Estimation of Maize Foliar Temperature and Stomatal Conductance as Indicators of Water Stress Based on Optical and Thermal Imagery Acquired Using an Unmanned Aerial Vehicle (UAV) Platform

Estimation of Maize Foliar Temperature and Stomatal Conductance as Indicators of Water Stress Based on Optical and Thermal Imagery Acquired Using an Unmanned Aerial Vehicle (UAV) Platform

Climatic variability and extreme weather events impact agricultural production, especially in sub-Saharan smallholder cropping systems, which are commonly rainfed. Hence, the development of early warning systems regarding moisture availability can facilitate planning, mitigate losses and optimise yi...

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Bibliographic Details
Main Authors: Kiara Brewer, Alistair Clulow, Mbulisi Sibanda, Shaeden Gokool, John Odindi, Onisimo Mutanga, Vivek Naiken, Vimbayi G. P. Chimonyo, Tafadzwanashe Mabhaudhi
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Drones
Subjects:
drones
foliar temperature
machine learning
maize phenotyping
precision agriculture
smallholder farming systems
Online Access:https://www.mdpi.com/2504-446X/6/7/169

Internet

https://www.mdpi.com/2504-446X/6/7/169

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