Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000200266 |
Resumo: | Precision irrigation seeks to establish strategies which achieve an efficient ratio between the volume of water used (reduction in input) and the productivity obtained (increase in production). There are several studies in the literature on strategies for achieving this efficiency, such as those dealing with the method of volumetric water balance (VWB). However, it is also of great practical and economic interest to set up versatile implementations of irrigation strategies that: (i) maintain the performance obtained with other implementations, (ii) rely on few computational resources, (iii) adapt well to field conditions, and (iv) allow easy modification of the irrigation strategy. In this study, such characteristics are achieved when using an Artificial Neural Network (ANN) to determine the period of irrigation for a watermelon crop in the Irrigation Perimeter of the Lower Acaraú, in the state of Ceará, Brazil. The Volumetric Water Balance was taken as the standard for comparing the management carried out with the proposed implementation of ANN. The statistical analysis demonstrates the effectiveness of the proposed management, which is able to replace VWB as a strategy in automation. |
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Engenharia Agrícola |
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Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon cropprecision irrigationautomationneural algorithmsPrecision irrigation seeks to establish strategies which achieve an efficient ratio between the volume of water used (reduction in input) and the productivity obtained (increase in production). There are several studies in the literature on strategies for achieving this efficiency, such as those dealing with the method of volumetric water balance (VWB). However, it is also of great practical and economic interest to set up versatile implementations of irrigation strategies that: (i) maintain the performance obtained with other implementations, (ii) rely on few computational resources, (iii) adapt well to field conditions, and (iv) allow easy modification of the irrigation strategy. In this study, such characteristics are achieved when using an Artificial Neural Network (ANN) to determine the period of irrigation for a watermelon crop in the Irrigation Perimeter of the Lower Acaraú, in the state of Ceará, Brazil. The Volumetric Water Balance was taken as the standard for comparing the management carried out with the proposed implementation of ANN. The statistical analysis demonstrates the effectiveness of the proposed management, which is able to replace VWB as a strategy in automation.Associação Brasileira de Engenharia Agrícola2015-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000200266Engenharia Agrícola v.35 n.2 2015reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-Eng.Agric.v35n2p266-279/2015info:eu-repo/semantics/openAccessROCHA NETO,ODÍLIO C. DATEIXEIRA,ADUNIAS DOS S.BRAGA,ARTHUR P. DE S.SANTOS,CLEMILSON C. DOSLEÃO,RAIMUNDO A. DE O.eng2016-07-14T00:00:00Zoai:scielo:S0100-69162015000200266Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2016-07-14T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop |
title |
Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop |
spellingShingle |
Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop ROCHA NETO,ODÍLIO C. DA precision irrigation automation neural algorithms |
title_short |
Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop |
title_full |
Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop |
title_fullStr |
Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop |
title_full_unstemmed |
Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop |
title_sort |
Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop |
author |
ROCHA NETO,ODÍLIO C. DA |
author_facet |
ROCHA NETO,ODÍLIO C. DA TEIXEIRA,ADUNIAS DOS S. BRAGA,ARTHUR P. DE S. SANTOS,CLEMILSON C. DOS LEÃO,RAIMUNDO A. DE O. |
author_role |
author |
author2 |
TEIXEIRA,ADUNIAS DOS S. BRAGA,ARTHUR P. DE S. SANTOS,CLEMILSON C. DOS LEÃO,RAIMUNDO A. DE O. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
ROCHA NETO,ODÍLIO C. DA TEIXEIRA,ADUNIAS DOS S. BRAGA,ARTHUR P. DE S. SANTOS,CLEMILSON C. DOS LEÃO,RAIMUNDO A. DE O. |
dc.subject.por.fl_str_mv |
precision irrigation automation neural algorithms |
topic |
precision irrigation automation neural algorithms |
description |
Precision irrigation seeks to establish strategies which achieve an efficient ratio between the volume of water used (reduction in input) and the productivity obtained (increase in production). There are several studies in the literature on strategies for achieving this efficiency, such as those dealing with the method of volumetric water balance (VWB). However, it is also of great practical and economic interest to set up versatile implementations of irrigation strategies that: (i) maintain the performance obtained with other implementations, (ii) rely on few computational resources, (iii) adapt well to field conditions, and (iv) allow easy modification of the irrigation strategy. In this study, such characteristics are achieved when using an Artificial Neural Network (ANN) to determine the period of irrigation for a watermelon crop in the Irrigation Perimeter of the Lower Acaraú, in the state of Ceará, Brazil. The Volumetric Water Balance was taken as the standard for comparing the management carried out with the proposed implementation of ANN. The statistical analysis demonstrates the effectiveness of the proposed management, which is able to replace VWB as a strategy in automation. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-04-01 |
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=S0100-69162015000200266 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000200266 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-Eng.Agric.v35n2p266-279/2015 |
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 |
Associação Brasileira de Engenharia Agrícola |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
dc.source.none.fl_str_mv |
Engenharia Agrícola v.35 n.2 2015 reponame:Engenharia Agrícola instname:Associação Brasileira de Engenharia Agrícola (SBEA) instacron:SBEA |
instname_str |
Associação Brasileira de Engenharia Agrícola (SBEA) |
instacron_str |
SBEA |
institution |
SBEA |
reponame_str |
Engenharia Agrícola |
collection |
Engenharia Agrícola |
repository.name.fl_str_mv |
Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA) |
repository.mail.fl_str_mv |
revistasbea@sbea.org.br||sbea@sbea.org.br |
_version_ |
1752126272312442880 |