Are unmanned aerial vehicle-based hyperspectral imaging and machine learning advancing crop science?
hyperspectral imagery
machine learning
precision agriculture
remote sensing
unmanned aerial vehicle (UAV)
Journal
Trends in plant science
ISSN: 1878-4372
Titre abrégé: Trends Plant Sci
Pays: England
ID NLM: 9890299
Informations de publication
Date de publication:
04 Oct 2023
04 Oct 2023
Historique:
received:
13
10
2022
revised:
07
08
2023
accepted:
05
09
2023
medline:
7
10
2023
pubmed:
7
10
2023
entrez:
6
10
2023
Statut:
aheadofprint
Résumé
The past few years have seen increased interest in unmanned aerial vehicle (UAV)-based hyperspectral imaging (HSI) and machine learning (ML) in agricultural research, concomitant with an increase in published research on these topics. We provide an updated review, written for agriculturalists, highlighting the benefits in the retrieval of biophysical parameters of crops via UAVs relative to less sophisticated options. We reviewed >70 recent papers and found few consistent results between similar studies. Owing to their high complexity and cost, especially when applied to crops of low value, the benefits of most of the research reviewed are difficult to explain. Future effort will be necessary to distill research findings into lower-cost options for end-users.
Identifiants
pubmed: 37802693
pii: S1360-1385(23)00294-7
doi: 10.1016/j.tplants.2023.09.001
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests The authors have no interests to declare.