Estimation of total leaf area in perennial plants using image analysis
Autor(a) principal: | |
---|---|
Data de Publicação: | 2011 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/1234 |
Resumo: | One feature of most horticultural crop plants that is biologically relevant to their yield and productivity is total leaf area. However, direct methods of estimation of the leaf area cause damage to the plants, whereas indirect methods such as based on light measurement, demand accuracy in the setup of the measurement procedure, which is specific to each crop. Coffee is one of the most important perennial plants related to worldwide trade, and this demands some ability to estimate the productivity of the crop, as well as all the perennial plants involved in production of agricultural products. This study aims to build a model based on indirect measures to estimate the leaf area in coffee plants using image analysis. Two models were evaluated, one based on the height and width of the canopies, and other based on the area of the digital image of a tree. The results of the models have been compared with the real area of the leaves using the destructive approach with measurement of area of all the leaves using a digital scanner. Comparisons between the models and the real values indicated values of adjusted R2 of about 0.82 with a model using the height and the width values, and about 0.91 in the second model which used the area projection. The robustness of the model using the height and the width values were tested using data presented in the literature to other cultivars and achieved R2 = 0.54 with an outlier point and 0.91 without it. |
id |
UFLA_5a1b0df68837de01ba5f8f5fb853f310 |
---|---|
oai_identifier_str |
oai:localhost:1/1234 |
network_acronym_str |
UFLA |
network_name_str |
Repositório Institucional da UFLA |
repository_id_str |
|
spelling |
Estimation of total leaf area in perennial plants using image analysisEstimativa da área foliar total de culturas perenes por meio de análise de imagensCafeeiroModeloMétodo não destrutivoCoffee treeModelNon-destructive methodOne feature of most horticultural crop plants that is biologically relevant to their yield and productivity is total leaf area. However, direct methods of estimation of the leaf area cause damage to the plants, whereas indirect methods such as based on light measurement, demand accuracy in the setup of the measurement procedure, which is specific to each crop. Coffee is one of the most important perennial plants related to worldwide trade, and this demands some ability to estimate the productivity of the crop, as well as all the perennial plants involved in production of agricultural products. This study aims to build a model based on indirect measures to estimate the leaf area in coffee plants using image analysis. Two models were evaluated, one based on the height and width of the canopies, and other based on the area of the digital image of a tree. The results of the models have been compared with the real area of the leaves using the destructive approach with measurement of area of all the leaves using a digital scanner. Comparisons between the models and the real values indicated values of adjusted R2 of about 0.82 with a model using the height and the width values, and about 0.91 in the second model which used the area projection. The robustness of the model using the height and the width values were tested using data presented in the literature to other cultivars and achieved R2 = 0.54 with an outlier point and 0.91 without it.A área foliar é um atributo biológico relevante para a produtividade de culturas comerciais. Os métodos diretos de estimação da área foliar causam dano às plantas, enquanto os indiretos, como aqueles baseados na medição da quantidade de luz no interior da planta, exigem ajustes e protocolos de medição específicos para cada tipo de cultura. O cafeeiro é uma das mais importantes plantas perenes relacionadas ao comércio de produtos agrícolas em escala mundial, o que demanda habilidade de estimar sua produtividade, tal como ocorre para as outras culturas perenes. Este trabalho visa construir um modelo que contenha um método indireto de estimativa de área foliar em cafeeiros por meio da análise de imagens. Dois modelos foram analisados, sendo que em um foram usadas a altura e a largura dos dosséis e, no outro, se baseou na área projetada do dossel. Os resultados foram comparados com o método direto, através do qual se retiraram todas as folhas dos cafeeiros o que permitiu observar valores de R2 ajustado de 0,82 para o modelo em que se usaram a altura e a largura dos dosséis, e de 0,91 para o modelo da área projetada. A robustez do método da altura e largura foi testada usando-se dados de literatura relativos a outra cultivar oferecendo valores de R2 de 0,54, considerando-se um ponto fora da curva, e de 0,91 sem se considerar este ponto.2013-10-18T12:32:30Z2013-10-18T12:32:30Z2011info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfMARCON, M. et al. Estimation of total leaf area in perennial plants using image analysis. Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, v. 15, n. 1, p. 96-101, jan. 2011.http://repositorio.ufla.br/jspui/handle/1/1234Revista Brasileira de Engenharia Agrícola e Ambientalreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAMarcon, MarlonMariano, KleberBraga Júnior, Roberto AlvesPaglis, Carlos MaurícioScalco, Myriane StellaHorgan, Graham W.info:eu-repo/semantics/openAccesseng2023-05-26T18:58:20Zoai:localhost:1/1234Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-26T18:58:20Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Estimation of total leaf area in perennial plants using image analysis Estimativa da área foliar total de culturas perenes por meio de análise de imagens |
title |
Estimation of total leaf area in perennial plants using image analysis |
spellingShingle |
Estimation of total leaf area in perennial plants using image analysis Marcon, Marlon Cafeeiro Modelo Método não destrutivo Coffee tree Model Non-destructive method |
title_short |
Estimation of total leaf area in perennial plants using image analysis |
title_full |
Estimation of total leaf area in perennial plants using image analysis |
title_fullStr |
Estimation of total leaf area in perennial plants using image analysis |
title_full_unstemmed |
Estimation of total leaf area in perennial plants using image analysis |
title_sort |
Estimation of total leaf area in perennial plants using image analysis |
author |
Marcon, Marlon |
author_facet |
Marcon, Marlon Mariano, Kleber Braga Júnior, Roberto Alves Paglis, Carlos Maurício Scalco, Myriane Stella Horgan, Graham W. |
author_role |
author |
author2 |
Mariano, Kleber Braga Júnior, Roberto Alves Paglis, Carlos Maurício Scalco, Myriane Stella Horgan, Graham W. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Marcon, Marlon Mariano, Kleber Braga Júnior, Roberto Alves Paglis, Carlos Maurício Scalco, Myriane Stella Horgan, Graham W. |
dc.subject.por.fl_str_mv |
Cafeeiro Modelo Método não destrutivo Coffee tree Model Non-destructive method |
topic |
Cafeeiro Modelo Método não destrutivo Coffee tree Model Non-destructive method |
description |
One feature of most horticultural crop plants that is biologically relevant to their yield and productivity is total leaf area. However, direct methods of estimation of the leaf area cause damage to the plants, whereas indirect methods such as based on light measurement, demand accuracy in the setup of the measurement procedure, which is specific to each crop. Coffee is one of the most important perennial plants related to worldwide trade, and this demands some ability to estimate the productivity of the crop, as well as all the perennial plants involved in production of agricultural products. This study aims to build a model based on indirect measures to estimate the leaf area in coffee plants using image analysis. Two models were evaluated, one based on the height and width of the canopies, and other based on the area of the digital image of a tree. The results of the models have been compared with the real area of the leaves using the destructive approach with measurement of area of all the leaves using a digital scanner. Comparisons between the models and the real values indicated values of adjusted R2 of about 0.82 with a model using the height and the width values, and about 0.91 in the second model which used the area projection. The robustness of the model using the height and the width values were tested using data presented in the literature to other cultivars and achieved R2 = 0.54 with an outlier point and 0.91 without it. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011 2013-10-18T12:32:30Z 2013-10-18T12:32:30Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
MARCON, M. et al. Estimation of total leaf area in perennial plants using image analysis. Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, v. 15, n. 1, p. 96-101, jan. 2011. http://repositorio.ufla.br/jspui/handle/1/1234 |
identifier_str_mv |
MARCON, M. et al. Estimation of total leaf area in perennial plants using image analysis. Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, v. 15, n. 1, p. 96-101, jan. 2011. |
url |
http://repositorio.ufla.br/jspui/handle/1/1234 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1815439011023421440 |