Abstract
Soil texture, topographical data, fruit zone light measurements, yield components, and fruit composition data were taken from 125 locations in each of four Vitis vinifera L. cv. Cabernet Sauvignon vineyards in the Lodi region of California during the 2017, 2018, and 2019 seasons. Data were compared against three sources of normalized difference vegetation index (NDVI) with different spatial resolutions: Landsat 8 (LS8NDVI; 30 m), Sentinel-2 (S2NDVI; 10 m), and manned aircraft (at high resolution, HR) with the interrow removed (HRNDVI; 20 cm). The manned aircraft also captured canopy temperature (CT) derived from infrared (thermal) wavelengths (HRCT; 40 cm) for additional comparisons. HRNDVI was inversely related to HRCT, as well as to several chemical components of fruit composition including tannins and anthocyanins. While some constituents of fruit composition such as anthocyanins may be related to NDVI, canopy temperature, and/or indirect measurements collected in the field, results presented here suggest that yield and fruit composition have a strong seasonal response and therefore environmental conditions should be considered if more accurate predictions are desired. Furthermore, freely available public satellite data sources with mixed canopy and interrow pixels, such as Sentinel-2 and Landsat 8, provided similar information related to predicting specific fruit composition parameters compared to higher resolution imagery from contracted manned aircraft, from which the interrow signal was removed. Growers and wineries interested in predicting fruit composition that accounts for spatial variability may be able to conserve resources by using publicly available imagery sources and small numbers of targeted samples to achieve this goal.
- objective measures of fruit quality
- precision viticulture
- principal components analysis
- remote sensing of vegetation
- vineyard variability
- Vitis vinifera cv. Cabernet Sauvignon
- Received September 2021.
- Revision received November 2021.
- Revision received November 2021.
- Revision received November 2021.
- Accepted December 2021.
- Published online April 2022
This is an open access article distributed under the CC BY license (https://creativecommons.org/licenses/by/4.0/).