Varietal phenology and maturation in the grapevine: its interaction with leaf area to fruit weight manipulations

Varietal phenology and maturation in the grapevine: CHRISTCHURCH NEW ZEALAND www.lincoln.ac.nz its interaction with leaf area to fruit weight manipulations Amber Parker Email: amber.parker@plantandfood.co.nz Supervisor: Dr Rainer Hofmann Co-supervisor: Dr. Michael Trought External Co-supervisor: Prof. Cornelis van Leeuwen Assoc. Supervisor: Prof. Don Kulasiri Romeo Bragato Trust

Overview Background Assessing phenology LA: FW manipulations Application Summary: Key Findings and Future

Varietal phenology and maturation in the grapevine: its interaction with leaf area to fruit weight manipulations Genetic : Varieties

Varietal phenology and maturation in the grapevine: its interaction with leaf area to fruit weight manipulations VARIETAL PHENOLOGY AND BERRY MATURATION FLOWERING FRUITSET VERAISON BERRY MATURATION Soluble solids (SS)/sugar TA ph Berry weight MATURITY/ 200g/L SUGAR HARVEST

Varietal phenology and maturation in the grapevine: its interaction with leaf area to fruit weight manipulations Management : LA:FW ratio 6 main leaves per shoot 12 main leaves per shoot

Phenology and maturation Management : LA:FW ratio Varietal phenology and maturity Environment : Temperature Genetic : Varieties

Phenology and maturation Management : LA:FW ratio CHO manipulations: Crop and leaf removal Number of canes Nodes per cane Training system Irrigation Vine nutrition Soil Choices: Development Target berry composition Rainfall Solar radiation and/or UV Frost Environment : Temperature Genetic : Varieties Rootstock Clones

Phenology and maturation Management : LA:FW ratio In season manipulation to shift phenology Varietal phenology and maturity Key factor driving phenology Environment : Temperature Genetic : Varieties Alternate choices with different phenological timing

Q1: What are the differences in phenology and berry composition between varieties as a function of thermal time? Objective: Compare varieties and create a classification of different varieties

Q1: What are the differences in phenology and berry composition between varieties as a function of thermal time? Database establishment Test different phenological models characterise each variety for the selected model

A word on the M word... GDD = A MODEL Environment : Temperature Grapevine Flowering Veraison Model (GFV) (Parker et al. 2011) Linear summation of daily average temperatures Start date = 60 th DOY (Northern hemisphere) Base temperature = 0 C

A word on the M word... GFV AVERAGE DAILY TEMP> 0⁰C ADD IT! F* 60 th DOY (Northern Hemisphere) F* F* F* = ⁰C.d VARIETAL PHENOLOGY AND BERRY MATURATION FLOWERING VERAISON 200g/L SUGAR 242 DOY = 30 August ~ 1 September

Q1: What are the differences in phenology and berry composition between varieties as a function of thermal time? Sugar concentrations: - one element of berry composition -proxy measurement of maturity Tested: - 7 different phenological models - Hourly Average/Daily Average/ Daily Maximum Temperatures GFV and Sigmoid options 35 varieties characterised 200g/L sugar

Q1: What are the differences in phenology and berry composition between varieties as a function of thermal time? Summary of findings Testing of a phenological model on the largest varietal database for Vitis vinifera L. ~ 120 sites, - 1960-2010 Largest variety classification to date -Flowering: 2215 observations, 95 varieties -Veraison: 2270 observations, 104 varieties -200g/L sugar: 560 observations, 35 varieties

Q1: What are the differences in phenology and berry composition between varieties as a function of thermal time? Summary of findings Methodology - Large scale analysis (quantity of data) Spatial and temporal variation Database size - Uncertainty assessment (Confidence Intervals)

TEMPERATURE Key findings Classifications using the GFV model Applications: - Defined typical timing for each variety -Varietal choice - New sites - Relevance with climate change - VARIETAL PHENOLOGY AND BERRY MATURATION FLOWERING 95 varieties classified VERAISON 104 varieties classified 200g/L SUGAR 35 varieties classified 1120 C.d 1411 C.d 2286 C.d VERAISON 2941 C.d 2876 C.d 200g/L SUGAR 3720 C.d Early Late Early Late Early Late Meunier Semebat Garanoir Semebat Pinot noir Sciaccarello

TEMPERATURE Veraison and soluble solids relationship FLOWERING GFV model 95 varieties classified 1120 C.d 1411 C.d Early Late Meunier Semebat VARIETAL PHENOLOGY AND BERRY MATURATION FRUITSET VERAISON BERRY MATURATION Soluble solids (SS)/sugar TA ph Berry weight 200g/L SUGAR Sigmoid/GFV model GFV model : 35 varieties classified 2876 C.d 3720 C.d Early Late Pinot noir Sciaccarello - Relationship of different veraison measurements - Soluble solids (SS)? - SS value(s) =alternative measure for modelling - Tested : elasticity, deformability, softness, colour - Looked at individual and population measurements

