Evaluating management practices in precision agriculture for maize yield with spatial econometrics

Detalhes bibliográficos
Autor(a) principal: Santos, Nuno
Data de Publicação: 2022
Outros Autores: Proença, Isabel, Canavarro, Mariana
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/28078
Resumo: Precision agriculture (PA) aims to provide data on soil, nutrient use, irrigation, and crops, to guide management strategic decisions towards an efficient use of inputs, increasing production and avoiding environmental problems due to excessive accumulation of fertilizers. In this paper, PA data from a large Portuguese farm producing maize were used to assess the effectiveness of agronomic management decisions concerning fertilizer and nutrient use, seed choice, and water content, in terms of crop productivity. The maize yield in 2017 and 2018 was modelled as a function of manageable inputs and unmanageable factors introduced as control variables. Panel spatial econometric methods were used for specification and estimation, to control for spatial dependence and spatial heterogeneity. The model proved to fit the data remarkably well and could be a good reference for specifying models to explain maize production; thus, helping researchers who need to deal with the huge amount of data that normally originates from PA. Additionally, it can be considered another tool for farm managers, helping in the design and evaluation of their agronomic management decisions.
id RCAP_f6dda70f327fec196100035d6e7bb3fb
oai_identifier_str oai:www.repository.utl.pt:10400.5/28078
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Evaluating management practices in precision agriculture for maize yield with spatial econometricsPrecision AgricultureAgronomic ManagementMaize YieldSpatial PanelsSpatial Regression ModelsPrecision agriculture (PA) aims to provide data on soil, nutrient use, irrigation, and crops, to guide management strategic decisions towards an efficient use of inputs, increasing production and avoiding environmental problems due to excessive accumulation of fertilizers. In this paper, PA data from a large Portuguese farm producing maize were used to assess the effectiveness of agronomic management decisions concerning fertilizer and nutrient use, seed choice, and water content, in terms of crop productivity. The maize yield in 2017 and 2018 was modelled as a function of manageable inputs and unmanageable factors introduced as control variables. Panel spatial econometric methods were used for specification and estimation, to control for spatial dependence and spatial heterogeneity. The model proved to fit the data remarkably well and could be a good reference for specifying models to explain maize production; thus, helping researchers who need to deal with the huge amount of data that normally originates from PA. Additionally, it can be considered another tool for farm managers, helping in the design and evaluation of their agronomic management decisions.MDPIRepositório da Universidade de LisboaSantos, NunoProença, IsabelCanavarro, Mariana2023-08-02T21:52:53Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/28078engSantos, Nuno; Isabel Proença and Mariana Canavarro .(2022). “Evaluating management practices in precision agriculture for maize yield with spatial econometrics”. Standard, Vol. 2, No. 2: pp. 121-135. https://doi.org/10.3390/standards2020010 . (Search PDF in 2023).10.3390/standards20200102305-6703info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-13T01:31:05Zoai:www.repository.utl.pt:10400.5/28078Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:26:55.747397Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Evaluating management practices in precision agriculture for maize yield with spatial econometrics
title Evaluating management practices in precision agriculture for maize yield with spatial econometrics
spellingShingle Evaluating management practices in precision agriculture for maize yield with spatial econometrics
Santos, Nuno
Precision Agriculture
Agronomic Management
Maize Yield
Spatial Panels
Spatial Regression Models
title_short Evaluating management practices in precision agriculture for maize yield with spatial econometrics
title_full Evaluating management practices in precision agriculture for maize yield with spatial econometrics
title_fullStr Evaluating management practices in precision agriculture for maize yield with spatial econometrics
title_full_unstemmed Evaluating management practices in precision agriculture for maize yield with spatial econometrics
title_sort Evaluating management practices in precision agriculture for maize yield with spatial econometrics
author Santos, Nuno
author_facet Santos, Nuno
Proença, Isabel
Canavarro, Mariana
author_role author
author2 Proença, Isabel
Canavarro, Mariana
author2_role author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Santos, Nuno
Proença, Isabel
Canavarro, Mariana
dc.subject.por.fl_str_mv Precision Agriculture
Agronomic Management
Maize Yield
Spatial Panels
Spatial Regression Models
topic Precision Agriculture
Agronomic Management
Maize Yield
Spatial Panels
Spatial Regression Models
description Precision agriculture (PA) aims to provide data on soil, nutrient use, irrigation, and crops, to guide management strategic decisions towards an efficient use of inputs, increasing production and avoiding environmental problems due to excessive accumulation of fertilizers. In this paper, PA data from a large Portuguese farm producing maize were used to assess the effectiveness of agronomic management decisions concerning fertilizer and nutrient use, seed choice, and water content, in terms of crop productivity. The maize yield in 2017 and 2018 was modelled as a function of manageable inputs and unmanageable factors introduced as control variables. Panel spatial econometric methods were used for specification and estimation, to control for spatial dependence and spatial heterogeneity. The model proved to fit the data remarkably well and could be a good reference for specifying models to explain maize production; thus, helping researchers who need to deal with the huge amount of data that normally originates from PA. Additionally, it can be considered another tool for farm managers, helping in the design and evaluation of their agronomic management decisions.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
2023-08-02T21:52:53Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/28078
url http://hdl.handle.net/10400.5/28078
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Santos, Nuno; Isabel Proença and Mariana Canavarro .(2022). “Evaluating management practices in precision agriculture for maize yield with spatial econometrics”. Standard, Vol. 2, No. 2: pp. 121-135. https://doi.org/10.3390/standards2020010 . (Search PDF in 2023).
10.3390/standards2020010
2305-6703
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799133537548369920