Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Upcoming SlideShare
What to Upload to SlideShare
What to Upload to SlideShare
Loading in …3
×
1 of 23

BigDataGrapes_Table and Wine Grapes Pilot

0

Share

Download to read offline

Aikaterini Kassimati presentation on the Table and Wine Grapes Pilot progress at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)

BigDataGrapes_Table and Wine Grapes Pilot

  1. 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. 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. 3. WWW.BIGDATAGRAPES.EU Table and Wine Grapes Pilot 3 Introduction & Specific Goals “Big Data for the Grapevine Industries” Workshop
  4. 4. WWW.BIGDATAGRAPES.EU Table and Wine Grapes Pilot Introduction “Big Data for the Grapevine Industries” Workshop
  5. 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. 6. WWW.BIGDATAGRAPES.EU Table and Wine Grapes Pilot 6 Technical Guidelines and Methodology “Big Data for the Grapevine Industries” Workshop
  7. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 19. WWW.BIGDATAGRAPES.EU 19 Expected Timeline “Big Data for the Grapevine Industries” Workshop
  20. 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. 21. WWW.BIGDATAGRAPES.EU Table and Wine Grapes Pilot Envisaged Outcomes 21“Big Data for the Grapevine Industries” Workshop
  22. 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
  23. 23. WWW.BIGDATAGRAPES.EU Aikaterini Kasimati Maritina Stavrakaki AUA akasimati@aua.gr maritina@aua.gr @BigDataGrapes https://www.linkedin.com/groups/13574473 Thank you!! 23

×