Estimation of winter wheat nitrogen status and prediction of crop yield by satellite and proximal sensing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F21%3A43921650" target="_blank" >RIV/62156489:43210/21:43921650 - isvavai.cz</a>
Result on the web
<a href="https://mendelnet.cz/media/mnet_2021_full.pdf" target="_blank" >https://mendelnet.cz/media/mnet_2021_full.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Estimation of winter wheat nitrogen status and prediction of crop yield by satellite and proximal sensing
Original language description
Remote and proximal sensing of crop has been widely used in the last decades for agricultural applications, both for assessing vegetation condition and for subsequent yield prediction. In this work, we take advantage of vegetation indices for an advanced monitoring of spatial variability of winter wheat biophysical parameters, nitrogen status and prediction of crop yield estimation. Input data were obtained from farm field trials with winter wheat in 2019 and 2020 at Zdounky and Rašovice (Czech Republic) with a total area of 136 ha. To estimate the crop parameters, a plant sampling was realized in the stem elongation vegetation phase and later the grain sampling before harvest. Spectral properties were obtained from the satellite imagery of Sentinel-2 as the set of broadband vegetation indices (GNDVI, NDRE, NDVI, NRERI, RENDVI) and proximal crop sensor systems (Fritzmeier ISARIA, AgLeader OptRx). Spatial data were processed and analyzed using tools of geographic information systems and then statistically evaluated relationships between variables by using correlation analysis. The finding of high level of correlation between in-vegetation crop sensing and grain yield showed the possibility to identify yield spatial variability by both sensing systems in early stage of crop growth. This can be implemented for development of decision support tools for yield zoning in site specific crop management - precision farming.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
40101 - Agriculture
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
MendelNet 2021: Proceedings of International PhD Students Conference
ISBN
978-80-7509-821-4
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
55-60
Publisher name
Mendelova univerzita v Brně
Place of publication
Brno
Event location
Brno
Event date
Nov 10, 2021
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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