Remote Sensing, Yield, Physical Characteristics, and Fruit Composition Variability in Cabernet Sauvignon Vineyards

• DOI: 10.5344/ajev.2021.21038
• Publication Date: 2022-02-24T19:00:16Z
• Authors: Brent Sams; Robert G.V. Bramley; Luis Sanchez; Nick Dokoozlian; Christopher Ford; Vinay Pagay
• Keywords: 04 agricultural and veterinary sciences; 0405 other agricultural sciences

Soil texture, topographical data, fruit zone light measurements, yield components, and composition data were taken from 125 locations in each of four <i>Vitis vinifera</i> L. cv. Cabernet Sauvignon vineyards the Lodi region California during 2017, 2018, 2019 seasons. Data compared against three sources normalized difference vegetation index (NDVI) with different spatial resolutions: Landsat 8 (LS8_NDVI; 30 m), Sentinel-2 (S2_NDVI; 10 manned aircraft (at high resolution, HR) interrow removed (HR_NDVI; 20 cm). The also captured canopy temperature (CT) derived infrared (thermal) wavelengths (HR_CT; 40 cm) for additional comparisons. HR_NDVI was inversely related to HR_CT, as well several chemical components including tannins anthocyanins. While some constituents such anthocyanins may be NDVI, temperature, and/or indirect measurements collected field, results presented here suggest that have a strong seasonal response therefore environmental conditions should considered if more accurate predictions are desired. Furthermore, freely available public satellite mixed pixels, 8, provided similar information predicting specific parameters higher resolution imagery contracted aircraft, which signal removed. Growers wineries interested accounts variability able conserve resources by using publicly small numbers targeted samples achieve this goal.