MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000400458 |
Resumo: | ABSTRACT An adequate combination of factors involved in the technology used for phytosanitary product application contributes to an efficient spray deposition on the target. The objective of this study was to use multivariate analysis to characterize the magnitude of effects and the order of influence of three factors that interfere with the quality of phytosanitary product application in coffee plants. An entirely randomized design was adopted, with four repetitions, using a 2 × 2 × 3 factorial scheme, with two classes of droplets quality (fine and coarse), two application rates (250 and 400 L ha-1), and the use of adjuvants (with no adjuvant or with Fighter®and Aureo® adjuvants). The quality of the application was determined by jointly analyzing the spray deposition on three thirds of leaves, in their internal and external layers, the runoff to soil, coverage, droplet density, relative amplitude, and the volumetric median diameter. The results underwent analysis of variance (ANOVA) to measure the effect sizes (η2). After testing the assumptions of multivariate analysis, clustering and principal component analyses were performed. The class of droplets was found to be the most influential factor in the quality of the phytosanitary product application (spray deposition and runoff to soil). When focusing on spray deposition on leaves, the second-most influential factor was the application rate and the relation between the application rate and the adjuvants. For the other variables, the second-most influential factor was the application rate. |
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MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTSApplication ratedroplet sizeadjuvantsEta squaredPCAcluster analysisABSTRACT An adequate combination of factors involved in the technology used for phytosanitary product application contributes to an efficient spray deposition on the target. The objective of this study was to use multivariate analysis to characterize the magnitude of effects and the order of influence of three factors that interfere with the quality of phytosanitary product application in coffee plants. An entirely randomized design was adopted, with four repetitions, using a 2 × 2 × 3 factorial scheme, with two classes of droplets quality (fine and coarse), two application rates (250 and 400 L ha-1), and the use of adjuvants (with no adjuvant or with Fighter®and Aureo® adjuvants). The quality of the application was determined by jointly analyzing the spray deposition on three thirds of leaves, in their internal and external layers, the runoff to soil, coverage, droplet density, relative amplitude, and the volumetric median diameter. The results underwent analysis of variance (ANOVA) to measure the effect sizes (η2). After testing the assumptions of multivariate analysis, clustering and principal component analyses were performed. The class of droplets was found to be the most influential factor in the quality of the phytosanitary product application (spray deposition and runoff to soil). When focusing on spray deposition on leaves, the second-most influential factor was the application rate and the relation between the application rate and the adjuvants. For the other variables, the second-most influential factor was the application rate.Associação Brasileira de Engenharia Agrícola2021-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000400458Engenharia Agrícola v.41 n.4 2021reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v41n4p458-467/2021info:eu-repo/semantics/openAccessPalma,Roxanna P.Cunha,João P. A. R. daGuimarães,Ednaldo C.Santana,Denise G. deAssunção,Heli H. T. deeng2021-09-13T00:00:00Zoai:scielo:S0100-69162021000400458Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2021-09-13T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS |
title |
MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS |
spellingShingle |
MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS Palma,Roxanna P. Application rate droplet size adjuvants Eta squared PCA cluster analysis |
title_short |
MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS |
title_full |
MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS |
title_fullStr |
MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS |
title_full_unstemmed |
MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS |
title_sort |
MULTIVARIATE ANALYSIS APPLIED TO SPRAY DEPOSITION IN GROUND APPLICATION OF PHYTOSANITARY PRODUCTS IN COFFEE PLANTS |
author |
Palma,Roxanna P. |
author_facet |
Palma,Roxanna P. Cunha,João P. A. R. da Guimarães,Ednaldo C. Santana,Denise G. de Assunção,Heli H. T. de |
author_role |
author |
author2 |
Cunha,João P. A. R. da Guimarães,Ednaldo C. Santana,Denise G. de Assunção,Heli H. T. de |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Palma,Roxanna P. Cunha,João P. A. R. da Guimarães,Ednaldo C. Santana,Denise G. de Assunção,Heli H. T. de |
dc.subject.por.fl_str_mv |
Application rate droplet size adjuvants Eta squared PCA cluster analysis |
topic |
Application rate droplet size adjuvants Eta squared PCA cluster analysis |
description |
ABSTRACT An adequate combination of factors involved in the technology used for phytosanitary product application contributes to an efficient spray deposition on the target. The objective of this study was to use multivariate analysis to characterize the magnitude of effects and the order of influence of three factors that interfere with the quality of phytosanitary product application in coffee plants. An entirely randomized design was adopted, with four repetitions, using a 2 × 2 × 3 factorial scheme, with two classes of droplets quality (fine and coarse), two application rates (250 and 400 L ha-1), and the use of adjuvants (with no adjuvant or with Fighter®and Aureo® adjuvants). The quality of the application was determined by jointly analyzing the spray deposition on three thirds of leaves, in their internal and external layers, the runoff to soil, coverage, droplet density, relative amplitude, and the volumetric median diameter. The results underwent analysis of variance (ANOVA) to measure the effect sizes (η2). After testing the assumptions of multivariate analysis, clustering and principal component analyses were performed. The class of droplets was found to be the most influential factor in the quality of the phytosanitary product application (spray deposition and runoff to soil). When focusing on spray deposition on leaves, the second-most influential factor was the application rate and the relation between the application rate and the adjuvants. For the other variables, the second-most influential factor was the application rate. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-08-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000400458 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000400458 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-eng.agric.v41n4p458-467/2021 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
dc.source.none.fl_str_mv |
Engenharia Agrícola v.41 n.4 2021 reponame:Engenharia Agrícola instname:Associação Brasileira de Engenharia Agrícola (SBEA) instacron:SBEA |
instname_str |
Associação Brasileira de Engenharia Agrícola (SBEA) |
instacron_str |
SBEA |
institution |
SBEA |
reponame_str |
Engenharia Agrícola |
collection |
Engenharia Agrícola |
repository.name.fl_str_mv |
Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA) |
repository.mail.fl_str_mv |
revistasbea@sbea.org.br||sbea@sbea.org.br |
_version_ |
1752126275250552832 |