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WWW.BIGDATAGRAPES.EU
BigDataGrapes - Big Data to Enable Global Disruption of the
Grapevine-powered Industries has received funding from the
European Union’s Horizon 2020 research and innovation programme
under grant agreement No 780751.
Table and Wine Grapes
Pilot
“Big Data for the Grapevine Industries” Workshop |
Pisa , Italy, 08/03/2019
Aikaterini Kasimati | Laboratory of Precision Agriculture
Maritina Stavrakaki | Laboratory of
Viticulture
Agricultural University of Athens
“Big Data for the Grapevine Industries”
Workshop
WWW.BIGDATAGRAPES.EU
Tables and Wine Grapes Pilot
Introduction & Specific Goals
Technical Guidelines and Methodology
• Site Description
• Equipment Used and Measurements
 Data Collected
 Expected Timeline
 Envisaged Outcomes
“Big Data for the Grapevine Industries” Workshop 2
Presentation Outline
WWW.BIGDATAGRAPES.EU
Table and Wine Grapes
Pilot
3
Introduction & Specific Goals
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU
Table and Wine Grapes Pilot
Introduction
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU
This pilot will continuously collect and monitor sensor, farming and
phenological data derived from all test sites located in Greece.
Pilot’s goal
 Denote associations and correlations between precision agriculture
information and phenological data and grape chemical analysis
Ultimate goal
 Correlate the aforementioned data with earth observation data to
examine the effectiveness of applying machine learning techniques and
eventually train the relevant machine learning components
5
Table and Wine Grapes Pilot
Specific Goals
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU
Table and Wine Grapes
Pilot
6
Technical Guidelines and
Methodology
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 7
Three test sites in the
north-eastern part of
Peloponnese, Greece:
• Palivou Estate
• Kontogiannis
Estate
• Fasoulis Estate
Site Description
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 8
• Nemea
• Vitis vinifera L. cv.
‘Agiorgitiko’ and ‘Merlot’
for winemaking
• northeast-southwest
row orientation
• VSP - cane
pruning, double Guyot
training/trellis system
Site Description
Palivou Estate
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 9
• Ancient Corinth
• ‘Roditis’, ‘Savatiano’,
‘Mavroudi’ and
‘Soultanina’ for
winemaking north-south
row orientation
• VSP - cane
pruning, double Guyot
or double Royat
training/trellis system
Site Description
Kontogiannis Estate
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 10
Site Description
Fasoulis Estate
“Big Data for the Grapevine Industries” Workshop
• Nemea
• 22 different table grape
varieties
• Southeast- Northwest
row orientation
WWW.BIGDATAGRAPES.EU 11
 HiPer V RTK GPS
Topographical data: field boundary points and elevation data
Equipment Used and Measurements
Topographical and Elevation Mapping
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 12
 EM38-MK2 probe
Soil electrical conductivity (ECa) at 0.5 and 1.0 m depth (mS/m)
https://photos.app.goo.gl/5LzP3WpcbsRvJEAe9
Equipment Used and Measurements
Geo-referenced Apparent Soil Electrical Conductivity
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 13
 Crop Circle ACS-470
Basic reflectance information from plant canopies and classic spectral
vegetative index data (NDVI, NDRE etc.)
Equipment Used and Measurements
Canopy Characteristics and Vegetation Indices
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 14
 Crop Circle RapidSCAN CS-45
Basic reflectance information from plant canopies and classic spectral
vegetative index data (NDVI, NDRE etc.)
