A Hebrew University study suggests AI tools could help growers better manage water use by predicting healthy plant behavior and flagging early signs of stress.
A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant ...
A research team has developed a low-cost, high-throughput phenotyping platform that continuously measures plant transpiration ...
A proper mechanistic understanding of how whole-tree transpiration varies as a function of environmental conditions is essential for predicting how vegetation will respond to climate change, ...
Cornell University researchers have created the world's first synthetic tree. So far, it's a very small 'tree' which stands in a palm-sized piece of hydrogel. This 'tree simulates the process of ...
A new Israeli study suggests that machine-learning models may soon give growers a far more precise way to predict how much water their crops use each day, while also laying the groundwork for earlier ...
Plant and Soil, Vol. 412, No. 1/2, Part I: Special Issue: Belowground solutions to global challenges (March 2017), pp. 215-233 (19 pages) Aims: A soil-plant-atmosphere continuum (SPAC) model for ...
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