Estimation of buckwheat leaf area by leaf dimensions

Detalhes bibliográficos
Autor(a) principal: Cargnelutti Filho, Alberto
Data de Publicação: 2021
Outros Autores: Pezzini, Rafael Vieira, Neu, Ismael Mario Márcio, Dumke, Gabriel Elias
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Semina. Ciências Agrárias (Online)
Texto Completo: https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/41574
Resumo: The objective of this work was to model and identify the best models for estimating the leaf area, determined by digital photos, of buckwheat (Fagopyrum esculentum Moench) of the cultivars IPR91-Baili and IPR92-Altar, as a function of length (L), width (W) or length x width product (LW) of the leaf blade. Ten uniformity trials (blank experiments) were carried out, five with IPR91-Baili cultivar and five with IPR92-Altar cultivar. The trials were performed on five sowing dates. In each trial and cultivar, expanded leaves were collected at random from the lower, middle and upper segments of the plants, totaling 1,815 leaves. In these 1,815 leaves, L and W were measured and the LW of the leaf blade was calculated, which were used as independent variables in the model. The leaf area of each leaf was determined using the digital photo method (Y), which was used as a dependent variable of the model. For each sowing date, cultivar and thirds of the plant, 80% of the leaves (1,452 leaves) were randomly separated for the generation of the models and 20% of the leaves (363 leaves) for the validation of the models of leaf area estimation as a function of linear dimensions. For buckwheat, IPR91-Baili and IPR92-Altar cultivars, the quadratic model (Y = 0.5217 + 0.6581LW + 0.0004LW2, R2 = 0.9590), power model (Y = 0.6809LW1.0037, R2 = 0.9587), linear model (Y = 0.0653 + 0.6892LW, R2 = 0.9587) and linear model without intercept (Y = 0.6907LW, R2 = 0.9587) are indicated for the estimation of leaf area determined by digital photos (Y) based on the LW of the leaf blade (x), and, preferably, the linear model without intercept can be used, due to its greater simplicity.
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spelling Estimation of buckwheat leaf area by leaf dimensionsEstimação de área foliar de trigo mourisco por dimensões foliaresLeaf area by digital photosFagopyrum esculentum MoenchNon-destructive methodModelingBuckwheat.Leaf area by digital photosFagopyrum esculentum MoenchNon-destructive methodModelingBuckwheat.The objective of this work was to model and identify the best models for estimating the leaf area, determined by digital photos, of buckwheat (Fagopyrum esculentum Moench) of the cultivars IPR91-Baili and IPR92-Altar, as a function of length (L), width (W) or length x width product (LW) of the leaf blade. Ten uniformity trials (blank experiments) were carried out, five with IPR91-Baili cultivar and five with IPR92-Altar cultivar. The trials were performed on five sowing dates. In each trial and cultivar, expanded leaves were collected at random from the lower, middle and upper segments of the plants, totaling 1,815 leaves. In these 1,815 leaves, L and W were measured and the LW of the leaf blade was calculated, which were used as independent variables in the model. The leaf area of each leaf was determined using the digital photo method (Y), which was used as a dependent variable of the model. For each sowing date, cultivar and thirds of the plant, 80% of the leaves (1,452 leaves) were randomly separated for the generation of the models and 20% of the leaves (363 leaves) for the validation of the models of leaf area estimation as a function of linear dimensions. For buckwheat, IPR91-Baili and IPR92-Altar cultivars, the quadratic model (Y = 0.5217 + 0.6581LW + 0.0004LW2, R2 = 0.9590), power model (Y = 0.6809LW1.0037, R2 = 0.9587), linear model (Y = 0.0653 + 0.6892LW, R2 = 0.9587) and linear model without intercept (Y = 0.6907LW, R2 = 0.9587) are indicated for the estimation of leaf area determined by digital photos (Y) based on the LW of the leaf blade (x), and, preferably, the linear model without intercept can be used, due to its greater simplicity.O objetivo deste trabalho foi modelar e identificar os melhores modelos para a estimação da área foliar determinada por fotos digitais, de trigo mourisco (Fagopyrum esculentum Moench) das cultivares IPR91-Baili e IPR92-Altar, em função do comprimento, ou da largura e/ou do produto comprimento vezes largura do limbo foliar. Foram conduzidos dez ensaios de uniformidade (experimentos em branco), sendo cinco com a cultivar IPR91-Baili e cinco com a cultivar IPR92-Altar. Os ensaios foram realizados em cinco datas de semeadura. Em cada ensaio e cultivar foram coletadas, aleatoriamente, folhas expandidas dos terços inferior, médio e superior das plantas, totalizando 1.815 folhas. Nessas 1.815 folhas, foram mensurados o comprimento (C) e a largura (L) e calculado o produto do comprimento vezes a largura (CL) do limbo foliar. Determinou-se a área foliar de cada folha, por meio do método de fotos digitais (Y). Para cada data de semeadura, cultivar e terços da planta foram separadas, aleatoriamente, 80% das folhas (1.452 folhas) para a geração de modelos e 20% das folhas (363 folhas) para a validação dos modelos de estimação da área foliar em função das dimensões lineares. Para o trigo mourisco, cultivares IPR91-Baili e IPR92-Altar, os modelos quadrático (? = 0,5217 + 0,6581x + 0,0004x2, R2 = 0,9590), potência (? = 0,6809x1,0037, R2 = 0,9587), linear (? = 0,0653 + 0,6892x, R2 = 0,9587) e linear sem intercepto (? = 0,6907x, R2 = 0,9587), são indicados para a estimação da área foliar determinada por fotos digitais (Y) com base no produto comprimento vezes largura do limbo foliar (x), podendo, preferencialmente, ser utilizado o modelo linear sem intercepto, devido a sua maior simplicidade.UEL2021-04-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPesquisa Científicaapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/4157410.5433/1679-0359.2021v42n3Supl1p1529Semina: Ciências Agrárias; Vol. 42 No. 3Supl1 (2021); 1529-1548Semina: Ciências Agrárias; v. 42 n. 3Supl1 (2021); 1529-15481679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELenghttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/41574/29439Copyright (c) 2021 Semina: Ciências Agráriashttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessCargnelutti Filho, AlbertoPezzini, Rafael VieiraNeu, Ismael Mario MárcioDumke, Gabriel Elias2022-09-30T15:56:50Zoai:ojs.pkp.sfu.ca:article/41574Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2022-09-30T15:56:50Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false
dc.title.none.fl_str_mv Estimation of buckwheat leaf area by leaf dimensions
Estimação de área foliar de trigo mourisco por dimensões foliares
title Estimation of buckwheat leaf area by leaf dimensions
spellingShingle Estimation of buckwheat leaf area by leaf dimensions
Cargnelutti Filho, Alberto
Leaf area by digital photos
Fagopyrum esculentum Moench
Non-destructive method
Modeling
Buckwheat.
