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dormant bud winter hardiness XII International Conference on - - PowerPoint PPT Presentation

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Phenotypic deconstruction of dormant bud winter hardiness XII International Conference on Grapevine Breeding and Genetics Universitde Bordeaux 7/15/2018-7/20/2018 Jason P. Londo and Alisson P. Kovaleski Cold Hardiness: phenotyping 6-8

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SLIDE 1

Phenotypic deconstruction of dormant bud winter hardiness

XII International Conference on Grapevine Breeding and Genetics

Universitéde Bordeaux 7/15/2018-7/20/2018

Jason P. Londo and Alisson P. Kovaleski

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SLIDE 2

Cold Hardiness: phenotyping 6-8 months of non-visual physiology

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10 20

Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14

Key Aspects:

Cane, Trunk, Phloem, Xylem, Cambium, Compou mpound nd Bud Cold Hardiness: minimum temperatures do not breach bud’s

  • defenses. Buds track temperature.

Dormancy is critical: must be induced to gain cold hardiness, maintained to prevent damage. Timing is everything.

Maximum Hardiness

0°C 11°C

Chilling hour accumulation

Endodormancy Ecodormancy

Temperature °C Full Chilling Insufficient Chilling

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SLIDE 3

Phenotyping dormant bud cold hardiness

0.E+00 1.E-04 2.E-04 3.E-04 4.E-04 5.E-04 6.E-04

1.9

  • 2.1
  • 6.1
  • 10.2
  • 14.3
  • 18.4
  • 22.4
  • 26.5
  • 30.5
  • 34.6

Voltage (V) Temperature (°C)

Low Temperature Exotherm (LTE)

HTE

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SLIDE 4

Tracking Bud Survival

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  • 5.00

5.00 15.00

7-Nov 7-Dec 6-Jan 5-Feb 7-Mar 6-Apr

2012-2013

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5.00 15.00

12-Nov 12-Dec 11-Jan 10-Feb 12-Mar 11-Apr

2013-2014

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  • 25.00
  • 15.00
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5.00 15.00

12-Nov 12-Dec 11-Jan 10-Feb 12-Mar

2014-2015

  • V. riparia
  • V. amurensis
  • V. vinifera
  • The type of winter determines bud cold hardiness: strong environmental component
  • Buds do not gain maximum hardiness unless the winter conditions are severe.
  • Phenotyping the entire winter is logistically challenging, we need to deconstruct the

responses.

Degrees C°

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SLIDE 5

σ T– Changes in LTE based on

mean and oscillation. Starting LTE: ~ - 12 12°C Mean 7°C 0°C oscillation Mean 7°C 3°C oscillation (4 to 10°C) Mean 7°C 5°C oscillation (2 to 12°C) Mean 2°C 0°C oscillation Mean 2°C 5°C oscillation (-3 to 7°C) LTE: ~ - 12°C LTE: ~ - 12°C LTE: ~ - 17 17°C LTE: ~ - 15 15°C LTE: ~ - 20 20°C Starting LTE: ~ - 12 12°C 3°C 5°C 5°C 8°C 0°C

Acclimation:

Gaining Cold Hardiness

Londo and Kovaleski2017

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SLIDE 6

σ T– Changes in LTE based on

mean and oscillation.

Acclimation:

Gaining Cold Hardiness

Londo and Kovaleski2017

  • V. amurensis
  • V. riparia
  • V. labrusca
  • V. cinerea
  • V. rupestris
  • V. aestivalis
  • V. vulpina

Strong Weak

  • V. vinifera

Response

σ T- Significantly different

between species.

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SLIDE 7
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4-Aug 3-Sep 3-Oct 2-Nov 2-Dec 1-Jan 31-Jan 2-Mar 1-Apr 1-May31-May

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3-Oct 2-Nov 2-Dec 1-Jan 31-Jan 2-Mar 1-Apr 1-May

Measured LTE values °C 2013-2014 43 different Vitis riparia

σ T

Comparing cold hardiness response with statistics based models No genotype effect Genotype effect

LTE °C

All V. riparia respond to temperature fluctuations in the same way. Dormancy induction may modulate max LTE?

