A sensorless, Big Data based approach for phenology and meteorological drought forecasting in vineyards.

ABSTRACT: A web-based app was developed and tested to provide predictions of phenological stages of budburst, flowering and veraison, as well as warnings for meteorological drought. Such predictions are especially urgent under a climate change scenario where earlier phenology and water scarcity are increasingly frequent. By utilizing a calibration data set provided by 25 vineyards observed in the Emilia Romagna Region for two years (2021-2022), the above stages were predicted as per the binary event classification paradigm and selection of the best fitting algorithm based on the comparison between several metrics. The seasonal vineyard water balance was calculated by subtracting daily bare or grassed soil evapotranspiration (ET_s) and canopy transpiration (T_c) from the initial w

SUBMITTER: Canavera G 

PROVIDER: S-EPMC10556084 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature