The Productivity Challenge for Wine California Grapes

Nick DokoozlianEconomic Sustainability of Grapevine

Lisbon, Portugal January 2015

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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 grape 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

1860 1880 1900 1920 1940 1960 1980 2000 2020

Cor

n yi

eld

(tons

per

acr

e)

0

5

10

15

20

25

Synthetic N fertilizers and

pesticides

Advances in genetics, technology and

agronomic practices

U.S. corn yields have more than quadrupled since 1920

2012

2

Crop biotechnology

Year

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Win

e an

d gr

ape

yiel

d in

the

Cen

tral

Val

ley

(tons

per

acr

e)

0123456789

101112 Improved trellising,

canopy management, vineyard design

Drip irrigation and improved irrigation

management technology

Virus elimination and clonal selection

California grape yields have doubled since 1920W

ine

grap

e yi

eld

per a

cre

in th

e

Cen

tral

Val

ley

(tons

per

acr

e )

3Year

2012

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Win

e an

d gr

ape

yiel

d in

the

Cen

tral

Val

ley

(tons

per

acr

e)

0123456789

101112 Improved trellising,

canopy management, vineyard design

Drip irrigation and improved irrigation

management technology

Virus elimination and clonal selection

California grape yields have doubled since 1920W

ine

grap

e yi

eld

per a

cre

in th

e

Cen

tral

Val

ley

(tons

per

acr

e)

4Year

Why haven’t we done better?• Unable to exploit traditional plant breeding for

variety improvement • Difficulty in applying precision farming practices

to perennial cropping systems • Extended time lag between technology

development and vineyard planting cycle • Historical view of yield vs. quality and the

lack of acceptance of objective fruit quality measures

Yield per acre

Gra

pe a

nd w

ine

qual

ity

Historical view of yield and quality

Increasing yield

Incr

easi

ng q

ualit

y

5

Yield vs. QualityTraditional View

Yield per hectare

Gra

pe a

nd w

ine

qual

ity

Yield and QualityCabernet Sauvignon, Napa Valley

Increasing yield

Incr

easi

ng q

ualit

y

6

Over the last 50

years, bothyield and

quality have improved

1959

1990

2010

Yield = 8 tons Color = 1.0 mg/g

Yield = 12 tons Color = 1.2 mg/g

Yield = 18 tons Color = 1.8 mg/g

Canopy size or capacity (Pruning weight)

Fruit yield

Canopy size Fruit yield

Crop Load Fruit yield relative to canopy size

Crop load, not yield per acre, drives quality

Frui

t and

win

e co

mpo

sitio

n

Yield: Pruning Weight Ratio

5 to 8 kg fruit per kg pruning weight

Leaf area limiting to

fruit quality > 10 kg fruit

per kg pruning weight

Canopy more than adequate for optimum quality < 5 kg fruit per kg pruning weight

Incr

easi

ng q

ualit

y

Increasing crop load

Yield: Pruning Weight Ratio0 5 10 15 20 25

Aro

ma

chem

istr

y(C

ombi

ned

mou

thfe

el a

ctiv

ity v

alue

s)

0

100

200

300

400

500

600Zinfandel

0 5 10 15 20 25

Aro

ma

inte

nsity

via

sen

sory

(1-5

)

1

2

3

4

5

Fruit Chemistry

Wine Sensory

Com

bine

d ar

oma

activ

ity v

alue

s

Yield: Pruning Weight Ratio0 5 10 15 20 25

Mou

thfe

el c

hem

istr

y(C

ombi

ned

mou

thfe

el a

ctiv

ity v

alue

s)

0

100

200

300

400Zinfandel

Mou

thfe

el in

tens

ity v

ia s

enso

ry (1

-5)

1

2

3

4

5

Fruit Chemistry

Wine Sensory

Yield per acre

Gra

pe a

nd w

ine

qual

ity

Modern view of yield and quality

Increasing yield

Incr

easi

ng q

ualit

y

11

Yield vs. QualityModern View

Objective of Today’s MeetingWhat is our roadmap for improving productivity and quality?

