The Productivity Challenge for California

Nick Dokoozlian Economic Sustainability of Grapevine Lisbon, Portugal January 2015

0 The Productivity Challenge for California Wine Grapes

• Suitable land, labor and water for premium wine production are becoming more scarce and expensive • Need to increase supply without dramatically increasing production area and environmental footprint • Must increase both yield and quality simultaneously • Similar challenges are being faced by nearly all other agricultural commodities worldwide

1 U.S. corn yields have more than quadrupled since 1920 25 Advances in genetics,

20 technology and agronomic practices

15 Synthetic N Crop 10 and pesticides biotechnology

5 Corn yield (tons per acre) (tons Corn yield 0 1860 1880 1900 1920 1940 1960 1980 20002012 2020 Year 2 California grape yields have doubled since 1920 12 Improved trellising, 11 ) management, 10 Virus elimination design 9 and clonal 8 selection 7 6 5 Drip irrigation and 4 improved irrigation 3 management Wine and grape yield in the Central Valley (tons per acre) 2 technology Central Valley (tons per acre Central Valley

Wine grape yield per acre in the Wine 1 0 1920 1930 1940 1950 1960 1970 1980 1990 20002012 2010 Year 3 California grape yields have doubled since 1920 12 Improved trellising, 11 ) Why haven’t we donecanopy better?management, 10 Virus elimination vineyard design • Unable9 toand exploit clonal traditional plant breeding for 8 varietyselection improvement • Difficulty7 in applying precision farming practices 6 to perennial cropping systems 5 Drip irrigation and • Extended4 time lag betweenimproved technology irrigation 3 development and vineyardmanagement planting cycle Wine and grape yield in the Central Valley (tons per acre) 2 technology • (tons per acre Historical Central Valley view of yield vs. quality and the

Wine grape yield per acre in the Wine 1 lack of acceptance of objective fruit 0 1920quality 1930 1940measures 1950 1960 1970 1980 1990 2000 2010 Year 4 Historical view of yield and quality

Yield vs. Quality Traditional View Increasing quality

Grape and wine quality Increasing yield Yield per acre 5 Yield and Quality , Napa Valley

2010 Yield = 18 tons Color = 1.8 mg/g

1990 Yield = 12 tons Color = 1.2 mg/g 1959 Over the last 50 Yield = 8 tons Color = 1.0 mg/g years, both Increasing quality yield and Grape and wine quality Increasing yield quality have Yield per hectare improved 6 Crop Load Fruit yield relative to canopy size

Fruit yield Canopy size

Canopy size or Fruit yield capacity (Pruning weight) Crop load, not yield per acre, drives quality Fruit and wine composition Increasing quality Canopy more than adequate for optimum quality < 5 Yield: Pruning Weight Ratio kg fruit weight per kgpruning Increasing crop load 5 to8 pruning weight kg fruitper > 10 fruit quality limiting to Leaf area pruning weight per kg gfruit kg 600 5 Zinfandel

500 Fruit 4 400 Chemistry

300 Wine 3 Sensory

200

Aroma chemistry 2 100 Combined aroma activity values activity Combined aroma

0 1 (1-5) via sensory Aroma intensity 0 5 10 15 20 25 (Combined mouthfeel activity values) (Combined mouthfeel activity Yield: Pruning Weight Ratio ) 1-5 (

Zinfandel

400 5 y

300 4 Fruit via sensor via

Chemistry y 200 3

100 2

Mouthfeel chemistry Mouthfeel Wine Sensory

0 1

0 5 10 15 20 intensit Mouthfeel 25 (Combined mouthfeel activity values) activity mouthfeel (Combined Yield: Pruning Weight Ratio Modern view of yield and quality

Yield vs. Quality Modern View Increasing quality

Grape and wine quality Increasing yield Yield per acre 11 WhatObjective is our roadmapof Today’s for Meeting improving productivity and quality? Germplasm Molecular Precision selection and physiology, and genetic genomics and agronomic improvement other omics practices

• Clonal selection • Characterize • Variability • x scion regulation of key characterization evaluations yield and fruit and management • Emerging varietal quality pathways • Remote and evaluations • Functional proximal sensor • Maintain disease- genomics data integration free plant • Genetic • Prescription materials improvement farming practices

