Leaf area estimate of Pennisetum glaucum by linear dimensions

Detalhes bibliográficos
Autor(a) principal: Leite, Mauricio Luiz de Mello Vieira
Data de Publicação: 2019
Outros Autores: Lucena, Leandro Ricardo Rodrigues de, Cruz, Manoela Gomes da, Sá Júnior, Eduardo Henrique de, Simões, Vicente José Laamon Pinto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta Scientiarum. Animal Sciences (Online)
Texto Completo: https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808
Resumo: Leaf area measurements are of the main parameters used in agronomic studies to evaluate plant growth. The current study used a non-destructive method based on linear leaf dimensions (length and width) to select the regression model to estimate millet (Pennisetum glaucum) leaf area. For two millet genotype (IPA BULK 1 BF and ADR 300) 128 randomly-chosen leaves were measured at different vegetative growth stages. Measures of length and width of each leaf were made using digital calipers. Leaf area was measured using a gravimetric method. The best-fit leaf area estimation model was selected via linear, potential and gamma regression models. Leaf area values varied from 3.02 to 209.21 cm2. The average value was 95.31 cm2. The potential regression model exhibited lower residual sum of squares and Akaike's information criterion and similar determination coefficient and Willmott index. Thus, potential regression was more efficient in explaining the leaf area of millet, independent of the genotype, when compared to other models evaluated in this research. Length (L) and width (W) could be used in the following potential regression model  to estimate millet leaf blade.
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spelling Leaf area estimate of Pennisetum glaucum by linear dimensionsleaf blademilletmodelingnon-destructive method.Leaf area measurements are of the main parameters used in agronomic studies to evaluate plant growth. The current study used a non-destructive method based on linear leaf dimensions (length and width) to select the regression model to estimate millet (Pennisetum glaucum) leaf area. For two millet genotype (IPA BULK 1 BF and ADR 300) 128 randomly-chosen leaves were measured at different vegetative growth stages. Measures of length and width of each leaf were made using digital calipers. Leaf area was measured using a gravimetric method. The best-fit leaf area estimation model was selected via linear, potential and gamma regression models. Leaf area values varied from 3.02 to 209.21 cm2. The average value was 95.31 cm2. The potential regression model exhibited lower residual sum of squares and Akaike's information criterion and similar determination coefficient and Willmott index. Thus, potential regression was more efficient in explaining the leaf area of millet, independent of the genotype, when compared to other models evaluated in this research. Length (L) and width (W) could be used in the following potential regression model  to estimate millet leaf blade.Editora da Universidade Estadual de Maringá2019-02-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/vnd.openxmlformats-officedocument.wordprocessingml.documenthttps://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/4280810.4025/actascianimsci.v41i1.42808Acta Scientiarum. Animal Sciences; Vol 41 (2019): Publicação Contínua; e42808Acta Scientiarum. Animal Sciences; v. 41 (2019): Publicação Contínua; e428081807-86721806-2636reponame:Acta Scientiarum. Animal Sciences (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttps://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808/pdfhttps://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808/751375147232https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808/751375147233Copyright (c) 2019 Acta Scientiarum. Animal Scienceshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessLeite, Mauricio Luiz de Mello VieiraLucena, Leandro Ricardo Rodrigues deCruz, Manoela Gomes daSá Júnior, Eduardo Henrique deSimões, Vicente José Laamon Pinto2019-07-17T08:32:20Zoai:periodicos.uem.br/ojs:article/42808Revistahttp://www.periodicos.uem.br/ojs/index.php/ActaSciAnimSciPUBhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAnimSci/oaiactaanim@uem.br||actaanim@uem.br|| rev.acta@gmail.com1807-86721806-2636opendoar:2019-07-17T08:32:20Acta Scientiarum. Animal Sciences (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Leaf area estimate of Pennisetum glaucum by linear dimensions
title Leaf area estimate of Pennisetum glaucum by linear dimensions
spellingShingle Leaf area estimate of Pennisetum glaucum by linear dimensions
Leite, Mauricio Luiz de Mello Vieira
leaf blade
millet
modeling
non-destructive method.
title_short Leaf area estimate of Pennisetum glaucum by linear dimensions
title_full Leaf area estimate of Pennisetum glaucum by linear dimensions
title_fullStr Leaf area estimate of Pennisetum glaucum by linear dimensions
title_full_unstemmed Leaf area estimate of Pennisetum glaucum by linear dimensions
title_sort Leaf area estimate of Pennisetum glaucum by linear dimensions
author Leite, Mauricio Luiz de Mello Vieira
author_facet Leite, Mauricio Luiz de Mello Vieira
Lucena, Leandro Ricardo Rodrigues de
Cruz, Manoela Gomes da
Sá Júnior, Eduardo Henrique de
Simões, Vicente José Laamon Pinto
author_role author
author2 Lucena, Leandro Ricardo Rodrigues de
Cruz, Manoela Gomes da
Sá Júnior, Eduardo Henrique de
Simões, Vicente José Laamon Pinto
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Leite, Mauricio Luiz de Mello Vieira
Lucena, Leandro Ricardo Rodrigues de
Cruz, Manoela Gomes da
Sá Júnior, Eduardo Henrique de
Simões, Vicente José Laamon Pinto
dc.subject.por.fl_str_mv leaf blade
millet
modeling
non-destructive method.
topic leaf blade
millet
modeling
non-destructive method.
description Leaf area measurements are of the main parameters used in agronomic studies to evaluate plant growth. The current study used a non-destructive method based on linear leaf dimensions (length and width) to select the regression model to estimate millet (Pennisetum glaucum) leaf area. For two millet genotype (IPA BULK 1 BF and ADR 300) 128 randomly-chosen leaves were measured at different vegetative growth stages. Measures of length and width of each leaf were made using digital calipers. Leaf area was measured using a gravimetric method. The best-fit leaf area estimation model was selected via linear, potential and gamma regression models. Leaf area values varied from 3.02 to 209.21 cm2. The average value was 95.31 cm2. The potential regression model exhibited lower residual sum of squares and Akaike's information criterion and similar determination coefficient and Willmott index. Thus, potential regression was more efficient in explaining the leaf area of millet, independent of the genotype, when compared to other models evaluated in this research. Length (L) and width (W) could be used in the following potential regression model  to estimate millet leaf blade.
publishDate 2019
dc.date.none.fl_str_mv 2019-02-13
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://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808
10.4025/actascianimsci.v41i1.42808
url https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808
identifier_str_mv 10.4025/actascianimsci.v41i1.42808
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808/pdf
https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808/751375147232
https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/42808/751375147233
dc.rights.driver.fl_str_mv Copyright (c) 2019 Acta Scientiarum. Animal Sciences
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2019 Acta Scientiarum. Animal Sciences
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/vnd.openxmlformats-officedocument.wordprocessingml.document
application/vnd.openxmlformats-officedocument.wordprocessingml.document
dc.publisher.none.fl_str_mv Editora da Universidade Estadual de Maringá
publisher.none.fl_str_mv Editora da Universidade Estadual de Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Animal Sciences; Vol 41 (2019): Publicação Contínua; e42808
Acta Scientiarum. Animal Sciences; v. 41 (2019): Publicação Contínua; e42808
1807-8672
1806-2636
reponame:Acta Scientiarum. Animal Sciences (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta Scientiarum. Animal Sciences (Online)
collection Acta Scientiarum. Animal Sciences (Online)
repository.name.fl_str_mv Acta Scientiarum. Animal Sciences (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv actaanim@uem.br||actaanim@uem.br|| rev.acta@gmail.com
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