TEMPERATURE New key findings for characterising veraison VERAISON ASSESSMENT Elasticity Deformability Softness (50%) Colour(50%) Pinot noir/sauvignon blanc Pinot noir 4.8 Brix 7 Brix 8.1 Brix 9.3 Brix FLOWERING GFV model 95 varieties classified 1120 C.d 1411 C.d Early Late Meunier Semebat VARIETAL PHENOLOGY AND BERRY MATURATION FRUITSET VERAISON BERRY MATURATION Soluble solids (SS)/sugar TA ph Berry weight 200g/L SUGAR Sigmoid/GFV model GFV model : 35 varieties classified 2876 C.d 3720 C.d Early Late Pinot noir Sciaccarello -Characterisation of different veraison measurements in relation to SS

Q2: How does the LA: FW ratio influence varietal phenology, timing and evolution of berry composition? Remove leaves Leave crop A Leave leaves Drop crop B

Leaf area / Fruit weight ratio Leaving/ Removing leaves Leaving/ Removing crop 1. Relative importance of leaf vs. crop removal? 2. Advance/delay veraison? 3. Alter soluble solids accumulation (rate and quantity)? 4. Do varieties behave the same at the same LA/FW?

Experiment 1 : LEAF vs CROP removal Veraison Harvest Fruitset Flowering Budburst 12 leaves 6 leaves Full crop Full crop 50% crop removed 50% crop removed 75% crop removed 75% crop removed Equivalent ratios achieved by different methods

In the field...

In the field...

In the field...

Key findings: veraison -Trimming at fruitset caused a greater delay than altering yield - Duration for PN 6L Full crop longer Veraison (% softness) SB: 2010-11 100 80 60 40 20 0 6 leaves 100% crop 6 leaves 50% crop removal 12 leaves 100% crop 12 leaves 50% crop removal 20 40 60 80 100 DOY

Key findings: Soluble solids Both LA and FW important! - Both stages of fruitset and veraison: - LA = Slower Rate -Crop removal = Faster rate -Rates slowest 6 leaves full crop SB: 2010-11 Soluble solids ( o Brix) 24 22 20 18 16 14 12 10 8 6 4 6 leaves 100% crop 6 leaves 50% crop removal 12 leaves 100% crop 12 leaves 50% crop removal 20 30 40 50 60 70 80 90 100 110 DOY

Key findings: Soluble solids SB: 2010-11 -Same ratio, similar response ONSET + RATES dynamic understanding Soluble solids ( o Brix) 24 22 20 18 16 14 12 10 8 6 6 leaves 100% crop 6 leaves 50% crop removal 12 leaves 100% crop 12 leaves 50% crop removal 4 20 30 40 50 60 70 80 90 100 110 DOY

Key findings 45 3.2 Titratable acidity (g/l) 40 35 30 25 20 15 6 leaves 100% crop 6 leaves 50% crop removal 12 leaves 100% crop 12 leaves 50% crop removal ph 3.0 2.8 2.6 10 2.4 20 30 40 50 60 70 80 90 100 110 DOY 20 30 40 50 60 70 80 90 100 110 DOY Other measured parameters unchanged Altering the relative balance of metabolites by LA: FW manipulations

Q3: To what extent do varieties behave in a similar way at the same LA: FW ratio? - Veraison: delays due to decreased LA consistent for both varieties - PN: duration slower 6L full crop - SB: greater effect of crop removal - SS accumulation: Same rates for same treatments -Next: - Define limits and thresholds - characterise the response as a continuum

Experiment 2 : Extreme LA:FW Veraison Harvest Fruitset Flowering Budburst

Experiment 2 : Extreme LA:FW LEAVES 3 6 9 12 15 18 Full crop CROP 50% crop removed LEAVES 3 6 9 12 15 18 Laterals Present Absent - Vines defoliated at harvest and actual leaf area measured - Pinot noir (PN) and Sauvignon blanc (SB)

Key findings 50% crop removal -Advance DOY 8 Brix (SB) SB 2010-2011 26 b) -Reaches plateau SS 100% and 50% crop = continuum + Laterals -Advance DOY 8 Brix (SB) -Both varieties: - Rates SS accumulation - Harvest SS Soluble solids at harvest ( o Brix) 24 22 20 18 16 14 12 10 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 LA: FW (m 2 /kg) 100% crop, no laterals 50% crop, no laterals 100% crop, laterals

