Comparison of Proximal and Remote Sensing for the Diagnosis of Crop Status in Site-Specific Crop Management.

ISARIA N crop sensor Sentinel nitrogen remote sensing variable rate application

Journal

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

Informations de publication

Date de publication:
22 Dec 2021
Historique:
received: 22 10 2021
revised: 07 12 2021
accepted: 15 12 2021
entrez: 11 1 2022
pubmed: 12 1 2022
medline: 13 1 2022
Statut: epublish

Résumé

The presented paper deals with the issue of selecting a suitable system for monitoring the winter wheat crop in order to determine its condition as a basis for variable applications of nitrogen fertilizers. In a four-year (2017-2020) field experiment, 1400 ha of winter wheat crop were monitored using the ISARIA on-the-go system and remote sensing using Sentinel-2 multispectral satellite images. The results of spectral measurements of ISARIA vegetation indices (IRMI, IBI) were statistically compared with the values of selected vegetation indices obtained from Sentinel-2 (EVI, GNDVI, NDMI, NDRE, NDVI and NRERI) in order to determine potential hips. Positive correlations were found between the vegetation indices determined by the ISARIA system and indices obtained by multispectral images from Sentinel-2 satellites. The correlations were medium to strong (r = 0.51-0.89). Therefore, it can be stated that both technologies were able to capture a similar trend in the development of vegetation. Furthermore, the influence of climatic conditions on the vegetation indices was analyzed in individual years of the experiment. The values of vegetation indices show significant differences between the individual years. The results of vegetation indices obtained by the analysis of spectral images from Sentinel-2 satellites varied the most. The values of winter wheat yield varied between the individual years. Yield was the highest in 2017 (7.83 t/ha), while the lowest was recorded in 2020 (6.96 t/ha). There was no statistically significant difference between 2018 (7.27 t/ha) and 2019 (7.44 t/ha).

Identifiants

pubmed: 35009565
pii: s22010019
doi: 10.3390/s22010019
pmc: PMC8747194
pii:
doi:

Substances chimiques

Nitrogen N762921K75

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Mendel University in Brno
ID : AF-IGA2020-IP054
Organisme : Mendel University in Brno
ID : AF-IGA2021-IP073

Références

Sensors (Basel). 2013 Aug 16;13(8):10823-43
pubmed: 23959242
Environ Manage. 2013 Oct;52(4):1023-39
pubmed: 23974904
Sensors (Basel). 2018 Mar 15;18(3):
pubmed: 29543736

Auteurs

Jiří Mezera (J)

Department of Agrosystems and Bioclimatology, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic.

Vojtěch Lukas (V)

Department of Agrosystems and Bioclimatology, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic.

Igor Horniaček (I)

Department of Agrosystems and Bioclimatology, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic.

Vladimír Smutný (V)

Department of Agrosystems and Bioclimatology, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic.

Jakub Elbl (J)

Department of Agrosystems and Bioclimatology, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic.

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