Vineyard water stress evaluation using a multispectral index: a case study in the Chianti area

Considering climate change, water management in viticulture is becoming increasingly important for quality and yield of the grapes. Precision irrigation allows to achieve these goals through optimizing water use. This approach is particularly advantageous to supply specific irrigation in water limited conditions, but it requires a quick and accurate identification of the grapevine water status and its variability in the vineyard. Traditional sensing methods require specific equipment and long elaboration steps that cannot be easily used by all the wineries. In vineyards, normalized difference vegetation index (NDVI) is currently largely detected to evaluate the variability of plant characteristics. Monitoring the crop water status using NDVI would allow to have a rapid and simple support for the irrigation management. The objective of the study is to set a site-specific model able to estimate the grapevine water stress and its variability at different phenological stages, using NDVI as input. The experiment was carried out in 2018 in a 'Sangiovese' vineyard located in the Chianti area, Tuscany (Italy). Data were collected on July 18 and August 23 in 15 analysis stations for the calibration and 12 stations for the validation of the model. In each station, NDVI index was measured using proximal and remote (sentinel 2) multispectral sensors. The water stress was estimated using a portable thermal camera through the crop water stress index (CWSI), analyzing 9 repetitions per station. A square regression model was set for each phenological stage, using NDVI as predictor. Models were calibrated for proximal (July 18, R²=0.578; August 23 R²=0.573) and remote (July 18, R²=0.476) sensing and they were validated for proximal (July 18, R²=0.658; August 23, R²=0.545) and for remote (July 18, R²=0.466). Results show that NDVI was able to predict the water status of the studied vineyard, thus the obtained models can be used for a site-specific water management.