Cargando…
Electrophysiological assessment of plant status outside a Faraday cage using supervised machine learning
Living organisms have evolved complex signaling networks to drive appropriate physiological processes in response to changing environmental conditions. Amongst them, electric signals are a universal method to rapidly transmit information. In animals, bioelectrical activity measurements in the heart...
Autores principales: | Tran, Daniel, Dutoit, Fabien, Najdenovska, Elena, Wallbridge, Nigel, Plummer, Carrol, Mazza, Marco, Raileanu, Laura Elena, Camps, Cédric |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864072/ https://www.ncbi.nlm.nih.gov/pubmed/31745185 http://dx.doi.org/10.1038/s41598-019-53675-4 |
Ejemplares similares
-
Detecting stress caused by nitrogen deficit using deep learning techniques applied on plant electrophysiological data
por: González I Juclà, Daniel, et al.
Publicado: (2023) -
Faraday cage in the Adams' Hall
Publicado: (1955) -
Work inside the Faraday cage of the PS
por: CERN PhotoLab
Publicado: (1961) -
Preinjector for Linac 1, Faraday cage
Publicado: (1974) -
Preinjector for Linac 1, inside the Faraday cage
Publicado: (1974)