Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora)
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Publication Date: | 2008 |
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Format: | Article |
Language: | eng |
Source: | LOCUS Repositório Institucional da UFV |
Download full: | https://doi.org/10.1111/j.1744-7348.2008.00235.x http://www.locus.ufv.br/handle/123456789/22384 |
Summary: | We aimed to evaluate the currently used allometric models, as well as to propose a reliable and accurate model using non-destructive measurements of leaf length (L) and/or width (W), for estimating the area of leaves of eight field-grown coffee cultivars. For model construction, a total of 1563 leaves were randomly selected from different levels of the tree canopies and encompassed the full spectrum of measurable leaf sizes (0.3–263 cm 2 ) for each genotype. Power models better fit coffee leaf area (LA) than linear models. To validate the model, an independent data set of 388 leaves was used. We demonstrated that the currently used allometric models are biased, underestimating the area of a coffee leaf. We developed a single power model Y= 1⁄4 β◦ x β1 based on two leaf dimensions [LA = 0.6626 (LW) 1.0116 ; standard errors: β◦ = 0.0064, β1 = 0.0019; R2 = 0.996] with high precision and accuracy, random dispersion pattern of residuals and also unbiased, irrespective of cultivar and leaf size and shape. Even when the L (but not width) alone was used as the single leaf dimension, the power model developed still predicted with good accuracy the LA but at the expense of some loss of precision, as particularly found for 8% of the leaves sampled with length-to-width ratios below 2.0 or above 3.0. |
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Antunes, W. C.Pompelli, M. F.Carretero, D. M.DaMatta, F. M.2018-10-23T14:53:15Z2018-10-23T14:53:15Z2008-07-290003-4746https://doi.org/10.1111/j.1744-7348.2008.00235.xhttp://www.locus.ufv.br/handle/123456789/22384We aimed to evaluate the currently used allometric models, as well as to propose a reliable and accurate model using non-destructive measurements of leaf length (L) and/or width (W), for estimating the area of leaves of eight field-grown coffee cultivars. For model construction, a total of 1563 leaves were randomly selected from different levels of the tree canopies and encompassed the full spectrum of measurable leaf sizes (0.3–263 cm 2 ) for each genotype. Power models better fit coffee leaf area (LA) than linear models. To validate the model, an independent data set of 388 leaves was used. We demonstrated that the currently used allometric models are biased, underestimating the area of a coffee leaf. We developed a single power model Y= 1⁄4 β◦ x β1 based on two leaf dimensions [LA = 0.6626 (LW) 1.0116 ; standard errors: β◦ = 0.0064, β1 = 0.0019; R2 = 0.996] with high precision and accuracy, random dispersion pattern of residuals and also unbiased, irrespective of cultivar and leaf size and shape. Even when the L (but not width) alone was used as the single leaf dimension, the power model developed still predicted with good accuracy the LA but at the expense of some loss of precision, as particularly found for 8% of the leaves sampled with length-to-width ratios below 2.0 or above 3.0.engAnnals of Applied BiologyVolume 153, Issue 1, Pages 33-40, August 2008Coffea arabicaCoffea canephoraEstimating modelAllometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora)info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfartigoapplication/pdf799885https://locus.ufv.br//bitstream/123456789/22384/1/artigo.pdfeabeac10a51ce3c64c87a736eb188becMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/22384/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/223842018-10-23 12:02:17.854oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452018-10-23T15:02:17LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.en.fl_str_mv |
Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora) |
title |
Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora) |
spellingShingle |
Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora) Antunes, W. C. Coffea arabica Coffea canephora Estimating model |
title_short |
Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora) |
title_full |
Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora) |
title_fullStr |
Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora) |
title_full_unstemmed |
Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora) |
title_sort |
Allometric models for non‐destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora) |
author |
Antunes, W. C. |
author_facet |
Antunes, W. C. Pompelli, M. F. Carretero, D. M. DaMatta, F. M. |
author_role |
author |
author2 |
Pompelli, M. F. Carretero, D. M. DaMatta, F. M. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Antunes, W. C. Pompelli, M. F. Carretero, D. M. DaMatta, F. M. |
dc.subject.pt-BR.fl_str_mv |
Coffea arabica Coffea canephora Estimating model |
topic |
Coffea arabica Coffea canephora Estimating model |
description |
We aimed to evaluate the currently used allometric models, as well as to propose a reliable and accurate model using non-destructive measurements of leaf length (L) and/or width (W), for estimating the area of leaves of eight field-grown coffee cultivars. For model construction, a total of 1563 leaves were randomly selected from different levels of the tree canopies and encompassed the full spectrum of measurable leaf sizes (0.3–263 cm 2 ) for each genotype. Power models better fit coffee leaf area (LA) than linear models. To validate the model, an independent data set of 388 leaves was used. We demonstrated that the currently used allometric models are biased, underestimating the area of a coffee leaf. We developed a single power model Y= 1⁄4 β◦ x β1 based on two leaf dimensions [LA = 0.6626 (LW) 1.0116 ; standard errors: β◦ = 0.0064, β1 = 0.0019; R2 = 0.996] with high precision and accuracy, random dispersion pattern of residuals and also unbiased, irrespective of cultivar and leaf size and shape. Even when the L (but not width) alone was used as the single leaf dimension, the power model developed still predicted with good accuracy the LA but at the expense of some loss of precision, as particularly found for 8% of the leaves sampled with length-to-width ratios below 2.0 or above 3.0. |
publishDate |
2008 |
dc.date.issued.fl_str_mv |
2008-07-29 |
dc.date.accessioned.fl_str_mv |
2018-10-23T14:53:15Z |
dc.date.available.fl_str_mv |
2018-10-23T14:53:15Z |
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 |
https://doi.org/10.1111/j.1744-7348.2008.00235.x http://www.locus.ufv.br/handle/123456789/22384 |
dc.identifier.issn.none.fl_str_mv |
0003-4746 |
identifier_str_mv |
0003-4746 |
url |
https://doi.org/10.1111/j.1744-7348.2008.00235.x http://www.locus.ufv.br/handle/123456789/22384 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.pt-BR.fl_str_mv |
Volume 153, Issue 1, Pages 33-40, August 2008 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Annals of Applied Biology |
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Annals of Applied Biology |
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