Londo and Kovaleski 2018: in review

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SLIDE 8

Deacclimation:

Chilling and Losing Cold Hardiness

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10 20 30

17-Sep 17-Oct 16-Nov 16-Dec 15-Jan 14-Feb 16-Mar 15-Apr 15-May

LTE °C

−30 −25 −20 −15 −10 −5 10 20 30 40 50 60 70 80 90

°

360 860 1580

10 °C

−30 −25 −20 −15 −10 −5 10 20 30 40 50 60 70 80 90

Time (day) °

360 860 1580

22 °C

−30 −25 −20 −15 −10 −5

LTE (°C)

10 20 30 40 50 60 70 80 90 Days 10 20 30 40 50 60 70 80 90 Days Endodormancy Ecodormancy

Chilling accumulation increases rate of deacclimation Chilling accumulates

Kovaleski, Reisch and Londo 2018: in review

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SLIDE 9

−25 −20 −15 −10 −5 50 100 150

Time (Day) LTE (°C) T (°C)

25 50 75 100 400 800 1200 1600

Accumulated Chill

4 22

Rate (%)

Deacclimation and Chilling

Chill Accumulation ~ Deacclimation potential

Endodormancy Ecodormancy

−25 −20 −15 −10 −5

° (°C)

2 4 7 8 10 11 22

−25 −20 −15 −10 −5

° Temperature (°C)

2

Full speed depends on the airplane Rate of deacclimation depends on the temperature

Ψdeacc Deacclimation rates at different chilling and temperatures

0.0 0.5 1.0 1.5 2.0 2.5 4 8 12 16 22 30

Temperature (°C) °

1580 (97 %) 1030 (60 %) 860 (30 %) 360 ( 0 %)

ature (°C) k deacc ( °C day-1 )

Kovaleski, Reisch and Londo 2018: in review

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SLIDE 10

0.5 1 1.5 2 2.5 3 250 500 750 1000 1250 1500

  • Cab. Sauv. 10°C

Riesling 10°C Riesling 22°C

  • V. riparia 22°C

Deacclimationrate, °C/day

Chill Accumulation

  • V. amurensis 22°C
  • V. amurensis 10°C
  • V. riparia 10°C
  • Cab. Sauv. 22°C

What does this have to do with phenotyping?

Deacclimation potential is driven by chilling Deacclimation rate is temperature specific New high-throughput phenotypes for mapping populations Slope: Dormancy transition speed and Inflection Point: 50% Deacclimating potential Rate/Ratio

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SLIDE 11

Deacclimation rate in 4 mapping families at 15°C

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  • V. riparia
  • V. amurensis
  • V. cinerea
  • V. vulpina
  • V. vinifera

X

LTE °C Days in 15 °C T0 T4 T11 T21

Rate of loss °C/day

0.57 0.51 0.30 0.29

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2/5 2/10 2/15 2/20 2/25

  • V. riparia family
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2/5 2/10 2/15 2/20 2/25

  • V. vulpina family

15°C 0.29 °C/Day 15°C 0.57 °C/Day 4°C 0.07 °C/Day 4°C 0.04 °C/Day LTE °C LTE °C

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SLIDE 12
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10 20 30 40 Aug-16 Oct-16 Nov-16 Jan-17 Mar-17 Apr-17 Jun-17

Phenotypes in action: Integration of σ T andΣdeac predict cold hardiness σ T

Σdeac

Outc tcome

  • me: Breaking the curve into

two portions identifies separate phenotypes: 1) Response potential: variation at species level = σ T 2) Dormancy/deacclimation resistance: variation at genotype level = Σdeac Combining these two traits increases prediction ability and can be used to help map the traits.

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10 20 30 40 Aug-16 Oct-16 Nov-16 Jan-17 Mar-17 Apr-17 Jun-17

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SLIDE 13
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10 20 30 40 Aug-16 Oct-16 Nov-16 Jan-17 Mar-17 Apr-17 Jun-17

Phenotypes in action: Integration of σ T andΣdeac predict cold hardiness σ T

Σdeac

Outc tcome

  • me: Breaking the curve into

two portions identifies separate phenotypes: 1) Response potential: variation at species level = σ T 2) Dormancy/deacclimation resistance: variation at genotype level = Σdeac Combining these two traits increases prediction ability and can be used to help map the traits.

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SLIDE 14

Summary

  • Understanding the complexity of the cold hardiness trait:
  • Temperature variation is a strong contributor to acclimation ability
  • species level trait.
  • Dormancy induction may determine max potential LTE
  • new phenotype goal.
  • Deacclimation rate and potential is key to predicting frost risk and budbreak

– genotype level trait.

  • Development of high(er)-throughput phenotyping for cold hardiness
  • Ongoing development of a model for predicting behavior
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SLIDE 15

Thank hank you

  • u fo

for you

  • ur attention.

ention. Qu Questio stions? ns?

Researc rch Geneticist st Jason Londo Kathlee een Deys Deys Hanna Martens Bill l Srmack ck John K Keeton Bob Martens Greg Noden Bruce Reisch Bill Wilse sey Tim Martinso son Lynn Johnson Ravine ines s Wine Cellar ars Anthony Road Wine Co. Anne Fennell – SDSU Krista ta Shelli i – USDA, Parma ma PhD Candidat idate Alisso sson Koval aleski ski