• Clonal selection • Rootstock x scion

evaluations• Emerging varietal

evaluations • Maintain disease-

free plant materials

• Characterize regulation of key yield and fruit quality pathways

• Functional genomics

• Genetic improvement

• Variability characterization and management

• Remote and proximal sensor data integration

• Prescription farming practices

Germplasm selection and

genetic improvement

12

Molecular physiology,

genomics and other omics

Precision viticulture and

agronomic practices

Objective of Today’s MeetingWhat is our roadmap for improving productivity and quality?

• Clonal selection • Rootstock x scion

evaluations• Emerging varietal

evaluations • Maintain disease-

free plant materials

• Characterize regulation of key yield and fruit quality pathways

• Functional genomics

• Genetic improvement

• Variability characterization and management

• Remote and proximal sensor data integration

• Prescription farming practices

Germplasm selection and

genetic improvement

13

Molecular physiology,

genomics and other omics

Precision viticulture and

agronomic practices

Variability maps used to spatially

alter vineyard practices

Precision Viticulture Automated

sensors measuring intra-

field vineyard variability – crop

load, canopy size, irrigation requirements

GIS technology uses this

information to construct

spatial maps of key vine

performance parameters

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Variability maps used to spatially

alter vineyard practices

Precision Viticulture Automated

sensors measuring intra-

field vineyard variability – crop

load, canopy size, irrigation requirements

GIS technology uses this

information to construct

spatial maps of key vine

performance parameters

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Precision Viticulture Need for differential management, not only

differential harvest Goal is to characterize field variability in order to apply

inputs and differential farming practices to achieve maximum yield in all sections of the block

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Yield maps illustrate vine performance variability

Cabernet Sauvignon

9.2 tons/acre 22.7 tons/ha

0

5

10

15

20

0‐1

1‐2

2‐3

3‐4

4‐5

5‐6

6‐7

7‐8

8‐9

9‐10

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12‐13

13‐14

14‐15

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16‐17

17‐18

18‐19

19‐20

Block acreage (%

)

Yield (tons/acre)

Colony 2A Cabernet Sauvignon / 32.1 acres

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Mean yield = 9.2 tons per acre or 22.7 tons per hectare

0

5

10

15

20

0‐1

1‐2

2‐3

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18‐19

19‐20

Block acreage (%

)

Yield (tons/acre)

Colony 2A Cabernet Sauvignon / 32.1 acres

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40% of vineyard below meanblock yield

Block improvementopportunity

= 30% yield increase

Mean yield = 9.2 tons per acre or 22.7 tons per hectare

0

5

10

15

20

0‐1

1‐2

2‐3

3‐4

4‐5

5‐6

6‐7

7‐8

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9‐10

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12‐13

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18‐19

19‐20

Block acreage (%

)

Yield (tons/acre)

Colony 2A Cabernet Sauvignon / 32.1 acres

19

40% of vineyard below meanblock yield

Block improvementopportunity

= 30% yield increase

Mean yield = 9.2 tons per acre or 22.7 tons per hectare

20% of vinesproduce quality

below district mean

Improvementopportunity significant

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

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Plant available

water in soil

Vegetation Index

(NDVI)

Yield Fruit Quality

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Integrated vineyard analytics -

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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

Anthocyanins

Mouthfeel compounds (polymeric tannins, pigmented polymers)

GQI scale = 0 to 100

Significant Correlations with Yield per AcreParameter Correlation (r2)

Subsurface K+

Soil rooting depthSubsurface pHSubsurface P

Subsurface organic matterSubsurface K/Mg ratio

0.9030.774

– 0.805– 0.805– 0.882– 0.890

Significant Correlations with Grape Quality Parameter Correlation (r2)

Soil rooting depthSurface CA

Subsurface CA / Mg ratioSurface CEC

– 0.673– 0.506– 0.510– 0.554

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Modeling Yield and Fruit Quality Data with Soil Parameters

