Precision agriculture and the digital contributions for site-specific management of the fields
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , , |
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 |