12 WhatObjective is our roadmapof Today’s for Meeting improving productivity and quality? Germplasm Molecular Precision selection and physiology, viticulture and genetic genomics and agronomic improvement other omics practices

• Clonal selection • Characterize • Variability • Rootstock x scion regulation of key characterization evaluations yield and fruit and management • Emerging varietal quality pathways • Remote and evaluations • Functional proximal sensor • Maintain disease- genomics data integration free plant • Genetic • Prescription materials improvement farming practices

13

Automated GIS sensors technology measuring intra- uses this field vineyard information to variability – crop construct load, canopy spatial maps size, irrigation of key vine requirements performance parameters

Variability maps used to spatially alter vineyard practices

14 Precision Viticulture

Automated GIS sensors technology measuring intra- uses this field vineyard information to Precisionvariability – Viticulture crop construct load, canopy spatial maps Need for differentialsize, irrigation management , notof onlykey vine requirements performance differential parameters Goal is to characterize field variability in order to apply inputs and differential farming practices to achieve maximum yieldVariability in all sections of the block maps used to spatially alter vineyard practices

15 Yield maps illustrate vine performance variability Cabernet Sauvignon 9.2 tons/acre 22.7 tons/ha

16 / 32.1 acres 20 Colony 2A Cabernet Sauvignon Mean yield = 9.2 tons per acre or 22.7 tons per hectare (%)

15

10 acreage

5 Block

0 1 2 3 4 5 6 7 8 9 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 10 11 12 13 14 15 16 17 18 19 20 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 0 1 2 3 4 5 6 7 8 ‐ 9 10 11 12 13 14 15 16 17 18 19 Yield (tons/acre)

17 / 32.1 acres 20 Colony 2A Cabernet Sauvignon Mean yield = 9.2 tons per acre or 22.7 tons per hectare (%) 15 40% of vineyard below mean 10 block yield acreage

Block improvement 5

Block opportunity = 30% yield increase 0 1 2 3 4 5 6 7 8 9 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 10 11 12 13 14 15 16 17 18 19 20 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 0 1 2 3 4 5 6 7 8 ‐ 9 10 11 12 13 14 15 16 17 18 19 Yield (tons/acre)

18 / 32.1 acres 20 Colony 2A Cabernet Sauvignon Mean yield = 9.2 tons per acre or 22.7 tons per hectare (%) 15 40% of vineyard 20% of vines below mean produce quality 10 block yield below district mean acreage

Block improvement 5 Improvement

Block opportunity opportunity = 30% yield increase significant 0 1 2 3 4 5 6 7 8 9 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 10 11 12 13 14 15 16 17 18 19 20 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 0 1 2 3 4 5 6 7 8 ‐ 9 10 11 12 13 14 15 16 17 18 19 Yield (tons/acre)

19 The Productivity Challenge for Wine Grapes What can we learn from agronomic crops? Significant advances in the productivity of agronomic crops has occurred during the past two decades via: – Use of remote and proximal sensors to monitor crop development – Application of agricultural analytics and data analysis – Implementation of variable rate management 20 Integrated vineyard analytics -

Plant Vegetation Fruit available Yield Index Quality water in soil (NDVI)

21 Grape Quality Index

Grape Quality Index • Objective, chemical measure of fruit quality correlating with final wine sensory attributes. Index integrates:  Negative aroma (green) compounds  Positive aroma (fresh fruit, dark fruit, jammy fruit) compounds GQI scale = 0 to 100  Anthocyanins  Mouthfeel compounds (polymeric tannins, pigmented polymers)

22 Modeling Yield and Fruit Quality Data with Soil Parameters Significant Correlations with Yield per Acre Parameter Correlation (r2) Subsurface K+ 0.903 Soil rooting depth 0.774 Subsurface pH – 0.805 Subsurface P – 0.805 Subsurface organic matter – 0.882 Subsurface K/Mg ratio – 0.890 Significant Correlations with Grape Quality Parameter Correlation (r2) Soil rooting depth – 0.673 Surface CA – 0.506 Subsurface CA / Mg ratio – 0.510 Surface CEC – 0.554

