Nir Averbuch

This study uses machine learning models trained on gravimetric and environmental data to predict daily plant transpiration with high accuracy.

The paper introduces a wireless sensor network for continuous monitoring of plant-environment interactions, showing strong correlation between transpiration and biomass gain.

This study evaluates the accuracy of the FAO-56 Penman-Monteith equation in a greenhouse using microclimatic data and machine learning to predict evapotranspiration.