Precision agriculture and the digital contributions for site-specific management of the fields

Detalhes bibliográficos
Autor(a) principal: Molin,Jose Paulo
Data de Publicação: 2020
Outros Autores: Bazame,Helizani Couto, Maldaner,Leonardo, Corredo,Lucas de Paula, Martello,Mauricio
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista ciência agronômica (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000500408
Resumo: ABSTRACT Site-specific management practices have been possible due to the wide range of solutions for data acquisition and interventions at the field level. Different approaches have to be considered for data collection, like dedicated soil and plant sensors, or even associated with the capacity of the agricultural machinery to generate valuable data that allows the farmer or the manager to infer the spatial variability of the fields. However, high computational resources are needed to convert extensive databases into useful information for site-specific management. Thus, technologies from industry, such as the Internet of Things and Artificial Intelligence, applied to agricultural production, have supported the decision-making process of precision agriculture practices. The interpretation and the integration of information from different sources of data allow enhancement of agricultural management due to its capacity to predict attributes of the crop and soil using advanced data-driven tools. Some examples are crop monitoring, local applications of inputs, and disease detection using cloud-based systems in digital platforms, previously elaborated for decision-support systems. In this review, we discuss the different approaches and technological resources, popularly named as Agriculture 4.0 or digital farming, inserted in the context of the management of spatial variability of the fields considering different sources of crop and soil data.
id UFC-2_4f171b2963f717f80d11b64f3c73acaf
oai_identifier_str oai:scielo:S1806-66902020000500408
network_acronym_str UFC-2
network_name_str Revista ciência agronômica (Online)
repository_id_str
spelling Precision agriculture and the digital contributions for site-specific management of the fieldsArtificial IntelligenceCloud ComputingDecision-support SystemInternet of ThingsABSTRACT Site-specific management practices have been possible due to the wide range of solutions for data acquisition and interventions at the field level. Different approaches have to be considered for data collection, like dedicated soil and plant sensors, or even associated with the capacity of the agricultural machinery to generate valuable data that allows the farmer or the manager to infer the spatial variability of the fields. However, high computational resources are needed to convert extensive databases into useful information for site-specific management. Thus, technologies from industry, such as the Internet of Things and Artificial Intelligence, applied to agricultural production, have supported the decision-making process of precision agriculture practices. The interpretation and the integration of information from different sources of data allow enhancement of agricultural management due to its capacity to predict attributes of the crop and soil using advanced data-driven tools. Some examples are crop monitoring, local applications of inputs, and disease detection using cloud-based systems in digital platforms, previously elaborated for decision-support systems. In this review, we discuss the different approaches and technological resources, popularly named as Agriculture 4.0 or digital farming, inserted in the context of the management of spatial variability of the fields considering different sources of crop and soil data.Universidade Federal do Ceará2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000500408Revista Ciência Agronômica v.51 n.spe 2020reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFC10.5935/1806-6690.20200088info:eu-repo/semantics/openAccessMolin,Jose PauloBazame,Helizani CoutoMaldaner,LeonardoCorredo,Lucas de PaulaMartello,MauricioMartello,Mauricioeng2021-08-17T00:00:00Zoai:scielo:S1806-66902020000500408Revistahttp://www.ccarevista.ufc.br/PUBhttps://old.scielo.br/oai/scielo-oai.php||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2021-08-17T00:00Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Precision agriculture and the digital contributions for site-specific management of the fields
title Precision agriculture and the digital contributions for site-specific management of the fields
spellingShingle Precision agriculture and the digital contributions for site-specific management of the fields
Molin,Jose Paulo
Artificial Intelligence
Cloud Computing
Decision-support System
Internet of Things
title_short Precision agriculture and the digital contributions for site-specific management of the fields
title_full Precision agriculture and the digital contributions for site-specific management of the fields
title_fullStr Precision agriculture and the digital contributions for site-specific management of the fields
title_full_unstemmed Precision agriculture and the digital contributions for site-specific management of the fields
title_sort Precision agriculture and the digital contributions for site-specific management of the fields
author Molin,Jose Paulo
author_facet Molin,Jose Paulo
Bazame,Helizani Couto
Maldaner,Leonardo
Corredo,Lucas de Paula
Martello,Mauricio
author_role author
author2 Bazame,Helizani Couto
Maldaner,Leonardo
Corredo,Lucas de Paula
Martello,Mauricio
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Molin,Jose Paulo
Bazame,Helizani Couto
Maldaner,Leonardo
Corredo,Lucas de Paula
Martello,Mauricio
Martello,Mauricio
dc.subject.por.fl_str_mv Artificial Intelligence
Cloud Computing
Decision-support System
Internet of Things
topic Artificial Intelligence
Cloud Computing
Decision-support System
Internet of Things
description ABSTRACT Site-specific management practices have been possible due to the wide range of solutions for data acquisition and interventions at the field level. Different approaches have to be considered for data collection, like dedicated soil and plant sensors, or even associated with the capacity of the agricultural machinery to generate valuable data that allows the farmer or the manager to infer the spatial variability of the fields. However, high computational resources are needed to convert extensive databases into useful information for site-specific management. Thus, technologies from industry, such as the Internet of Things and Artificial Intelligence, applied to agricultural production, have supported the decision-making process of precision agriculture practices. The interpretation and the integration of information from different sources of data allow enhancement of agricultural management due to its capacity to predict attributes of the crop and soil using advanced data-driven tools. Some examples are crop monitoring, local applications of inputs, and disease detection using cloud-based systems in digital platforms, previously elaborated for decision-support systems. In this review, we discuss the different approaches and technological resources, popularly named as Agriculture 4.0 or digital farming, inserted in the context of the management of spatial variability of the fields considering different sources of crop and soil data.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000500408
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000500408
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.5935/1806-6690.20200088
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Universidade Federal do Ceará
publisher.none.fl_str_mv Universidade Federal do Ceará
dc.source.none.fl_str_mv Revista Ciência Agronômica v.51 n.spe 2020
reponame:Revista ciência agronômica (Online)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Revista ciência agronômica (Online)
collection Revista ciência agronômica (Online)
repository.name.fl_str_mv Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv ||alekdutra@ufc.br|| ccarev@ufc.br
_version_ 1750297489929404416