Abstract
Spectral-based vegetation indices (VI) have been shown to be good proxies of grapevine stem water potential (Ψstem), assisting in irrigation decision-making for commercial vineyards. However, VI-Ψstem correlations are mostly reported at the leaf or canopy scales, using proximal canopy-based sensors or very-high-spatial resolution images derived from sensors mounted on small airplanes or drones. Here, for the first time, we take advantage of high-spatial resolution (3-m) near-daily images acquired from Planet’s nano-satellite constellation to derive VI-Ψstem correlations at the vineyard scale. Weekly Ψstem was measured along the growing season of 2017 in six vines each in 81 commercial vineyards and in 60 pairs of grapevines in a 2.4 ha experimental vineyard in Israel. The Clip application programming interface (API), provided by Planet, and the Google Earth Engine platform were used to derive spatially continuous time series of four VIs—GNDVI, NDVI, EVI and SAVI—in the 82 vineyards. Results show that per-week multivariable linear models using variables extracted from VI time series successfully tracked spatial variations in Ψstem across the experimental vineyard (Pearson’s-r = 0.45–0.84; N = 60). A simple linear regression model enabled monitoring seasonal changes in Ψstem along the growing season in the vineyard (r = 0.80–0.82). Planet VIs and seasonal Ψstem data from the 82 vineyards were used to derive a ‘global’ model for in-season monitoring of Ψstem at the vineyard-level (r = 0.78; RMSE = 18.5%; N = 970). The ‘global’ model, which requires only a few VI variables extracted from Planet images, may be used for real-time weekly assessment of Ψstem in Mediterranean vineyards, substantially improving the efficiency of conventional in-field monitoring efforts.
Highlights
Deficit irrigation is a commonly used irrigation strategy in vineyards aiming to achieve high-quality berries for premium wine production [1]
We examine the use of simple regression and multivariable linear models, with several vegetation indices (VI)-based metrics extracted from the VI time series, to predict spatio-temporal variability in Ψstem along the growing season
The relationship between stem water potential and vegetation indices was evaluated in Mediterranean vineyards through the use of high spatial resolution Planet nano-satellite imaging on the freely available Google Earth Engine (GEE) cloud computing system for the first time
Summary
Deficit irrigation is a commonly used irrigation strategy in vineyards aiming to achieve high-quality berries for premium wine production [1]. Proper irrigation management is compulsory to achieve uniform quality of berries across the vineyard area. An effective method to guide irrigation management of wine grapes is continuous spatial (across the vineyard) and temporal (along the season) monitoring of grapevine water status [2]. To achieve an accurate picture of the water status variability across the entire vineyard area, continuous Ψstem measurements are required from as many vines as possible. This task requires substantial human resources, making it time consuming
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