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Machine learning produces higher prediction accuracy than the Jarvis-type model of climatic control on stomatal conductance in a dryland wheat agro-ecosystem

Alireza Houshmandfar, G. O'Leary, Glenn J. Fitzgerald, Yang Chen, Sabine Tausz‐Posch, Kurt K. Benke, Shihab Uddin, Michael Tausz

2021Agricultural and Forest Meteorology18 citationsDOIOpen Access PDF

Topics & Concepts

Stomatal conductanceSupport vector machineVapour Pressure DeficitMachine learningRandom forestArtificial intelligencePhotosynthetically active radiationBiometeorologyEnvironmental scienceComputer scienceTranspirationEcologyBotanyCanopyPhotosynthesisBiologyPlant responses to elevated CO2Plant Water Relations and Carbon DynamicsAtmospheric chemistry and aerosols
Machine learning produces higher prediction accuracy than the Jarvis-type model of climatic control on stomatal conductance in a dryland wheat agro-ecosystem | Litcius