1. General phenological model to characterize the
timing of flowering and veraison of Vitis
vinifera L.
Un modèle phénologique pour caractériser la floraison et la véraison de
Vitis 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. The timing of phenology is a major
quality factor in viticulture
• Too late ripening -> green and acidic wines
• Too early ripening -> unbalanced wines lacking
aromas
• Ideally, complete ripeness is achieved at the
end of the season :
– September / October Northern hemisphere
– March / April Southern hemisphere
3. Growers can influence the timing of
ripeness
• By choosing early or
late ripening
varieties
4. Adaptation of plant material and
viticultural practices to obtain the right
timing of phenology
• Can be assessed through trial and error
• Can be assessed through phenological
modelling
5. Potential applications of phenology
modelling
• Adaptation of
plant material to
climatic
variations inside
a growing region
• Adaptation of
plant material to
climate change
Source : Bois 2007
Source : meteo France
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 in
altitude
• Improved modelling techniques based on the
mathematic Metropolis algorithm and
computational power
– Phenology Modelling Platform (I. Chuine)
8. 4 models were tested
• Spring Warming (~ GDD) starting at 1st of
January
– 3 parameters
• Spring Warming with unfixed parameters
– 3 parameters
• UniFORC
– 4 parameters
• UniCHILL
– 7 parameters
9. Model performances
Model: SW SW
t0 = 1 January
UniFORC UniCHILL
Flowering
EF 0.80 0.75 0.76 0.79
RMSE 5.4 6.1 6.0 5.6
Veraison
EF 0.74 0.57 0.72 0.69
RMSE 8.0 10.2 8.2 8.7
EF = Efficiency
RMSE = Root Means Squared Error
10. Effect of base temperature (Tb) on
model performances (veraison prediction)
0
5
10
15
20
25
30
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Base temperature (°C)
RMSE(days)
-2,5
-2
-1,5
-1
-0,5
0
0,5
1
EF
RMSE
EF
11. Effect of t0 on model performances
(veraison prediction; Tb unfixed)
t0 (DOY)
0 20 40 60 80 100
EF
0.50
0.55
0.60
0.65
0.70
0.75
12. This new phenology model is called
Grapevine Flowering Veraison Model (GFV)
• Summation of daily average
temperatures
• Counting starts at DOY 60 (1st of
March)
• Base temperature 0°C
• Remains easy to use
13. Comparison with GDD model
Flowering Veraison
GFV model GDD model GFV model GDD model
t0 60 1 60 1
Tb 0C 10C 0C 10C
EF 0.76 0.73 0.72 0.14
RMSE 5.9 6.3 7.7 14.3
16. Portugese varieties
• We do not have a lot of data on
Portugese varieties
• We would be happy to receive phenology
data with corresponding daily climatic
data, particularly for:
– Touriga nacional
– Touriga franca
17. Work under progress
• We are currently testing the model for
ripeness
• We are also working on a classification
for a broad range of varieties (~ 100)
and we would be very hapy to include
Portugese varieties
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 precocity
of grapevine varieties
• Matching grapevine varieties to local climatic
variations
• Matching grapevine varieties to a changing climate
