Evidence map›Paper›PMID 38732427›Full record

ArticlePlants (Basel, Switzerland)2024

Precision Estimation of Crop Coefficient for Maize Cultivation Using High-Resolution Satellite Imagery to Enhance Evapotranspiration Assessment in Agriculture.

Attila Nagy, Nikolett Éva Kiss, Erika Buday-Bódi, Tamás Magyar, Francesco Cavazza, Salvatore Luca Gentile, Haidi Abdullah, János Tamás, Zsolt Zoltán Fehér

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Attila NagyFaculty of Agricultural and Food Sciences and Environmental Management, Institute of Water and Environmental Management, University of Debrecen, H-4032 Debrecen, Hungary.ORCID 0000-0003-1220-8231
Nikolett Éva KissFaculty of Agricultural and Food Sciences and Environmental Management, Institute of Water and Environmental Management, University of Debrecen, H-4032 Debrecen, Hungary.
Erika Buday-BódiFaculty of Agricultural and Food Sciences and Environmental Management, Institute of Water and Environmental Management, University of Debrecen, H-4032 Debrecen, Hungary.ORCID 0000-0003-2971-9214
Tamás MagyarFaculty of Agricultural and Food Sciences and Environmental Management, Institute of Water and Environmental Management, University of Debrecen, H-4032 Debrecen, Hungary.ORCID 0000-0002-3973-6053
Francesco CavazzaConsorzio di Bonifica Canale Emiliano Romagnolo, Via E. Masi 8, 40137 Bologna, Italy.ORCID 0000-0002-3097-8865
Salvatore Luca GentileConsorzio di Bonifica Canale Emiliano Romagnolo, Via E. Masi 8, 40137 Bologna, Italy.
Haidi AbdullahFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Drienerlolaan 5, P.O. Box 217, 7500 AE Enschede, The Netherlands.ORCID 0000-0003-3059-9045
János TamásFaculty of Agricultural and Food Sciences and Environmental Management, Institute of Water and Environmental Management, University of Debrecen, H-4032 Debrecen, Hungary.
Zsolt Zoltán FehérFaculty of Agricultural and Food Sciences and Environmental Management, Institute of Water and Environmental Management, University of Debrecen, H-4032 Debrecen, Hungary.ORCID 0009-0007-6659-4197

Funding

European Union's Horizon 2020 "WATERAGRI Water retention and nutrient recycling in soils and streams for improved agricultural production" Grant Agreement No. 858375
6 · The paper itself

Abstract

The estimation of crop evapotranspiration (ETc) is crucial for irrigation water management, especially in arid regions. This can be particularly relevant in the Po Valley (Italy), where arable lands suffer from drought damages on an annual basis, causing drastic crop yield losses. This study presents a novel approach for vegetation-based estimation of crop evapotranspiration (ETc) for maize. Three years of high-resolution multispectral satellite (Sentinel-2)-based Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Red Edge Index (NDRE), and Leaf Area Index (LAI) time series data were used to derive crop coefficients of maize in nine plots at the Acqua Campus experimental farm of Irrigation Consortium for the Emilia Romagna Canal (CER), Italy. Since certain vegetation indices (VIs) (such as NDVI) have an exponential nature compared to the other indices, both linear and power regression models were evaluated to estimate the crop coefficient (K

Indexed as

maize water demandSentinel-2vegetation index-based crop evapotranspirationvegetation index-based Kc

Identifiers

PMID38732427
PMCPMC11085199

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.