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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Detalhes bibliográficos

Principais autores:	Kiara Brewer, Alistair Clulow, Mbulisi Sibanda, Shaeden Gokool, John Odindi, Onisimo Mutanga, Vivek Naiken, Vimbayi G. P. Chimonyo, Tafadzwanashe Mabhaudhi
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2022-07-01
coleção:	Drones
Assuntos:	drones foliar temperature machine learning maize phenotyping precision agriculture smallholder farming systems
Acesso em linha:	https://www.mdpi.com/2504-446X/6/7/169
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