Leaf area estimate of Pennisetum glaucum by linear dimensions
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
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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Acta Scientiarum. Animal Sciences (Online) |
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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 |
_version_ |
1799315362378940416 |