Non-destructive evaluation of the leaf area of garlic crop using mathematical models
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Bioscience journal (Online) |
Texto Completo: | https://seer.ufu.br/index.php/biosciencejournal/article/view/42344 |
Resumo: | Growth measurements such as leaf area (LA) and dry matter (DM) are important in experiments about plants population, fertilization, irrigation and others parameters of cultivation, in garlic crop. The LA and DM are commonly defined as destructive, lengthy and cause loss of plants in the experimental units. The objective of this study was to fit mathematical models using linear models that estimate the leaf area and dry matter of garlic plants - variety Ito. For that, garlic plants were collected at 30, 45, 60, 75, 90, 115 and 120 days after planting. The measurements of width (W), length (L) of leaves, LA, DM, pseudostem diameter (PD), number of leaves per plant (NL) and height (H) were determined in each time. The models were fitted to estimate the LA or DM as function of the variables W, L, L*W, PD and LA. The statistical analysis of the linear regression, coefficient of determination of the linear regression (R2), root mean square error (RMSE), modified concordance index (d1) and the BIAS index were verified to determine the most representative models. It`s possible to estimate the LA and the leaf DM of garlic plants using the variables: length, width, pseudostem diameter and height of plants. |
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Non-destructive evaluation of the leaf area of garlic crop using mathematical modelsAvaliação não-destrutiva de área foliar da cultura do alho através de modelos matemáticosAllium sativum L.AlometryGrowth.Agricultural ScienceAllium sativum L..Alometria.Crescimento.Growth measurements such as leaf area (LA) and dry matter (DM) are important in experiments about plants population, fertilization, irrigation and others parameters of cultivation, in garlic crop. The LA and DM are commonly defined as destructive, lengthy and cause loss of plants in the experimental units. The objective of this study was to fit mathematical models using linear models that estimate the leaf area and dry matter of garlic plants - variety Ito. For that, garlic plants were collected at 30, 45, 60, 75, 90, 115 and 120 days after planting. The measurements of width (W), length (L) of leaves, LA, DM, pseudostem diameter (PD), number of leaves per plant (NL) and height (H) were determined in each time. The models were fitted to estimate the LA or DM as function of the variables W, L, L*W, PD and LA. The statistical analysis of the linear regression, coefficient of determination of the linear regression (R2), root mean square error (RMSE), modified concordance index (d1) and the BIAS index were verified to determine the most representative models. It`s possible to estimate the LA and the leaf DM of garlic plants using the variables: length, width, pseudostem diameter and height of plants.Medidas de crescimento como área foliar (AF) e matéria seca (MS) são importantes em experimentos com população de plantas, adubação, irrigação e outros parâmetros de cultivo, na cultura do alho. Muitas vezes a AF e MS são definidas por avaliações destrutivas, demoradas e com perdas de plantas nas unidades experimentais. Objetivou-se, com este trabalho, definir modelos matemáticos através de medidas lineares, que estimem a área foliar e a matéria seca das folhas de plantas de alho da variedade Ito. Para isso, quinze plantas foram coletadas aos 30, 45, 60, 75, 90, 115 e 120 dias após o plantio (DAP). As medidas de largura (L), comprimento (C) das folhas, AF, MS, diâmetro do pseudocaule (DP), número de folhas por planta (NF) e altura da planta (AP) foram determinadas em cada época. Ajustaram-se modelos para estimar a AF ou MS em função das variáveis L, C, L*C, DP e AF. Para determinar os modelos mais representativos foram verificados a análise estatística da regressão linear, o coeficiente de determinação da regressão linear (R2), raiz do quadrado médio do erro (RQME), índice de concordância modificado (d1) e o índice BIAS. É possível estimar a AF e MS foliar de plantas de alho através das variáveis comprimento, largura, diâmetro do pseudocaule e altura de plantas.EDUFU2020-08-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/biosciencejournal/article/view/4234410.14393/BJ-v36n5a2020-42344Bioscience Journal ; Vol. 36 No. 5 (2020): Sept./Oct.; 1600-1606Bioscience Journal ; v. 36 n. 5 (2020): Sept./Oct.; 1600-16061981-3163reponame:Bioscience journal (Online)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/biosciencejournal/article/view/42344/29617Brazil; ContemporaryCopyright (c) 2020 Felipe Augusto Reis Gonçalves, Marcelo de Paula Senoski, Thiago Picinatti Raposo, Leonardo Angelo de Aquino, Maria Elisa de Sena Fernandeshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGonçalves, Felipe Augusto ReisSenoski, Marcelo de PaulaRaposo, Thiago PicinattiAquino, Leonardo Angelo deFernandes, Maria Elisa de Sena2022-06-10T13:38:13Zoai:ojs.www.seer.ufu.br:article/42344Revistahttps://seer.ufu.br/index.php/biosciencejournalPUBhttps://seer.ufu.br/index.php/biosciencejournal/oaibiosciencej@ufu.br||1981-31631516-3725opendoar:2022-06-10T13:38:13Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)false |
