Evidence map›Paper›PMID 35243753›Full record

ArticlePest management science2022

Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field.

Javier Plaza, Nilda Sánchez, Carmen García-Ariza, Rodrigo Pérez-Sánchez, Francisco Charfolé, Constantino Caminero-Saldaña

Abstract read
In one paragraph

Article in Pest management science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Javier PlazaPlant Production Group. Faculty of Environmental and Agricultural Sciences, University of Salamanca, Salamanca, Spain.ORCID https://orcid.org/0000-0002-8908-1606
Nilda SánchezPlant Production Group. Faculty of Environmental and Agricultural Sciences, University of Salamanca, Salamanca, Spain.ORCID https://orcid.org/0000-0002-8396-6550
Carmen García-ArizaPest Area. Technological Agricultural Institute of Castilla y León (ITACyL), Valladolid, Spain.
Rodrigo Pérez-SánchezPlant Production Group. Faculty of Environmental and Agricultural Sciences, University of Salamanca, Salamanca, Spain.ORCID https://orcid.org/0000-0001-5170-4698
Francisco CharfoléDepartment of Cartographic and Land Engineering, University of Salamanca, Ávila, Spain.
Constantino Caminero-SaldañaPest Area. Technological Agricultural Institute of Castilla y León (ITACyL), Valladolid, Spain.ORCID https://orcid.org/0000-0003-2381-3656

Funding

Diputación Provincial de PalenciaDiputación Provincial de ValladolidInstituto Tecnológico Agrario de Castilla y León (ITACyL)
6 · The paper itself

Abstract

backgroundThe common vole (Microtus arvalis) is a very destructive agricultural pest. Particularly in Europe, its monitoring is essential not only for adequate management and outbreak forecasting, but also for accurately determining the vole's impact on affected fields. In this study, several alternatives for estimating the damage to alfalfa fields by voles through unmanned vehicle systems (UASs) and multispectral cameras are presented. Currently, both the farmers and agencies involved in the integrated pest management (IPM) programs of voles do not have sufficiently precise methods for accurate assessments of the real impact to crops.

resultsOverall, the four multispectral classification methods presented showed similar performances. However, the normalized difference vegetation index (NDVI)-based segmentation exhibited the most accurate and reliable appraisal of the affected areas. Nevertheless, it must be noted that the simplest method, which was based on an automatic classification, provided results similar to those obtained by more complex methods. In addition, a significant direct relationship was found between the number of active burrows and damage to the alfalfa canopy.

conclusionUnmanned vehicle systems, combined with multispectral imagery classification, are an effective and easily transferable methodology for the assessment and monitoring of common vole damage to agricultural plots. This combination of methods facilitates decision-making processes for IPM control strategies against this pest. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Indexed as

ArvicolinaeCrops, AgriculturalAgricultureAnimalsEuropealfalfaclassificationMicrotus arvalis PallasmultispectralNDVIUAS

Identifiers

PMID35243753
PMCPMC9313580

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.