Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review.

Crops, Agricultural Hyperspectral Imaging Plant Diseases Remote Sensing Technology
cereals citrus early detection hyperspectral oil palm plant diseases remote sensing solanaceae

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
19 Jan 2022
Historique:
received: 25 10 2021
revised: 13 01 2022
accepted: 16 01 2022
entrez: 15 2 2022
pubmed: 16 2 2022
medline: 17 2 2022
Statut: epublish

Résumé

The development of hyperspectral remote sensing equipment, in recent years, has provided plant protection professionals with a new mechanism for assessing the phytosanitary state of crops. Semantically rich data coming from hyperspectral sensors are a prerequisite for the timely and rational implementation of plant protection measures. This review presents modern advances in early plant disease detection based on hyperspectral remote sensing. The review identifies current gaps in the methodologies of experiments. A further direction for experimental methodological development is indicated. A comparative study of the existing results is performed and a systematic table of different plants' disease detection by hyperspectral remote sensing is presented, including important wave bands and sensor model information.

Identifiants

DOI: 10.3390/s22030757 PMID: 35161504 PMC: PMC8839015
pubmed: 35161504
pii: s22030757
doi: 10.3390/s22030757
pmc: PMC8839015
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Ministry of Science and Higher Education of the Russian Federation
ID : World-class Research Center program: Advanced Digital Technologies (contract No. 075-15-2020-934 dated 17.11.2020)

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Auteurs

Anton Terentev (A)

All-Russian Institute of Plant Protection, 3 Podbelsokogo Str., Pushkin, 196608 Saint Petersburg, Russia.

Viktor Dolzhenko (V)

All-Russian Institute of Plant Protection, 3 Podbelsokogo Str., Pushkin, 196608 Saint Petersburg, Russia.

Alexander Fedotov (A)

World-Class Research Center «Advanced Digital Technologies», Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., 195251 Saint Petersburg, Russia.
ORCID: 0000-0002-7511-8076

Danila Eremenko (D)

World-Class Research Center «Advanced Digital Technologies», Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., 195251 Saint Petersburg, Russia.

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Classifications MeSH

questionsmedicales.fr › Aliments et boissons › Aliments › Produits agricoles › Current State of Hyperspectral Remote Sensing...
questionsmedicales.fr › Techniques d'investigation › Techniques de chimie analytique › Analyse spectrale › Imagerie hyperspectrale › Current State of Hyperspectral Remote Sensing...
questionsmedicales.fr › Phénomènes physiologiques des plantes › Maladies des plantes › Current State of Hyperspectral Remote Sensing...
questionsmedicales.fr › Sciences de l'information › Sources d'information › Moyens de communication › Télécommunications › Télémétrie › Technologie de télédétection › Current State of Hyperspectral Remote Sensing...