Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyards

Individual vineyards can vary spatially for several viticultural attributes, including water stress, nutrient status, growth/vigour and disease—which can, in turn, impact berry composition and resulting wine products. The goal of this study was to determine if vineyard variability detected by remot...

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Main Authors: Briann Dorin, Andrew Reynolds, Marilyne Jollineau, Hyun-Suk Lee, Adam Shemrock
Format: Article
Language:English
Published: International Viticulture and Enology Society 2022-09-01
Series:OENO One
Subjects:
Online Access:https://oeno-one.eu/article/view/5352
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author Briann Dorin
Andrew Reynolds
Marilyne Jollineau
Hyun-Suk Lee
Adam Shemrock
author_facet Briann Dorin
Andrew Reynolds
Marilyne Jollineau
Hyun-Suk Lee
Adam Shemrock
author_sort Briann Dorin
collection DOAJ
description Individual vineyards can vary spatially for several viticultural attributes, including water stress, nutrient status, growth/vigour and disease—which can, in turn, impact berry composition and resulting wine products. The goal of this study was to determine if vineyard variability detected by remote sensing using an unmanned aerial vehicle (UAV) could be used to zonally harvest vineyard blocks and produce wines that are sensorially differentiable. The specific hypothesis was that remote sensing would detect vineyard variation in viticultural variables and associate this variation with differences in wine sensory attributes based upon zonal harvesting. In six commercial Riesling vineyards across the Niagara Peninsula in Ontario, Canada, a UAV collected multispectral data, which were used to calculate the normalized difference vegetation index (NDVI). Grapevines (≈ 80) in a grid pattern were geo-located within each block and vineyard UAV NDVI maps were used for zonal harvesting of geo-located vines in areas corresponding to high vs. low NDVI. Wines made from these zones were then compared chemically and sensorially. Overall, wines created from high vs. low NDVI zones differed inconsistently in their basic wine composition. Sensorially, for certain sites and vintages, panellists distinguished between wines made from high vs. low NDVI zones using a sorting task. UAV NDVI demonstrated the ability to determine areas within a vineyard block that could produce wines that were sensorially distinguishable from one another.
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spelling doaj.art-95e68492aadc4ea39641e062f81d6de82022-12-22T04:30:30ZengInternational Viticulture and Enology SocietyOENO One2494-12712022-09-0156310.20870/oeno-one.2022.56.3.5352Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyardsBriann Dorin0Andrew Reynolds1Marilyne Jollineau2Hyun-Suk Lee3Adam Shemrock4Faculty of Environmental and Urban Change, York University, 4700 Keele St, Toronto, ON M3J 1P3Independent scholarEnvironmental Sustainability Research Centre, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, ON L2S 3A1Department of Biological Sciences, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, ON L2S 3A1AirTech UAV Solutions Inc., Inverary, ON Individual vineyards can vary spatially for several viticultural attributes, including water stress, nutrient status, growth/vigour and disease—which can, in turn, impact berry composition and resulting wine products. The goal of this study was to determine if vineyard variability detected by remote sensing using an unmanned aerial vehicle (UAV) could be used to zonally harvest vineyard blocks and produce wines that are sensorially differentiable. The specific hypothesis was that remote sensing would detect vineyard variation in viticultural variables and associate this variation with differences in wine sensory attributes based upon zonal harvesting. In six commercial Riesling vineyards across the Niagara Peninsula in Ontario, Canada, a UAV collected multispectral data, which were used to calculate the normalized difference vegetation index (NDVI). Grapevines (≈ 80) in a grid pattern were geo-located within each block and vineyard UAV NDVI maps were used for zonal harvesting of geo-located vines in areas corresponding to high vs. low NDVI. Wines made from these zones were then compared chemically and sensorially. Overall, wines created from high vs. low NDVI zones differed inconsistently in their basic wine composition. Sensorially, for certain sites and vintages, panellists distinguished between wines made from high vs. low NDVI zones using a sorting task. UAV NDVI demonstrated the ability to determine areas within a vineyard block that could produce wines that were sensorially distinguishable from one another. https://oeno-one.eu/article/view/5352Remote sensingprecision viticulturecool-climateRieslingsensory
spellingShingle Briann Dorin
Andrew Reynolds
Marilyne Jollineau
Hyun-Suk Lee
Adam Shemrock
Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyards
OENO One
Remote sensing
precision viticulture
cool-climate
Riesling
sensory
title Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyards
title_full Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyards
title_fullStr Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyards
title_full_unstemmed Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyards
title_short Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyards
title_sort utilization of unmanned aerial vehicles for zonal winemaking in cool climate riesling vineyards
topic Remote sensing
precision viticulture
cool-climate
Riesling
sensory
url https://oeno-one.eu/article/view/5352
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AT marilynejollineau utilizationofunmannedaerialvehiclesforzonalwinemakingincoolclimaterieslingvineyards
AT hyunsuklee utilizationofunmannedaerialvehiclesforzonalwinemakingincoolclimaterieslingvineyards
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