Combining mobile proximal soil sensors and a crop model to produce high spatial resolution yield prediction maps
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F25%3A00638306" target="_blank" >RIV/86652079:_____/25:00638306 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s11119-025-10274-w" target="_blank" >https://link.springer.com/article/10.1007/s11119-025-10274-w</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11119-025-10274-w" target="_blank" >10.1007/s11119-025-10274-w</a>
Alternative languages
Result language
angličtina
Original language name
Combining mobile proximal soil sensors and a crop model to produce high spatial resolution yield prediction maps
Original language description
Purpose:Precision agriculture requires detailed knowledge of the within-field variation of nyield forming factors and the productivity potential of each area of the field. The goal of this nwork was to use a case study to test all the steps of the process of creating a crop modelnbased yield map from soil mobile soil sensors and determine the impact of uncertainties and ninaccuracies on the results.nMethods: Soil texture maps (0- 90 cm of depth) of a field were derived from mobile sennsors and used as input for the process based deterministic crop growth model HERMES nto produce a high-resolution yield map.Results Compared to actual yield maps, the simnulated yield map successfully identified the major differences in productivity within the nfield, although some spatial variation was lost during the simulation, mostly at the point of ntranslating soil texture maps into soil water retention parameters. The model also showed na tendency to overestimate yield across the entire field. A crop model simulation based on nmeasured soil parameters resulted in a yield prediction accuracy of about 10% higher than na simulation based on estimated (mapped) soil parameters.nConclusion: The loss of spatial variability, although measurable, occurred at a scale that nmight not have a significant impact on the site-specific management plan. Most yield map ninaccuracies can be attributed more to model calibration than to the mapping process itself.
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
Precision Agriculture
ISSN
1385-2256
e-ISSN
1573-1618
Volume of the periodical
26
Issue of the periodical within the volume
5
Country of publishing house
DE - GERMANY
Number of pages
25
Pages from-to
79
UT code for WoS article
001550042400001
EID of the result in the Scopus database
2-s2.0-105013461379