Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)

One of the fields of research in precision agriculture (PA) is the delineation of potential management zones (PMZs, also known as site-specific management zones, or simply management zones). To delineate PMZs, cluster analysis is the main used and recommended methodology. For cluster analysis, mainl...

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Autores: Martínez Casasnovas, José Antonio, Escolà i Agustí, Alexandre, Arnó Satorra, Jaume
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/64519
Acceso en línea:https://doi.org/10.3390/agriculture8060084
http://hdl.handle.net/10459.1/64519
Access Level:acceso abierto
Palabra clave:Sentinel-2
accumulated NDVI
Apparent electrical conductivity
Topography
cluster analysis
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spelling Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)Martínez Casasnovas, José AntonioEscolà i Agustí, AlexandreArnó Satorra, JaumeSentinel-2accumulated NDVIApparent electrical conductivityTopographycluster analysisOne of the fields of research in precision agriculture (PA) is the delineation of potential management zones (PMZs, also known as site-specific management zones, or simply management zones). To delineate PMZs, cluster analysis is the main used and recommended methodology. For cluster analysis, mainly yield maps, remote sensing multispectral indices, apparent soil electrical conductivity (ECa), and topography data are used. Nevertheless, there is still no accepted protocol or guidelines for establishing PMZs, and different solutions exist. In addition, the farmer's expert knowledge is not usually taken into account in the delineation process. The objective of the present work was to propose a methodology to delineate potential management zones for differential crop management that expresses the productive potential of the soil within a field. The Management Zone Analyst (MZA) software, which implements a fuzzy c-means algorithm, was used to create different alternatives of PMZ that were validated with yield data in a maize (Zea mays L.) field. The farmers' expert knowledge was then taken into account to improve the resulting PMZs that best fitted to the yield spatial variability pattern. This knowledge was considered highly valuable information that could be also very useful for deciding management actions to be taken to reduce within-field variability.This research was funded by the contract C16022 between the University of Lleida and Ventafarinas, S.L. (Lleida, Spain).MDPI2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.3390/agriculture8060084http://hdl.handle.net/10459.1/64519reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.3390/agriculture8060084Agriculture, 2018, vol. 8, (6), 84, p. 1-18cc-by (c) Martínez et al., 2018info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/oai:recercat.cat:10459.1/645192026-05-29T05:05:01Z
dc.title.none.fl_str_mv Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)
title Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)
spellingShingle Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)
Martínez Casasnovas, José Antonio
Sentinel-2
accumulated NDVI
Apparent electrical conductivity
Topography
cluster analysis
title_short Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)
title_full Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)
title_fullStr Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)
title_full_unstemmed Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)
title_sort Use of farmer knowledge in the delineation of potential management zones in precision agriculture: a case study in maize (Zea mays L.)
dc.creator.none.fl_str_mv Martínez Casasnovas, José Antonio
Escolà i Agustí, Alexandre
Arnó Satorra, Jaume
author Martínez Casasnovas, José Antonio
author_facet Martínez Casasnovas, José Antonio
Escolà i Agustí, Alexandre
Arnó Satorra, Jaume
author_role author
author2 Escolà i Agustí, Alexandre
Arnó Satorra, Jaume
author2_role author
author
dc.subject.none.fl_str_mv Sentinel-2
accumulated NDVI
Apparent electrical conductivity
Topography
cluster analysis
topic Sentinel-2
accumulated NDVI
Apparent electrical conductivity
Topography
cluster analysis
description One of the fields of research in precision agriculture (PA) is the delineation of potential management zones (PMZs, also known as site-specific management zones, or simply management zones). To delineate PMZs, cluster analysis is the main used and recommended methodology. For cluster analysis, mainly yield maps, remote sensing multispectral indices, apparent soil electrical conductivity (ECa), and topography data are used. Nevertheless, there is still no accepted protocol or guidelines for establishing PMZs, and different solutions exist. In addition, the farmer's expert knowledge is not usually taken into account in the delineation process. The objective of the present work was to propose a methodology to delineate potential management zones for differential crop management that expresses the productive potential of the soil within a field. The Management Zone Analyst (MZA) software, which implements a fuzzy c-means algorithm, was used to create different alternatives of PMZ that were validated with yield data in a maize (Zea mays L.) field. The farmers' expert knowledge was then taken into account to improve the resulting PMZs that best fitted to the yield spatial variability pattern. This knowledge was considered highly valuable information that could be also very useful for deciding management actions to be taken to reduce within-field variability.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/agriculture8060084
http://hdl.handle.net/10459.1/64519
url https://doi.org/10.3390/agriculture8060084
http://hdl.handle.net/10459.1/64519
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.3390/agriculture8060084
Agriculture, 2018, vol. 8, (6), 84, p. 1-18
dc.rights.none.fl_str_mv cc-by (c) Martínez et al., 2018
info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv cc-by (c) Martínez et al., 2018
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
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