dc.title.none.fl_str_mv |
Non-destructive evaluation of the leaf area of garlic crop using mathematical models Avaliação não-destrutiva de área foliar da cultura do alho através de modelos matemáticos |
title |
Non-destructive evaluation of the leaf area of garlic crop using mathematical models |
spellingShingle |
Non-destructive evaluation of the leaf area of garlic crop using mathematical models Gonçalves, Felipe Augusto Reis Allium sativum L. Alometry Growth. Agricultural Science Allium sativum L.. Alometria. Crescimento. |
title_short |
Non-destructive evaluation of the leaf area of garlic crop using mathematical models |
title_full |
Non-destructive evaluation of the leaf area of garlic crop using mathematical models |
title_fullStr |
Non-destructive evaluation of the leaf area of garlic crop using mathematical models |
title_full_unstemmed |
Non-destructive evaluation of the leaf area of garlic crop using mathematical models |
title_sort |
Non-destructive evaluation of the leaf area of garlic crop using mathematical models |
author |
Gonçalves, Felipe Augusto Reis |
author_facet |
Gonçalves, Felipe Augusto Reis Senoski, Marcelo de Paula Raposo, Thiago Picinatti Aquino, Leonardo Angelo de Fernandes, Maria Elisa de Sena |
author_role |
author |
author2 |
Senoski, Marcelo de Paula Raposo, Thiago Picinatti Aquino, Leonardo Angelo de Fernandes, Maria Elisa de Sena |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Gonçalves, Felipe Augusto Reis Senoski, Marcelo de Paula Raposo, Thiago Picinatti Aquino, Leonardo Angelo de Fernandes, Maria Elisa de Sena |
dc.subject.por.fl_str_mv |
Allium sativum L. Alometry Growth. Agricultural Science Allium sativum L.. Alometria. Crescimento. |
topic |
Allium sativum L. Alometry Growth. Agricultural Science Allium sativum L.. Alometria. Crescimento. |
description |
Growth measurements such as leaf area (LA) and dry matter (DM) are important in experiments about plants population, fertilization, irrigation and others parameters of cultivation, in garlic crop. The LA and DM are commonly defined as destructive, lengthy and cause loss of plants in the experimental units. The objective of this study was to fit mathematical models using linear models that estimate the leaf area and dry matter of garlic plants - variety Ito. For that, garlic plants were collected at 30, 45, 60, 75, 90, 115 and 120 days after planting. The measurements of width (W), length (L) of leaves, LA, DM, pseudostem diameter (PD), number of leaves per plant (NL) and height (H) were determined in each time. The models were fitted to estimate the LA or DM as function of the variables W, L, L*W, PD and LA. The statistical analysis of the linear regression, coefficient of determination of the linear regression (R2), root mean square error (RMSE), modified concordance index (d1) and the BIAS index were verified to determine the most representative models. It`s possible to estimate the LA and the leaf DM of garlic plants using the variables: length, width, pseudostem diameter and height of plants. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-13 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://seer.ufu.br/index.php/biosciencejournal/article/view/42344 10.14393/BJ-v36n5a2020-42344 |
url |
https://seer.ufu.br/index.php/biosciencejournal/article/view/42344 |
identifier_str_mv |
10.14393/BJ-v36n5a2020-42344 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://seer.ufu.br/index.php/biosciencejournal/article/view/42344/29617 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
Brazil; Contemporary |
dc.publisher.none.fl_str_mv |
EDUFU |
publisher.none.fl_str_mv |
EDUFU |
dc.source.none.fl_str_mv |
Bioscience Journal ; Vol. 36 No. 5 (2020): Sept./Oct.; 1600-1606 Bioscience Journal ; v. 36 n. 5 (2020): Sept./Oct.; 1600-1606 1981-3163 reponame:Bioscience journal (Online) instname:Universidade Federal de Uberlândia (UFU) instacron:UFU |
instname_str |
Universidade Federal de Uberlândia (UFU) |
instacron_str |
UFU |
institution |
UFU |
reponame_str |
Bioscience journal (Online) |
collection |
Bioscience journal (Online) |
repository.name.fl_str_mv |
Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU) |
repository.mail.fl_str_mv |
biosciencej@ufu.br|| |
_version_ |
1797069080364056576 |