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

Abstract

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.