General phenological model to characterize thetiming of flowering and veraison of Vitisvinifera L.Un modèle phénologique p...
The timing of phenology is a majorquality factor in viticulture• Too late ripening -> green and acidic wines• Too early ri...
Growers can influence the timing ofripeness• By choosing early orlate ripeningvarieties
Adaptation of plant material andviticultural practices to obtain the righttiming of phenology• Can be assessed through tri...
Potential applications of phenologymodelling• Adaptation ofplant material toclimaticvariations insidea growing region• Ada...
Existing phenological models• Growing Degree Days (Winkler)• Huglin Index
Existing models can be improved• Larger data bases– In this study 4030 phenology observations from :• 123 locations (Franc...
4 models were tested• Spring Warming (~ GDD) starting at 1st ofJanuary– 3 parameters• Spring Warming with unfixed paramete...
Model performancesModel: SW SWt0 = 1 JanuaryUniFORC UniCHILLFloweringEF 0.80 0.75 0.76 0.79RMSE 5.4 6.1 6.0 5.6VeraisonEF ...
Effect of base temperature (Tb) onmodel performances (veraison prediction)0510152025300 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1...
Effect of t0 on model performances(veraison prediction; Tb unfixed)t0 (DOY)0 20 40 60 80 100EF0.500.550.600.650.700.75
This new phenology model is calledGrapevine Flowering Veraison Model (GFV)• Summation of daily averagetemperatures• Counti...
Comparison with GDD modelFlowering VeraisonGFV model GDD model GFV model GDD modelt0 60 1 60 1Tb 0C 10C 0C 10CEF 0.76 ...
Model validation for 50% floweringa) Cabernet francObservation (DOY)100 120 140 160 180 200 220 240Prediction(DOY)10012014...
Classification for veraisonF* = thermal summation at veraisonVariety F*Chasselas 2374Pinot noir 2511Sauvignon blanc 2528Ch...
Portugese varieties• We do not have a lot of data onPortugese varieties• We would be happy to receive phenologydata with c...
Work under progress• We are currently testing the model forripeness• We are also working on a classificationfor a broad ra...
Conclusion• GFV phenology model– easy to use– performs better than existing models– Generic model across varieties• t0 : D...
Upcoming SlideShare
Loading in...5
×

Gdd for flowering verasion new model van leeuwen

198

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
198
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
4
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Gdd for flowering verasion new model van leeuwen

  1. 1. General phenological model to characterize thetiming of flowering and veraison of Vitisvinifera L.Un modèle phénologique pour caractériser la floraison et la véraison deVitis vinifera L.Parker A., García de Cortázar-Atauri I.,van Leeuwen C. and Chuine I.Australian Journal of Grape and Wine Research 17, 206-216, 2011
  2. 2. The timing of phenology is a majorquality factor in viticulture• Too late ripening -> green and acidic wines• Too early ripening -> unbalanced wines lackingaromas• Ideally, complete ripeness is achieved at theend of the season :– September / October Northern hemisphere– March / April Southern hemisphere
  3. 3. Growers can influence the timing ofripeness• By choosing early orlate ripeningvarieties
  4. 4. Adaptation of plant material andviticultural practices to obtain the righttiming of phenology• Can be assessed through trial and error• Can be assessed through phenologicalmodelling
  5. 5. Potential applications of phenologymodelling• Adaptation ofplant material toclimaticvariations insidea growing region• Adaptation ofplant material toclimate changeSource : Bois 2007Source : meteo France
  6. 6. Existing phenological models• Growing Degree Days (Winkler)• Huglin Index
  7. 7. Existing models can be improved• Larger data bases– In this study 4030 phenology observations from :• 123 locations (France, Switzerland, Italy, Greece)• 81 varieties• 48 vintages• Meteo data < 5 km in distance ; < 100 m inaltitude• Improved modelling techniques based on themathematic Metropolis algorithm andcomputational power– Phenology Modelling Platform (I. Chuine)
  8. 8. 4 models were tested• Spring Warming (~ GDD) starting at 1st ofJanuary– 3 parameters• Spring Warming with unfixed parameters– 3 parameters• UniFORC– 4 parameters• UniCHILL– 7 parameters
  9. 9. Model performancesModel: SW SWt0 = 1 JanuaryUniFORC UniCHILLFloweringEF 0.80 0.75 0.76 0.79RMSE 5.4 6.1 6.0 5.6VeraisonEF 0.74 0.57 0.72 0.69RMSE 8.0 10.2 8.2 8.7EF = EfficiencyRMSE = Root Means Squared Error
  10. 10. Effect of base temperature (Tb) onmodel performances (veraison prediction)0510152025300 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Base temperature (°C)RMSE(days)-2,5-2-1,5-1-0,500,51EFRMSEEF
  11. 11. Effect of t0 on model performances(veraison prediction; Tb unfixed)t0 (DOY)0 20 40 60 80 100EF0.500.550.600.650.700.75
  12. 12. This new phenology model is calledGrapevine Flowering Veraison Model (GFV)• Summation of daily averagetemperatures• Counting starts at DOY 60 (1st ofMarch)• Base temperature 0°C• Remains easy to use
  13. 13. Comparison with GDD modelFlowering VeraisonGFV model GDD model GFV model GDD modelt0 60 1 60 1Tb 0C 10C 0C 10CEF 0.76 0.73 0.72 0.14RMSE 5.9 6.3 7.7 14.3
  14. 14. Model validation for 50% floweringa) Cabernet francObservation (DOY)100 120 140 160 180 200 220 240Prediction(DOY)100120140160180200220240 b) Cabernet-SauvignonObservation (DOY)100 120 140 160 180 200 220 240Prediction(DOY)100120140160180200220240c) ChardonnayObservation (DOY)100 120 140 160 180 200 220 240Prediction(DOY)100120140160180200220240 f) MerlotObservation (DOY)100 120 140 160 180 200 220 240Prediction(DOY)100120140160180200220240
  15. 15. Classification for veraisonF* = thermal summation at veraisonVariety F*Chasselas 2374Pinot noir 2511Sauvignon blanc 2528Chardonnay 2547Riesling 2590Syrah 2601Merlot 2636Cabernet-Sauvignon 2689Cabernet franc 2692Grenache 2761Ugni blanc 2799
  16. 16. Portugese varieties• We do not have a lot of data onPortugese varieties• We would be happy to receive phenologydata with corresponding daily climaticdata, particularly for:– Touriga nacional– Touriga franca
  17. 17. Work under progress• We are currently testing the model forripeness• We are also working on a classificationfor a broad range of varieties (~ 100)and we would be very hapy to includePortugese varieties
  18. 18. Conclusion• GFV phenology model– easy to use– performs better than existing models– Generic model across varieties• t0 : DOY 60• Tb : 0°C• Powerful tool for the classification of the precocityof grapevine varieties• Matching grapevine varieties to local climaticvariations• Matching grapevine varieties to a changing climate
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×