Invited Speaker

Abstract: Skilled regulated deficit irrigation regime is the basis for controlling grape yield and wine quality. High accuracy of grapevine evapotranspiration (ETc) modelling serves as a foundation for precise and efficient irrigation calculation. ETc measurements of Vitis vinifera ‘Cabernet Sauvignon’ were conducted during 2013-2017 with 6 drainage lysimeters in the mountainous region in Israel, along with a continuous record of meteorological data. The effect and interactions of meteorological variables (MV) such as temperature, total solar radiation, relative humidity and wind speed, as well as Leaf Area Index (LAI) on ETc were established. Different time-series multiple regression models (machine learning and non-linear models) were used to determine the relative influence of MV and LAI on ETc during four growing seasons and suggest several types of forecasting models for a fifth season. Additionally, within-season temporal patterns and variations according to five phenological stages (based on berry development) were studied. Finally, a comparison between different sets of variables and different regression models was performed to evaluate the quality of model fitting for ETc forecasting purposes. The findings show LAI had a pronounced impact on ETc compared to MVs and was found to have a relative influence ranging between 62 and 86% for the different growing seasons. Within each season, each phenological stage was characterized by a unique composition of relative importance of the predictor variables (MV, LAI and temporal predictors), with ETc variability being largely explained by the temporal variables. All non-linear regression models produced reliable results. Adding LAI data into the regression models resulted in improved models with higher levels of predictive performance. Using time-series statistics to explore meteorological and vegetative temporal characteristics, patterns, interrelations and relative influence on ETc may facilitate the understanding of plant response to meteorological conditions and ETc dynamics according to vegetative development, and assist in generating more precise and skillful applications of irrigation methods in the future.

Biography: Dr. Yishai Netzer is an applied field physiologist, specializing in viticulture. He received his MSc and PhD degrees from the Faculty of Agricultural, in the Hebrew University, Israel. His main research interests include skilled irrigation methods of table grapes and wine grapevines, and advanced approaches to evapotranspiration modeling. His field work involves multidisciplinary approaches to plant and soil relations, plant physiology, close and remote sensing, plant anatomy and wine quality.