Equipment Used and Measurements
Canopy Characteristics and Vegetation Indices
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 15
 SpectroSense2+ GPS
Leaf Area Index (LAI) and NDVI vegetation indices
Equipment Used and Measurements
Canopy Characteristics and Vegetation Indices
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 16
 Two Phantom 4 Pro drones Parrot Sequoia+ Multispectral sensor and
FLIR Vue Pro thermal infrared sensor
Aerial imagery data, vegetation indices, water activity maps
Equipment Used and Measurements
Drones with Multispectral and Thermal Sensors
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 17
 Two Vantage Pro 2 weather stations
Rain sensor, anemometer to measure wind speed and direction, air
temperature sensor, air and soil humidity sensor
Equipment Used and Measurements
Weather and Soil Data
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EUWP8 - Grapevine-powered Industry Application Pilots 18
 ATAGO N1-a refractometer w/ 0-32 Brix measurement range
Soluble solids
 Titration with a 0.1 N NaOH solution
Total titratable acidity -expressed as tartaric acid-
 HPLC Shimadzu Nexera (gradient pump Shimadzu Nexera X2, ProStar
model 410 AutoSampler, and ProStar model 330 Photodiode Array Detector)
Quantitative and qualitative analysis of the substances
 Modified colorimetric method
Antioxidant activity (2,2-diphenyl-1-picrylhydrazyl, DPPH)
 UV/Vis spectrophotometer
Reduction of the DPPH radical @ 517 nm and the absorption of the
antioxidant activity @ 593 nm
Equipment Used and Measurements
Qualitative and Quantitative Data
WWW.BIGDATAGRAPES.EU 19
Expected Timeline
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 20
• Identification of grapevine varieties
• Remote sensing for spatial data, topographical and elevation
mapping
• Geo-referenced apparent soil electrical conductivity (ECa)
• Canopy characteristics and vegetation indices
• Water activity and photosynthesis and chlorophyll data
• Qualitative and quantitative characters for wine and table
grapes
• Full phenolic profile of grapevine varieties
• Yield mapping
• Soil, weather and farming data
Data Collected
WWW.BIGDATAGRAPES.EU
Table and Wine Grapes
Pilot
Envisaged Outcomes
21“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU 22
 The collection of datasets for BigDataGrapes will serve
as the basis for carrying out research and technical
work
 These data will contribute to a data marketplace
demonstrator that will serve as the project’s
experimentation environment
 The data pool will be continuously enriched in volume
and range, in accordance with the needs and
requirements of the project
Envisaged Outcomes
“Big Data for the Grapevine Industries” Workshop
WWW.BIGDATAGRAPES.EU
Aikaterini Kasimati
Maritina Stavrakaki
AUA
akasimati@aua.gr
maritina@aua.gr
@BigDataGrapes
https://www.linkedin.com/groups/13574473
Thank you!!
23

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BigDataGrapes_Table and Wine Grapes Pilot

  • 1. WWW.BIGDATAGRAPES.EU BigDataGrapes - Big Data to Enable Global Disruption of the Grapevine-powered Industries has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 780751. Table and Wine Grapes Pilot “Big Data for the Grapevine Industries” Workshop | Pisa , Italy, 08/03/2019 Aikaterini Kasimati | Laboratory of Precision Agriculture Maritina Stavrakaki | Laboratory of Viticulture Agricultural University of Athens “Big Data for the Grapevine Industries” Workshop
  • 2. WWW.BIGDATAGRAPES.EU Tables and Wine Grapes Pilot Introduction & Specific Goals Technical Guidelines and Methodology • Site Description • Equipment Used and Measurements  Data Collected  Expected Timeline  Envisaged Outcomes “Big Data for the Grapevine Industries” Workshop 2 Presentation Outline
  • 3. WWW.BIGDATAGRAPES.EU Table and Wine Grapes Pilot 3 Introduction & Specific Goals “Big Data for the Grapevine Industries” Workshop
  • 4. WWW.BIGDATAGRAPES.EU Table and Wine Grapes Pilot Introduction “Big Data for the Grapevine Industries” Workshop
  • 5. WWW.BIGDATAGRAPES.EU This pilot will continuously collect and monitor sensor, farming and phenological data derived from all test sites located in Greece. Pilot’s goal  Denote associations and correlations between precision agriculture information and phenological data and grape chemical analysis Ultimate goal  Correlate the aforementioned data with earth observation data to examine the effectiveness of applying machine learning techniques and eventually train the relevant machine learning components 5 Table and Wine Grapes Pilot Specific Goals “Big Data for the Grapevine Industries” Workshop
  • 6. WWW.BIGDATAGRAPES.EU Table and Wine Grapes Pilot 6 Technical Guidelines and Methodology “Big Data for the Grapevine Industries” Workshop