Leaf area by digital photos
Fagopyrum esculentum Moench
Non-destructive method
Modeling
Buckwheat.
title_short Estimation of buckwheat leaf area by leaf dimensions
title_full Estimation of buckwheat leaf area by leaf dimensions
title_fullStr Estimation of buckwheat leaf area by leaf dimensions
title_full_unstemmed Estimation of buckwheat leaf area by leaf dimensions
title_sort Estimation of buckwheat leaf area by leaf dimensions
author Cargnelutti Filho, Alberto
author_facet Cargnelutti Filho, Alberto
Pezzini, Rafael Vieira
Neu, Ismael Mario Márcio
Dumke, Gabriel Elias
author_role author
author2 Pezzini, Rafael Vieira
Neu, Ismael Mario Márcio
Dumke, Gabriel Elias
author2_role author
author
author
dc.contributor.author.fl_str_mv Cargnelutti Filho, Alberto
Pezzini, Rafael Vieira
Neu, Ismael Mario Márcio
Dumke, Gabriel Elias
dc.subject.por.fl_str_mv Leaf area by digital photos
Fagopyrum esculentum Moench
Non-destructive method
Modeling
Buckwheat.
Leaf area by digital photos
Fagopyrum esculentum Moench
Non-destructive method
Modeling
Buckwheat.
topic Leaf area by digital photos
Fagopyrum esculentum Moench
Non-destructive method
Modeling
Buckwheat.
Leaf area by digital photos
Fagopyrum esculentum Moench
Non-destructive method
Modeling
Buckwheat.
description The objective of this work was to model and identify the best models for estimating the leaf area, determined by digital photos, of buckwheat (Fagopyrum esculentum Moench) of the cultivars IPR91-Baili and IPR92-Altar, as a function of length (L), width (W) or length x width product (LW) of the leaf blade. Ten uniformity trials (blank experiments) were carried out, five with IPR91-Baili cultivar and five with IPR92-Altar cultivar. The trials were performed on five sowing dates. In each trial and cultivar, expanded leaves were collected at random from the lower, middle and upper segments of the plants, totaling 1,815 leaves. In these 1,815 leaves, L and W were measured and the LW of the leaf blade was calculated, which were used as independent variables in the model. The leaf area of each leaf was determined using the digital photo method (Y), which was used as a dependent variable of the model. For each sowing date, cultivar and thirds of the plant, 80% of the leaves (1,452 leaves) were randomly separated for the generation of the models and 20% of the leaves (363 leaves) for the validation of the models of leaf area estimation as a function of linear dimensions. For buckwheat, IPR91-Baili and IPR92-Altar cultivars, the quadratic model (Y = 0.5217 + 0.6581LW + 0.0004LW2, R2 = 0.9590), power model (Y = 0.6809LW1.0037, R2 = 0.9587), linear model (Y = 0.0653 + 0.6892LW, R2 = 0.9587) and linear model without intercept (Y = 0.6907LW, R2 = 0.9587) are indicated for the estimation of leaf area determined by digital photos (Y) based on the LW of the leaf blade (x), and, preferably, the linear model without intercept can be used, due to its greater simplicity.
publishDate 2021
dc.date.none.fl_str_mv 2021-04-22
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Pesquisa Científica
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/41574
10.5433/1679-0359.2021v42n3Supl1p1529
url https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/41574
identifier_str_mv 10.5433/1679-0359.2021v42n3Supl1p1529
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/41574/29439
dc.rights.driver.fl_str_mv Copyright (c) 2021 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv UEL
publisher.none.fl_str_mv UEL
dc.source.none.fl_str_mv Semina: Ciências Agrárias; Vol. 42 No. 3Supl1 (2021); 1529-1548
Semina: Ciências Agrárias; v. 42 n. 3Supl1 (2021); 1529-1548
1679-0359
1676-546X
reponame:Semina. Ciências Agrárias (Online)
instname:Universidade Estadual de Londrina (UEL)
instacron:UEL
instname_str Universidade Estadual de Londrina (UEL)
instacron_str UEL
institution UEL
reponame_str Semina. Ciências Agrárias (Online)
collection Semina. Ciências Agrárias (Online)
repository.name.fl_str_mv Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)
repository.mail.fl_str_mv semina.agrarias@uel.br
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