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Assessing disease risk of bacterial blast in sweet cherry orchards

Florent Trouillas

UC Davis Plant Pathology

Kearney Agricultural Research and Extension

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BLOSSOM BLAST: symptoms

  • Many localized and sometime widespread events of blast in 2018, 2019, 2020, 2021, and 2023
  • New early varieties seem very susceptible
  • Royal Hazel, Royal Lynn, Coral Champagne and Chelan cvs.

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Mohamed Nouri

Mohamed Nouri

BLOSSOM BLAST: symptoms

  • Can be extremely severe
  • Requires cold and wet spring conditions

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BACTERIAL BUD FAILURE/BUD DROP:

  • In severe cases buds are killed
  • Buds drop

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BACTERIAL CANKER: symptoms

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  • Bacterial blast and canker are very active in California sweet cherry orchards

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  • Widespread events of blast in recent years

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  • Risk of blast may increase in the future with early blooms more exposed to spring frost
    • Use of early cultivars (Royal Hazel, Royal Lynn, Coral Champagne and Chelan)
    • Warming temperatures

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  • Little knowledge about the disease biology and epidemiology

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  • Need decision support tools for optimal use of antibiotic (kasugamycin, oxytetracycline) and for reducing the risk of resistance

Statement of problem - Rationale

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HYPOTHESIS:

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  • Bacterial populations of Pseudomonas syringae that overwinter in dormant buds provide the primary inoculum for blossom blast

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  • Determining the population levels of P. s.s. in dormant buds prior to bloom may help predict disease risk in orchards

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Objectives: year 3/3 of the project

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1- Our goal is to gain knowledge of blossom blast disease epidemiology

    • Bacterial population levels and dynamic in buds prior to bloom

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2- Can we assess disease risk in orchards prior to bloom?

    • Is there a correlation between population levels in bud and disease occurrence

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3- If so, can we develop risk prediction tool (Continuing proposal for 2026?)

    • Models?

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Pseudomonas syringae species characterization:

  • We sequenced 86 whole genomes of sweet cherry isolates to be used in phylogenomic analyses
  • 6 genomospecies within the P. syringae species complex were identified from symptomatic and asymptomatic cherry tissue
  • 4 putative pathogens

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Statewide surveys

Genome sequencing

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Pathogenicity studies: Canker and blast

Canker disease severity

Blast disease severity

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Outbreak of fruit rot in 2024 in orchards affected with blast in 2023:

  • Fruit rot leading to fruit drop caused by P. syringae pv. syringae (this is NOT hail damage!)

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Pathogenicity studies: Fruit rot/lesions

Field assays May 2024

At 5-days post inoculation

  • Only P. syringae pv. syringae caused fruit rot in unwounded fruits in the field

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Testing for antibiotic resistance:

  • Using genome sequence and baseline sensitivity studies data to predict drug resistance
  • 46% to 80% of P. syringae pv. syringae isolates tested had the ctpV gene which is known to confer resistance to copper
  • None of the 60 isolates from the P. syringae species complex had a gene or mutation that conferred resistance to kasugamycin
  • No isolates were resistant to kasugamycin or oxytetracycline in baseline sensitivity studies

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GENE PREDICTION

BASELINE SENSITIVTY STUDIES

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Real time PCR

with specific primers

DNA Extraction directly from plant tissue

Results within 8 hrs

PCR Assay to detect and quantify Pseudomonas syringae from buds

Asymptomatic tissues

Bacterial levels in orchards

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Using real time q-PCR assay (highly specific)

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High

Low

  • Flower buds sampled during late winter or early spring
  • Determine bacterial population levels in dormant buds

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Orchard 1

Orchard 2

Orchard 3

Orchard 4

High

Low

Disease threshold

Assess disease risk in orchards:

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Determine bacterial population temporal dynamic from buds:

Can we establish a correlation?

Bacterial population levels in bud prior to budbreak

Blast disease occurrence during cold and wet bloom

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Determine bacterial population temporal dynamic from buds:

  • What is the best sampling time or bud stage for disease risk prediction
    • From dormant buds to flowers
    • Once a month to every 2 weeks
    • 3-4 sampling locations, multiple cvs.

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Nov

Dec

Jan

Feb

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Bud swell

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Pink bud

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Pop corn

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Full bloom

Sampling times

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Orchard 1

Orchard 2

Dormant buds Oct

Dormant buds Jan

Dormant buds Dec

Flowers

  • Determine best sampling time for detecting the bacteria and assessing disease risk
  • Determine what environmental factors lead to population expansion in orchards

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Determine bacterial population temporal dynamic:

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Hanford, CA – Rainier cv.

Linden, CA – Chelan cv.

  • Determine if bacterial populations on dormant buds correlates with populations in flowers

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Assess disease risk in orchards:

Dormant buds in Jan

Flowers in March

Dormant buds in Jan

Flowers in March

Dormant buds in Dec

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Hanford, CA – Rainier cv.

Linden, CA – Chelan cv.

Disease threshold

Disease threshold

  • Determine what population level (log CFU of P.s.s) or threshold correlates with a blast event in orchards
  • Success here is weather-dependent (cold and humid conditions during bloom)

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Assess disease risk in orchards:

Dormant buds in Jan

Flowers in March

Dormant buds in Jan

Flowers in March

Dormant buds in Dec

High risk

Low risk

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  • Determine what population level (log CFU of P.s.s.) or threshold correlates with a blast event under experimental conditions
  • Inoculate plants/shoots with different concentration (log CFU) of P.s.s.
  • Place at - 4 °C for 2 hours
  • Determine the incidence/severity of blast

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Log 2 CFU

Log 3 CFU

Log 5 CFU

Log 4 CFU

Log 6 CFU

Assess disease risk in orchards:

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Expected outcomes:

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- Gain knowledge of the epidemiology of Bacterial blast

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- qPCR assay with specific primers to assess bud population of Pseudomonas syringae

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- Determine best sampling time to assess disease risk (late winter – early bloom)

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- Establish a bacterial population threshold associated with disease risk

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- Buds samples can be submitted to private or extension labs during late winter/early spring to determine disease risk

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- Model (continuing research)

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- Optimize the use and application timing of costly antibiotics (kasugamycin, oxytetracycline)

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Develop a disease risk prediction tool-Model:

Graph courtesy of Eduardo Donoso

  • Population dynamic and disease risk is modelized
  • Correlations with environmental variables (temperature, humidity, precipitations)

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Summary

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1- Hypothesis: Determining the population levels of P. s.s. in dormant buds may help predict disease risk in orchards for bacterial blast

2- Field testing to determine:

a) best sampling time

b) population threshold for disease risk

2- Building a model

(continuing research – collaboration with private company)

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Thank you!