019
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Contributors
• Guillaume Saubeau, Association des Créateurs de Variétés Nouvellesde Pomme de terre (ACVNPT)
• Alison Lees, James Hutton Institute• Håvard Eikemo, NIBIO• Riinu Kiiker and Britt Puidet, Estonian University of Life Sciences
(EULS)
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In field , live virulence monitoring: trap nurseries
Aims:• Monitoring of the stability of PLB resistance in time and
space for Europe. • ”Hunting the new” – sampling / genotyping / phenotyping• Test of mega cultivars. ”How to control (with less
chemicals) new more res. cultivars”• Input to IPMBlight2.0 DSSs
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Content Late blight development in the Trap nurseries. Implementing EUCABLIGHT protocol for the Trap nursery
data Estimating the Resistance scores (1-9 scale) Conclusion remarks
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Late blight development in Denmark
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Late blight development in Estonia
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Late blight development in Scotland
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What are stability of the reference cultivars?Denmark Scotland Wales
2004
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2016
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rAU
DPC
CultivarBintje
Sarpo Mira
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Scotland
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rAU
DPC
Cultivar Bintje Sarpo Mira
• EU_13_A2 dominates the scotish P. infestans poulation• EU_6_A1 started increasin from 2009• Other factors(e.g. Agronomic?)
Could the pathogen population be responsible?
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Denmark
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rAUD
PC
Cultivar Bintje Sarpo Mira
Could the pathogen populatiob be responsible?
EU_41_A2 is dominating in DK since 2013
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Implementation of the EUCABIGHT methodolgoy
• Apparent infection rate (AIR).• Time to reach 1 and 5%• AIR is not estimated when
• Severity values < 3 in the range 0.5-99%• Slope <0 • Rsuared < 0.5
• AUDPC is not calculated if first or last reading, or two consecutive readings are missing for one or more replications
• AUDPC is converted to rAUDPC• rAUDPC = AUDPC ÷ Duration of epidemic ÷ 100
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Determining the type of resistance with Delta plot2004 data from GE, DK, WA, EE and FI
Delta a: AIR (Logistic), Cultivar tested minus Bintje
-0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4
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ta t:
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til 1
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15KurasRobijnAlphaEscortBintjeGloriaErstling
RS + RNS (or RS not overcome)
Race-non-specific (RNS) Susceptible (none)
Race Specific (RS)
Lower AIR than Bintje
Days until 1% dislater than Bintje
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Estimation of 1-9 Scale
• Implemented with the scoring formula from JHI with rAUDPC• 2 reference or anchor cutltivars
• Bintje-Susceptible reference = 3 (y2)• Sarpo Mira- resistant reference=8 (y1)
• R score (y) for a test cultivar with rAUDPC (x) is calculated as• 𝑦𝑦 = 𝑦𝑦1 + 𝑥𝑥 − 𝑥𝑥1 × 𝑦𝑦2−𝑦𝑦1
𝑥𝑥2−𝑥𝑥1
• X1 and x2 are the rAUDPC of Sarpo Mira and Bintje, respectively
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R scores in Denmark
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Variability of R scores over the years?
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Comparison of R scores in 2017
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igs
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CountryDenmark
Estonia
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R scores from JHI Versus Dowley et al. (199)Denmark Scotland Wales
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Concluding remarks• Resistance of most cultivars are not stable across countries and
between years.• Different pathogen population• Different agronomic practices.
• Resistance is based on the interaction between the pathogen and the cultivars grown in a certain region
• Collaboration with breeders and help to understand epidemiological and evolutionary mechanisms to optimize the breeding of new cultivars.
• The inclusion of more than reference of cultivars to calculate R scores.
• Development of a common Resistance grading systems.
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Concluding remarks
• In the future, deployment of resistance will be the key component in PLB DSSs
• Discuss how resistance is included most effectively in our DSSs and how we can monitor (and predict) the stability of resistance across years and regions
• Protecting R genes by augmenting with fungicide.
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IPMBlight 2.0 – partners
NAES
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Thanks for your attention