Plant Physiological Analysis to Overcome Limitations to Plant Phenotyping.
LiDAR
climate resilience
deep-learning
hyperspectral
partial least squares regression
phenomics
photosynthesis
plant ecophysiology
spectral reflectance
Journal
Plants (Basel, Switzerland)
ISSN: 2223-7747
Titre abrégé: Plants (Basel)
Pays: Switzerland
ID NLM: 101596181
Informations de publication
Date de publication:
29 Nov 2023
29 Nov 2023
Historique:
received:
31
10
2023
revised:
24
11
2023
accepted:
26
11
2023
medline:
9
12
2023
pubmed:
9
12
2023
entrez:
9
12
2023
Statut:
epublish
Résumé
Plant physiological status is the interaction between the plant genome and the prevailing growth conditions. Accurate characterization of plant physiology is, therefore, fundamental to effective plant phenotyping studies; particularly those focused on identifying traits associated with improved yield, lower input requirements, and climate resilience. Here, we outline the approaches used to assess plant physiology and how these techniques of direct empirical observations of processes such as photosynthetic CO
Identifiants
pubmed: 38068650
pii: plants12234015
doi: 10.3390/plants12234015
pmc: PMC10708318
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
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