Varietal differences: Key findings 50% crop removal Findings: -Response form is same -Plateau = variety dependent -Defines conditions where varietal response altered by management (LA:FW) GFV summation at DOY = 8 o Brix 2900 2800 2700 2600 2500 2400 2300 2200 2610 2237 Pinot noir Sauvignon blanc 125 2100 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Management LA: FW (m 2 /kg) Genetic

MANAGEMENT TEMPERATURE Key findings Elasticity VERAISON ASSESSMENT Deformability Softness (50%) Colour(50%) Pinot noir/sauvignon blanc Pinot noir 4.8 Brix 7 Brix 8.1 Brix 9.3 Brix VARIETAL PHENOLOGY AND BERRY MATURATION FLOWERING GFV model 95 varieties classified 1120 C.d 1411 C.d Early Late Meunier Semebat FRUITSET VERAISON Colour/softness GFV model 104 varieties classified 2286 C.d 2941 C.d Early Late Garanoir Semebat BERRY RIPENING Soluble solids (SS)/sugar accumulation Titratable acidity decrease ph increase Berry weight decrease 200g/L SUGAR Sigmoid/GFV model GFV model : 35 varieties classified 2876 C.d 3720 C.d Early Late Pinot noir Sciaccarello LA : FW manipulations : LEAF VERSUS CROP REMOVAL LA FW Rate SS accumulation Rate SS accumulation Sauvignon blanc > Pinot noir Maximum SS values achieved with fruit removal LA Delay veraison FW Advance veraison + Laterals Earlier veraison (Sauvignon blanc) + Laterals Rate SS accumulation Harvest SS Sauvignon blanc and Pinot noir No change: TA, ph, Berry weight

Varietal characterisation -Choice Climate change - Climate change scenarios Management options - Delay timing: 1 week delay of veraison at 0.5 m 2 /kg - Implication for other metabolites Cool seasons- crop thinning to advance timing

Future work Background Phenological modelling NZ historical data Climate model context Soluble solids - Dynamic Veraison assessment methods Other varieties LA: FW manipulations Regression modelling Summary: Key Findings and Future Other berry components Site repetition Other varieties Thresholds Elasticity of responses

Publications Parker, A.K., Garcia de Cortázar-Atauri, I., Chuine, I., Barbeau, G., Bois, B., Boursiquot, J-M., Cahurel, J-Y., Claverie, M., Dufourcq, T., Gény, L., Guimberteau, G., Hofmann, R. W., Jacquet, O., Lacombe, T., Monamy, C., Ojeda, H., Panigai, L., Payan, J-C., Rodriquez Lovelle, B., Rouchaud, E., Schneider, C., Spring, J-L., Storchi, P., Tomasi, D., Trambouze, W., Trought, M., van Leeuwen, C. Classification of varieties for their timing of flowering and veraison using a modelling approach. A case study for the grapevine species Vitis vinifera L. In publication. Popular article: Bennett, J., Greven, M. & Parker, A. (2010). The influence of training systems and crop load on grapevine yield and fruit composition. New Zealand Wine Grower December 2010/January 2011, 14(3), 71-73.

Other grape publications Yiou, P., Garcia de Cortázar-Atauri, I., Chuine, I., Daux, V., Garnier, E. Viovy, N., van Leeuwen, C., Parker, A.K., Boursiquot, J-M. (2012). Continental atmospheric circulation over Europe during the Little Ice Age inferred from grape harvest dates. Climate of the Past., 8, 577-588. Parker, A. K., Garcia de Cortázar-Atauri, I., van Leeuwen, C., & Chuine, I. (2011) General phenological model to characterise the timing of flowering and veraison of Vitis vinifera L. Australian Journal of Grape and Wine Research, 17(2), 206-216. Garcia de Cortázar-Atauri, I., Daux, V., Garnier, E., Yiou, P., Viovy, N., Seguin, B., Parker, A., van Leeuwen, C., Chuine, I. (2010) Climate reconstructions from grape harvest dates: Methodology and uncertainties. Holocene, 20(4), 599-608.

Acknowledgements Supervisor: Dr Rainer Hofmann Co-supervisor: Dr. Michael Trought External Co-supervisor: Prof. Cornelis van Leeuwen Assoc. Supervisor: Prof. Don Kulasiri CHRISTCHURCH NEW ZEALAND www.lincoln.ac.nz AGMARDT Team at Plant and Food Marlborough and Palmerston North Team at Bordeaux-Sciences Agro Pernod Ricard NZ Ltd, Andrew Naylor, John Argyle and team at Brancott Estate. Wither Hills Isabelle Chuine and Inaki Garcia de Cortazar-Atauri, Luna Centioni, Marco Meroni, Montse Torres, Eric Lebon, Thierry Lacombe The Romeo Bragato Trust New Zealand Wine Growers MBIE Source of photos: Romeo Bragato Trust