23 Yield increases with canopy size (NDVI) orY-Values vine capacity 3550

28408

2130

(tons) 1420

710 Yield per hectare Yield 00 0.200246810120.30 0.40 0.500.3 0.60 0.70 0.80 Canopy size (NDVI) GQI decreases with canopy size (NDVI)Y-Values or vine capacity 10050 • Yield effect? • 80408 effect? 6030

4020

2010

00 0.200246810120.30 0.40 0.500.3 0.60 0.70 0.80 Grape Quality Index (GQI) Grape Quality Index Canopy size (NDVI) Y-Values 10050

80408 Low capacity 6030 vines 4020 High capacity 20 10 vines Grape Quality Index Grape Quality Index 00 0.200246810120.30 0.40 0.500.3 0.60 0.70 0.80 Canopy size (NDVI) Y-Values 509 Low capacity vines High capacity 4088 vines

307

206 Optimum

105 4 to 10 tons 16 to 25 tons

Yield:Pruning Wt. Ratio Yield:Pruning per hectare per hectare 40 0.200246810120.30 0.40 0.500.3 0.60 0.70 0.80 CanopyNDVI size (NDVI) Y-Values 1050 Low capacity 40 88 vines

306 High capacity

204 Optimum 4 to 10 tons vines per hectare 102 16 to 25 tons at mid-day (% ambient ) at mid-day (% ambient

Sunlight in the fruit zone in the fruit zone Sunlight per hectare 00 0.200246810120.30 0.40 0.500.3 0.60 0.70 0.80 Canopy size (NDVI) Variable rate management

29 Can differential management improve the quality of high capacity vines? Mean mid-day Treatment fruit zone PPF (% ambient)

Low capacity vines 5.8 a

High capacity vines 1.9 b High capacity vines w/additional basal 5.1 a leaf removal

30 Grape quality improved by canopy manipulation Y-Values 10050 Color, phenolics increased, IBMP reduced 80408 Impact of stored soil Low capacity moisture 6030 vines on GQI 4020 High capacity 20 10 vines Grape Quality Index Grape Quality Index 00 0.200246810120.30 0.40 0.500.3 0.60 0.70 0.80 NDVI Y-Values Quality improved by 10050 precision leaf removal 80408 Low capacity 6030 vines 4020 8 tons per hectare High capacity 20 10 Similar quality vines

Grape Quality Index Grape Quality Index 18 tons per hectare 00 0.200246810120.30 0.40 0.500.3 0.60 0.70 0.80 CanopyNDVI size (NDVI) Variable rate management

33 Automated Vineyard Analytics Crop estimation Sensor mapping canopy Digitized clusters and leaves

Geo-spatial shoot thinning Crop load variability

Vine row orientation

34 Precision irrigation and fertigation

System allows management of irrigation amount and frequency based on vine size 35 Changes in canopy vigor (NDVI)

Colony 2A Cabernet Sauvignon 2012 yield map July 2012 July 2013 Precision Irrigation 36 Yield per hectare of desired market quality What isthefuture ofviticulture? Time Transformational innovation Sustainable innovation 37 Wine Industry Innovation Stream

Sustaining Transformational Disruptive Innovation Innovation Innovation

Traditional cultural Development of Integration of practice research to variable rate genetic selection reduce costs and technology for and improvement, increase yield and pruning, canopy molecular quality management and physiology and irrigation precision agriculture technologies

6 tons per hectare 25 tons per hectare 50 tons per hectare GQI 70 GQI 80 GQI 90 38 The Productivity Challenge for Wine Grapes Summary • Simultaneous improvement of yield and quality will be achieved via an integrated systems approach – Germplasm improvement – Molecular physiology – Precision viticulture • Precision viticulture allows us to manage – not just characterize – yield and quality variability – Improve yield of low capacity vines – Improve fruit quality of high capacity vines 39 Acknowledgements • Mike Cleary • Luis Sanchez • Nona Ebisuda • Don Katayama • Andrew Morgan • Hui Chong • David Santino • Kari Severe • Terry Lee