COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS
Autor(a) principal: | |
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Data de Publicação: | 2022 |
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=S0100-69162022000500206 |
Resumo: | ABSTRACT Peanut (Arachis hypogaea L.) is a legume belonging to the Fabaceae family, whose production aims at high pod yields and quality. This study aimed to investigate peanut physical traits and point out their relationship with total pod mass. Therefore, we evaluated total pod mass and the pod physical components: grain mass, pod shell mass, pod length, greatest and smallest transverse pod diameters, number of grains per pod, pod area, pod perimeter, and fruit volume. Initially, these morphological variables were correlated by Pearson’s coefficient, and a correlation network was used to graphically express the obtained results. Path analysis identified that pod total mass has a cause-and-effect relationship with the variables number of grains per pod, grain mass, and pod shell mass. As a result, these variables can be used in indirect selection for higher crop yields; therefore, monitoring pod total mass before harvest is a strategy to predict the final yield of peanuts. |
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COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICSPath analysislegumeproductionArachis hypogaea L.ABSTRACT Peanut (Arachis hypogaea L.) is a legume belonging to the Fabaceae family, whose production aims at high pod yields and quality. This study aimed to investigate peanut physical traits and point out their relationship with total pod mass. Therefore, we evaluated total pod mass and the pod physical components: grain mass, pod shell mass, pod length, greatest and smallest transverse pod diameters, number of grains per pod, pod area, pod perimeter, and fruit volume. Initially, these morphological variables were correlated by Pearson’s coefficient, and a correlation network was used to graphically express the obtained results. Path analysis identified that pod total mass has a cause-and-effect relationship with the variables number of grains per pod, grain mass, and pod shell mass. As a result, these variables can be used in indirect selection for higher crop yields; therefore, monitoring pod total mass before harvest is a strategy to predict the final yield of peanuts.Associação Brasileira de Engenharia Agrícola2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000500206Engenharia Agrícola v.42 n.5 2022reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v42n5e20220018/2022info:eu-repo/semantics/openAccessOliveira,Job T. deOliveira,Rubens A. deCunha,Fernando F. daSilva,Priscilla A.Teodoro,Paulo E.eng2022-11-04T00:00:00Zoai:scielo:S0100-69162022000500206Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2022-11-04T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS |
title |
COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS |
spellingShingle |
COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS Oliveira,Job T. de Path analysis legume production Arachis hypogaea L. |
title_short |
COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS |
title_full |
COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS |
title_fullStr |
COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS |
title_full_unstemmed |
COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS |
title_sort |
COMMERCIAL CLASSIFICATION OF PEANUTS BASED ON POD PHYSICAL CHARACTERISTICS |
author |
Oliveira,Job T. de |
author_facet |
Oliveira,Job T. de Oliveira,Rubens A. de Cunha,Fernando F. da Silva,Priscilla A. Teodoro,Paulo E. |
author_role |
author |
author2 |
Oliveira,Rubens A. de Cunha,Fernando F. da Silva,Priscilla A. Teodoro,Paulo E. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Oliveira,Job T. de Oliveira,Rubens A. de Cunha,Fernando F. da Silva,Priscilla A. Teodoro,Paulo E. |
dc.subject.por.fl_str_mv |
Path analysis legume production Arachis hypogaea L. |
topic |
Path analysis legume production Arachis hypogaea L. |
description |
ABSTRACT Peanut (Arachis hypogaea L.) is a legume belonging to the Fabaceae family, whose production aims at high pod yields and quality. This study aimed to investigate peanut physical traits and point out their relationship with total pod mass. Therefore, we evaluated total pod mass and the pod physical components: grain mass, pod shell mass, pod length, greatest and smallest transverse pod diameters, number of grains per pod, pod area, pod perimeter, and fruit volume. Initially, these morphological variables were correlated by Pearson’s coefficient, and a correlation network was used to graphically express the obtained results. Path analysis identified that pod total mass has a cause-and-effect relationship with the variables number of grains per pod, grain mass, and pod shell mass. As a result, these variables can be used in indirect selection for higher crop yields; therefore, monitoring pod total mass before harvest is a strategy to predict the final yield of peanuts. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
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=S0100-69162022000500206 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000500206 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-eng.agric.v42n5e20220018/2022 |
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.42 n.5 2022 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_ |
1752126275391062016 |