Grapevine flowering of the Marlborough Region: Sauvignon blanc

Grapevine flowering of the Marlborough Region: Sauvignon blanc Amber K. PARKER, Tobias SCHULMANN, Andrew STURMAN, Robert AGNEW, Peyman ZAWAR-REZA, Marwan KATURJI, Eila GENDIG and Michael TROUGHT

Aim To model the time of flowering for Sauvignon blanc within the Marlborough region

The importance of flowering Use as start point to predict for veraison and maturity Temperatures at this time are important for: yield estimation bunch architecture Management decisions occur at this time: yield estimation thinning

Aim To model the time of flowering for Sauvignon blanc within the Marlborough region

Modelling flowering Temperature key driver

Modelling flowering Temperature key driver Need to capture: Spatial variation

Modelling flowering Temperature key driver Need to capture: Spatial variation Temporal variation (seasons/vintages) To convey regional variation within space and time

Aim To model the time of flowering for Sauvignon blanc within the Marlborough region

Methods A model to test: Grapevine Flowering Veraison Model (GFV) 1 Start date = 29 th August Accumulated GDD base 0 o C 1 Parker et al. (2011) Australian Journal of Grape and Wine Research 17, 206-216.

Characterisation of thermal time to flowering for Sauvignon blanc - GFV model Sauvignon blanc Thermal time (Base 0 C) from 29 th August until flowering F* = 1282 C.d. Parker et al. (2013) Agricultural and Forest Meteorology 180, 249-264. Use this value to determine date of flowering in new sites using temperature data

Methods A model to test: GFV Sauvignon blanc F* = 1282 C.d. Temperature data at new locations to predict time of flowering Automated weather stations (AWS) Weather Research and Forecasting (WRF) model data

Temperature and phenology networks Automated weather stations Phenology sites

100 Methods Earlier sites -2013 Flowering (%) 80 60 40 20 0 25 Nov 30 Nov 5 Dec 10 Dec 15 Dec 20 Dec Date RPC MRL SCR OYB VIL BOK SEA SED WRV WAI TOH Coastal, middle and lower Wairau

100 Middle group - 2013 Flowering (%) 80 60 40 20 0 25 Nov 30 Nov 5 Dec 10 Dec 15 Dec 20 Dec Date RPC MRL SCR OYB VIL BOK SEA SED WRV WAI TOH Two sites in Awatere Valley

100 Late sites - 2013 Flowering (%) 80 60 40 20 0 25 Nov 30 Nov 5 Dec 10 Dec 15 Dec 20 Dec Date RPC MRL SCR OYB VIL BOK SEA SED WRV WAI TOH Upper Wairau and Awatere Valley, Waihopai Valley

How do these observations compare to model predictions?

Day of the year Historical data versus AWS data 21/12 16/12 11/12 6/12

Predictions versus observations - 2013 AWS/GFV WRF/GFV Weather Research Forecasting Model + GFV model = predictions within a few days of observations

Extend predictions to a region-wide level Isochrone map of the date on which accumulated degree day values derived from the Grapevine Flowering Véraison model achieved F* = 1282 across the Marlborough region, based on the Weather Research and Forecasting model output at 1 km spatial resolution. Poster at: Terroir Congress, Hungary, 2014. A. K. Parker, T.Schulmann, A. Sturman, R.Agnew, P. Zawar-Reza, M. Katurji, E. Gendig, M.Trought

Summary Expansion of phenology network in Marlborough Good agreement between GFV/WRF output and observations for sites tested Future work: Test other sites Other phenological stages Modelling developmental time (i.e. start date = budburst)

Acknowledgements MPI for funding the project Development of advanced weather and climate modelling tools to help vineyard regions adapt to climate change (UOC30915) The New Zealand Grape and Wine Research Programme a joint initiative between PFR and NZ Winegrowers Marlborough Research Centre for historical data collection French and Europe collaborators and co-authors from GFV model development work www.plantandfood.co.nz amber.parker@plantandfood.co.nz