  • 7. WWW.BIGDATAGRAPES.EU 7 Three test sites in the north-eastern part of Peloponnese, Greece: • Palivou Estate • Kontogiannis Estate • Fasoulis Estate Site Description “Big Data for the Grapevine Industries” Workshop
  • 8. WWW.BIGDATAGRAPES.EU 8 • Nemea • Vitis vinifera L. cv. ‘Agiorgitiko’ and ‘Merlot’ for winemaking • northeast-southwest row orientation • VSP - cane pruning, double Guyot training/trellis system Site Description Palivou Estate “Big Data for the Grapevine Industries” Workshop
  • 9. WWW.BIGDATAGRAPES.EU 9 • Ancient Corinth • ‘Roditis’, ‘Savatiano’, ‘Mavroudi’ and ‘Soultanina’ for winemaking north-south row orientation • VSP - cane pruning, double Guyot or double Royat training/trellis system Site Description Kontogiannis Estate “Big Data for the Grapevine Industries” Workshop
  • 10. WWW.BIGDATAGRAPES.EU 10 Site Description Fasoulis Estate “Big Data for the Grapevine Industries” Workshop • Nemea • 22 different table grape varieties • Southeast- Northwest row orientation
  • 11. WWW.BIGDATAGRAPES.EU 11  HiPer V RTK GPS Topographical data: field boundary points and elevation data Equipment Used and Measurements Topographical and Elevation Mapping “Big Data for the Grapevine Industries” Workshop
  • 12. WWW.BIGDATAGRAPES.EU 12  EM38-MK2 probe Soil electrical conductivity (ECa) at 0.5 and 1.0 m depth (mS/m) https://photos.app.goo.gl/5LzP3WpcbsRvJEAe9 Equipment Used and Measurements Geo-referenced Apparent Soil Electrical Conductivity “Big Data for the Grapevine Industries” Workshop
  • 13. WWW.BIGDATAGRAPES.EU 13  Crop Circle ACS-470 Basic reflectance information from plant canopies and classic spectral vegetative index data (NDVI, NDRE etc.) Equipment Used and Measurements Canopy Characteristics and Vegetation Indices “Big Data for the Grapevine Industries” Workshop
  • 14. WWW.BIGDATAGRAPES.EU 14  Crop Circle RapidSCAN CS-45 Basic reflectance information from plant canopies and classic spectral vegetative index data (NDVI, NDRE etc.) Equipment Used and Measurements Canopy Characteristics and Vegetation Indices “Big Data for the Grapevine Industries” Workshop
  • 15. WWW.BIGDATAGRAPES.EU 15  SpectroSense2+ GPS Leaf Area Index (LAI) and NDVI vegetation indices Equipment Used and Measurements Canopy Characteristics and Vegetation Indices “Big Data for the Grapevine Industries” Workshop
  • 16. WWW.BIGDATAGRAPES.EU 16  Two Phantom 4 Pro drones Parrot Sequoia+ Multispectral sensor and FLIR Vue Pro thermal infrared sensor Aerial imagery data, vegetation indices, water activity maps Equipment Used and Measurements Drones with Multispectral and Thermal Sensors “Big Data for the Grapevine Industries” Workshop
  • 17. WWW.BIGDATAGRAPES.EU 17  Two Vantage Pro 2 weather stations Rain sensor, anemometer to measure wind speed and direction, air temperature sensor, air and soil humidity sensor Equipment Used and Measurements Weather and Soil Data “Big Data for the Grapevine Industries” Workshop
  • 18. WWW.BIGDATAGRAPES.EUWP8 - Grapevine-powered Industry Application Pilots 18  ATAGO N1-a refractometer w/ 0-32 Brix measurement range Soluble solids  Titration with a 0.1 N NaOH solution Total titratable acidity -expressed as tartaric acid-  HPLC Shimadzu Nexera (gradient pump Shimadzu Nexera X2, ProStar model 410 AutoSampler, and ProStar model 330 Photodiode Array Detector) Quantitative and qualitative analysis of the substances  Modified colorimetric method Antioxidant activity (2,2-diphenyl-1-picrylhydrazyl, DPPH)  UV/Vis spectrophotometer Reduction of the DPPH radical @ 517 nm and the absorption of the antioxidant activity @ 593 nm Equipment Used and Measurements Qualitative and Quantitative Data
  • 19. WWW.BIGDATAGRAPES.EU 19 Expected Timeline “Big Data for the Grapevine Industries” Workshop
  • 20. WWW.BIGDATAGRAPES.EU 20 • Identification of grapevine varieties • Remote sensing for spatial data, topographical and elevation mapping • Geo-referenced apparent soil electrical conductivity (ECa) • Canopy characteristics and vegetation indices • Water activity and photosynthesis and chlorophyll data • Qualitative and quantitative characters for wine and table grapes • Full phenolic profile of grapevine varieties • Yield mapping • Soil, weather and farming data Data Collected
  • 21. WWW.BIGDATAGRAPES.EU Table and Wine Grapes Pilot Envisaged Outcomes 21“Big Data for the Grapevine Industries” Workshop
  • 22. WWW.BIGDATAGRAPES.EU 22  The collection of datasets for BigDataGrapes will serve as the basis for carrying out research and technical work  These data will contribute to a data marketplace demonstrator that will serve as the project’s experimentation environment  The data pool will be continuously enriched in volume and range, in accordance with the needs and requirements of the project Envisaged Outcomes “Big Data for the Grapevine Industries” Workshop