Correlation of yield and vegetation indices from unmanned aerial vehicle multispectral imagery in Thailand rice production systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F25%3A00635882" target="_blank" >RIV/86652079:_____/25:00635882 - isvavai.cz</a>
Alternative codes found
RIV/62156489:43210/25:43927007
Result on the web
<a href="https://acsess.onlinelibrary.wiley.com/doi/10.1002/agg2.70107" target="_blank" >https://acsess.onlinelibrary.wiley.com/doi/10.1002/agg2.70107</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/agg2.70107" target="_blank" >10.1002/agg2.70107</a>
Alternative languages
Result language
angličtina
Original language name
Correlation of yield and vegetation indices from unmanned aerial vehicle multispectral imagery in Thailand rice production systems
Original language description
Unmanned aerial vehicles (UAVs) equipped with cameras are used for collecting vegetation indices (VIs) for health monitoring of field crops such as rice (Oryza sativa). This study evaluated the relationship of VIs derived from multispectral UAV images at different buffer zones around the sampling points with rice biomass and grain yield from 20 nonirrigated and irrigated fields in Sakhon Nakhon, Thailand, in 2021. Varying nitrogen (N) rates (21.8-98.7 kg ha-1) were applied in splits, at 14 days after transplanting and panicle initiation (PI) stage. One week after PI, multispectral images were captured by a DJI Phantom 4 Multispectral UAV before taking biomass samples at four 1-m2 sampling points for the three plots in each field. At harvest, whole plant samples were collected from nearby these sampling points for grain yield estimation. For each sampling point at buffer zones 5, 10, and 20 m, the average of four VIs (normalized difference vegetation index [NDVI], green NDVI [GNDVI], normalized difference red-edge [NDRE], and optimized soil adjusted vegetation index [OSAVI]) was computed. Correlation analysis showed NDRE had the highest correlation with grain yield in nonirrigated systems (r = 0.575-0.613) and pooled data (r = 0.523-0.539). NDVI moderately correlated with biomass (r = 0.224-0.233). Images within the 10-m buffer zone produced NDRE values most strongly linked to yield, both unadjusted and normalized by planting to sensing days and growing degree days. There is a potential to use NDRE as predictor of rice biomass yield in rice systems.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
40101 - Agriculture
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Agrosystems Geosciences & Environment
ISSN
2639-6696
e-ISSN
2639-6696
Volume of the periodical
8
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
e70107
UT code for WoS article
001482449900001
EID of the result in the Scopus database
2-s2.0-105004643937