UCCE Sonoma County Grape Day February 8, 2017 Assessing variability in the vineyard through a spatially explicit selective-harvest approach A case study in Sonoma L. Brillante, A. Beebee, R. Yu, J. Martinez, C. Chen, C. Plank, L. Sanchez & S.K.Kurtural (PI) 2017 Grape Day Sonoma County February 8, 2016 Introduction Vineyards are variable in space The efficient vineyard project The field site in Sonoma Results OUTLINE Plan of the talk Terrain analysis Grapevine water status Our approach to the selective harvest Chemical differences between zones Conclusions & Perspectives 1
VARIABILITY IN VINEYARDS VARIABILITY IS A COST! VINEYARD VARIABILITY The project Dr Kaan Kurtural Lab Oakville Experimental Station UNDERSTANDING AND MANAGING SPATIAL VARIABILITY SITE SPECIFIC VARIABLE RATE MANAGEMENT 2
UCCE Sonoma County Grape Day February 8, 2017 Six vineyards across California Sonoma Napa Galt 6 Vineyards SONOMA When variability is huge Paso Robles Delano (2 vineyards) The Work Flow SENSING High Resolution DEM NDVI DuoLite Electrical resistivity Multiplex Satellite images ` FIELD MEASUREMENTS Grapevine physiological measurements Plant water status Canopy microclimate Net gas exchange Soil measurements GEOSTATISTICAL ANALYSIS & MODELLING LABORATORY ANALYSIS Primary metabolism (wet chemistry) Secondary metabolism Flavan 3 ols Flavonols Anthocyanins Proanthocyanidins OUTPUT 3
Selective harvest in Sonoma The site Ph. Credit = L Unita 4
UCCE Sonoma County Grape Day February 8, 2017 The site A spatially explicit grid with 35 datapods Sensing Physiological measurements Laboratory analysis (primary and secondary metabolism) Geostatistical analysis Cabernet Sauvignon/110R Two single high h wires in a horizontally split canopy Planted at 7 x 11 feet Terrain analysis of the site GPS DATA (Elevation) Slope Soil Wetness Index 5
Water status Higher Water Stress Lower Water Stress 12 2/26/2017 6
UCCE Sonoma County Grape Day February 8, 2017 Grapevine water status 2 VERY DIFFERENT ZONES! Clustering Lower Water Stress Higher Water Stress Summarize in space and time Direct clustering with space and time Summarizetimeinformation information (water potential integrals) Spatial clustering of the time variable 14 2/26/2017 7
0 Summarize time: What is stem water potential integral Stem Water Poten ntial 16 2/26/2017 8
UCCE Sonoma County Grape Day February 8, 2017 Relationships with the environment Water Potential Integrals Surface soil electrical resistivity GOOD RELATIONSHIPS WITH SOIL AND TOPOGRAPHY! 3D model of water status 3D model of soil wetness Relationships with the environment Elevation Soil wetness index (MPa) r = 0.76 (MPa) ρ = 0.56 9
IS WATER STATUS A SENSITIVE TOOL TO DISCRIMINATE BETWEEN HARVEST ZONES? This clustering explain 70% of the observed variability in water status 10
UCCE Sonoma County Grape Day February 8, 2017 Stem water potential Photosynthesis (μmol CO μmol 1 2 H 2 O) (μmo olh 2 O m 2 s 1 ) (μmo olco 2 m 2 s 1 ) 11
Components of yield Not a significant correlation bt between water status tt and yield! Primary metabolism 30.4 26.7 12
UCCE Sonoma County Grape Day February 8, 2017 Degradation? Total anthocyanins * Anthocyanins ρ = 0.56 Stem Water Potentials Integrals (MPa) 3 5 OH Anthocyanin 3 OH Anthocyanin * * r = 0.53 Stem Water Potentials Integrals (MPa) Total Anthocyanins 3 OH Anthocyanins 3 5 OH Anthocyanins mg/g berry mg/g berry mg/g berry 26 2/26/2017 13
Tannins /g SDM) Total Proanthocyanidins (mg/ Total Proanthocyanidins * (+) Catechin r = 0.41 Stem Water Potentials Integrals (MPa) The wine Soluble solids * Malic Acid * just finished. STAY TUNED! 14
UCCE Sonoma County Grape Day February 8, 2017 Not only by pressure bomb: Modelling grapevine water status Brillante et al., 2016. Ecophysiological modelling of Burgundy wine terroirs by a machine learning approach. Front. Plant Sci. 7:796 29 2/26/2017 Simulating grapevine water status in two different scenarios. Future: irrigation prescription to minimize variability in the field 30 2/26/2017 15
Not only by hands: selective harvest by mechanical means Kurtural et al. 2012 Conclusions Vineyard variability affects harvest composition and then the wine Selective harvest can be a useful strategy when vineyard variability is too large to coalesce Water status allows to effectively discriminate between the harvest zones. Less of a need to take repeated measurements and can be easily modelled/sensed. 16
UCCE Sonoma County Grape Day February 8, 2017 Perspectives Need to evaluate relationships with our proximal sensors/water status modelling. Better investigate relationships with the environment, temporal variations. Wine analysis This is only one of the fields, we are testing variable rate management on the others. STAY TUNED! Acknowledgment Johann Martinez S. Kaan Kurtural Andrew Beebee Anita Oberholster Chik Brenneman Luis Sanchez & Jim O Donnell Cassandra Plank Runze Cliff Yu Chris Chen We have many interesting posters about different projects! Take a look! 17
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