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

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

Growers can influence the timing of ripeness

• By choosing early or late ripening varieties

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

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

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 (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)

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

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 = EfficiencyRMSE = Root Means Squared Error

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

(day

s)

-2,5

-2

-1,5

-1

-0,5

0

0,5

1

EF

RMSEEF

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

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

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

Model validation for 50% floweringa) Cabernet franc

Observation (DOY)

100 120 140 160 180 200 220 240

Pre

dict

ion

(DO

Y)

100

120

140

160

180

200

220

240 b) Cabernet-Sauvignon

Observation (DOY)

100 120 140 160 180 200 220 240

Pre

dict

ion

(DO

Y)

100

120

140

160

180

200

220

240

c) Chardonnay

Observation (DOY)

100 120 140 160 180 200 220 240

Pred

ictio

n (D

OY)

100

120

140

160

180

200

220

240 f) Merlot

Observation (DOY)

100 120 140 160 180 200 220 240

Pre

dict

ion

(DO

Y)

100

120

140

160

180

200

220

240

Classification for veraison

F* = thermal summation at veraison

Variety F*Chasselas 2374Pinot noir 2511Sauvignon blanc 2528Chardonnay 2547Riesling 2590Syrah 2601Merlot 2636Cabernet-Sauvignon 2689Cabernet franc 2692Grenache 2761Ugni blanc 2799

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

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

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