0

10

20

30

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50

0 2 4 6 8 10 12

Y-Values

Canopy size (NDVI)

Yiel

d pe

r hec

tare

(to

ns)

0.20 0.30 0.40 0.3 0.60 0.70 0.800.50

7

14

21

0

8

35

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Yield increases with canopy size (NDVI) or vine capacity

0

10

20

30

40

50

0 2 4 6 8 10 12

Y-Values

Canopy size (NDVI)

Gra

pe Q

ualit

y In

dex

(GQ

I)

0.20 0.30 0.40 0.3 0.60 0.70 0.800.50

20

40

60

0

8

100

80

GQI decreases with canopy size (NDVI) or vine capacity

• Yield effect?• Microclimate

effect?

0

10

20

30

40

50

0 2 4 6 8 10 12

Y-Values

Canopy size (NDVI)

Gra

pe Q

ualit

y In

dex

0.20 0.30 0.40 0.3 0.60 0.70 0.800.50

20

40

60

0

8

100

Low capacity vines

High capacity vines

80

0

10

20

30

40

50

0 2 4 6 8 10 12

Y-Values

NDVI

Yiel

d:Pr

unin

g W

t. R

atio

0.20 0.30 0.40 0.3 0.60 0.70 0.800.50

5

6

7

4

8

9 Low capacity vines High capacity

vines

4 to 10 tons per hectare

16 to 25 tons per hectare

8

Canopy size (NDVI)

Opt

imum

0

10

20

30

40

50

0 2 4 6 8 10 12

Y-Values

Canopy size (NDVI)

Sunl

ight

in th

e fr

uit z

one

at m

id-d

ay (%

am

bien

t )

0.20 0.30 0.40 0.3 0.60 0.70 0.800.50

2

4

6

0

8

10 Low capacity

vines

High capacity

vines 4 to 10 tons per hectare

16 to 25 tons per hectare

8

Opt

imum

Variable rate management

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TreatmentMean mid-dayfruit zone PPF(% ambient)

Low capacity vines 5.8 a

High capacity vines 1.9 b

High capacity vines w/additional basal

leaf removal 5.1 a

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Can differential management improve the quality of high capacity vines?

0

10

20

30

40

50

0 2 4 6 8 10 12

Y-Values

NDVI

Gra

pe Q

ualit

y In

dex

0.20 0.30 0.40 0.3 0.60 0.70 0.800.50

20

40

60

0

8

100

Low capacity vines

High capacity vines

80

Grape quality improved by canopy manipulation

Color, phenolics increased, IBMP reduced

Impact of stored soil moisture on GQI

0

10

20

30

40

50

0 2 4 6 8 10 12

Y-Values

NDVI

Gra

pe Q

ualit

y In

dex

0.20 0.30 0.40 0.3 0.60 0.70 0.800.50

20

40

60

0

8

100

Low capacity vines

High capacity vines

80

Quality improved by precision leaf

removal

Canopy size (NDVI)

8 tons per hectare

18 tons per hectare Similar quality

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

35

System allows management of irrigation amount and frequency based on vine size

Precision irrigation and fertigation

Precision IrrigationJuly 2012 July 2013

Changes in canopy vigor (NDVI)

Colony 2A 

Cabernet Sauvignon2012 yield map

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Yiel

d pe

r hec

tare

of

desi

red

mar

ket q

ualit

y

Time

Sustainable innovation

Transformational innovation

What is the future of viticulture ?

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SustainingInnovation

Wine Industry Innovation Stream

TransformationalInnovation

DisruptiveInnovation

Traditional culturalpractice research toreduce costs andincrease yield and quality

Development ofvariable rate technology for pruning, canopy management and irrigation

Integration of genetic selection and improvement, molecular physiology and precision agriculture technologies

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6 tons per hectare 25 tons per hectare 50 tons per hectare GQI 70 GQI 80 GQI 90

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