Analysis of defects in coffee beans compared to biplots for simultaneous tables

Detalhes bibliográficos
Autor(a) principal: Brighenti,Carla Regina Guimarães
Data de Publicação: 2018
Outros Autores: Cirillo,Marcelo Angelo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista ciência agronômica (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902018000100062
Resumo: ABSTRACT The demand for high quality coffee has become a consolidated criterion to achieve the best prices. Currently, cooperatives evaluate the coffee beans mainly through the particle size and the number of defects in the sample. This evaluation type generates counting data that originates contingency tables from different periods or groups involving the same variables in the row and column and there may be interest in knowing if two tables are related and how much are related. These are the so-called combined tables. Statistical analysis techniques normally employed do not include categorical data in the combined tables. The aim of this study was to evaluate the incidence of different types of defects in samples of large flat coffee beans in two different harvests through the construction of biplots. The decomposition theory in single simultaneous values of double entry contingency tables was used. The results of defect counting in beans of 24 coffee samples from southern Minas Gerais, Brazil, were evaluated in the 2014 and 2015 harvests. Moreover, the association among defect types, considered within different total defect proportions in the sample, was verified based on the percentage in 17/18 sieves. It was also evaluated the relative sums of squares from the similarity and dissimilarity among the harvests. It is concluded that the simultaneous analysis technique allows better visualizing the common behavior and alterations among different harvests, distinguishing the defect types associated with each harvest and among different proportions of large flat beans.
id UFC-2_a3d410896d66a95a7536bc60f4789f0d
oai_identifier_str oai:scielo:S1806-66902018000100062
network_acronym_str UFC-2
network_name_str Revista ciência agronômica (Online)
repository_id_str
spelling Analysis of defects in coffee beans compared to biplots for simultaneous tablesCoffea arabica L.Coffee qualityParticle sizeSVDSievesABSTRACT The demand for high quality coffee has become a consolidated criterion to achieve the best prices. Currently, cooperatives evaluate the coffee beans mainly through the particle size and the number of defects in the sample. This evaluation type generates counting data that originates contingency tables from different periods or groups involving the same variables in the row and column and there may be interest in knowing if two tables are related and how much are related. These are the so-called combined tables. Statistical analysis techniques normally employed do not include categorical data in the combined tables. The aim of this study was to evaluate the incidence of different types of defects in samples of large flat coffee beans in two different harvests through the construction of biplots. The decomposition theory in single simultaneous values of double entry contingency tables was used. The results of defect counting in beans of 24 coffee samples from southern Minas Gerais, Brazil, were evaluated in the 2014 and 2015 harvests. Moreover, the association among defect types, considered within different total defect proportions in the sample, was verified based on the percentage in 17/18 sieves. It was also evaluated the relative sums of squares from the similarity and dissimilarity among the harvests. It is concluded that the simultaneous analysis technique allows better visualizing the common behavior and alterations among different harvests, distinguishing the defect types associated with each harvest and among different proportions of large flat beans.Universidade Federal do Ceará2018-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902018000100062Revista Ciência Agronômica v.49 n.1 2018reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFC10.5935/1806-6690.20180007info:eu-repo/semantics/openAccessBrighenti,Carla Regina GuimarãesCirillo,Marcelo Angeloeng2018-01-30T00:00:00Zoai:scielo:S1806-66902018000100062Revistahttp://www.ccarevista.ufc.br/PUBhttps://old.scielo.br/oai/scielo-oai.php||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2018-01-30T00:00Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Analysis of defects in coffee beans compared to biplots for simultaneous tables
title Analysis of defects in coffee beans compared to biplots for simultaneous tables
spellingShingle Analysis of defects in coffee beans compared to biplots for simultaneous tables
Brighenti,Carla Regina Guimarães
Coffea arabica L.
Coffee quality
Particle size
SVD
Sieves
title_short Analysis of defects in coffee beans compared to biplots for simultaneous tables
title_full Analysis of defects in coffee beans compared to biplots for simultaneous tables
title_fullStr Analysis of defects in coffee beans compared to biplots for simultaneous tables
title_full_unstemmed Analysis of defects in coffee beans compared to biplots for simultaneous tables
title_sort Analysis of defects in coffee beans compared to biplots for simultaneous tables
author Brighenti,Carla Regina Guimarães
author_facet Brighenti,Carla Regina Guimarães
Cirillo,Marcelo Angelo
author_role author
author2 Cirillo,Marcelo Angelo
author2_role author
dc.contributor.author.fl_str_mv Brighenti,Carla Regina Guimarães
Cirillo,Marcelo Angelo
dc.subject.por.fl_str_mv Coffea arabica L.
Coffee quality
Particle size
SVD
Sieves
topic Coffea arabica L.
Coffee quality
Particle size
SVD
Sieves
description ABSTRACT The demand for high quality coffee has become a consolidated criterion to achieve the best prices. Currently, cooperatives evaluate the coffee beans mainly through the particle size and the number of defects in the sample. This evaluation type generates counting data that originates contingency tables from different periods or groups involving the same variables in the row and column and there may be interest in knowing if two tables are related and how much are related. These are the so-called combined tables. Statistical analysis techniques normally employed do not include categorical data in the combined tables. The aim of this study was to evaluate the incidence of different types of defects in samples of large flat coffee beans in two different harvests through the construction of biplots. The decomposition theory in single simultaneous values of double entry contingency tables was used. The results of defect counting in beans of 24 coffee samples from southern Minas Gerais, Brazil, were evaluated in the 2014 and 2015 harvests. Moreover, the association among defect types, considered within different total defect proportions in the sample, was verified based on the percentage in 17/18 sieves. It was also evaluated the relative sums of squares from the similarity and dissimilarity among the harvests. It is concluded that the simultaneous analysis technique allows better visualizing the common behavior and alterations among different harvests, distinguishing the defect types associated with each harvest and among different proportions of large flat beans.
publishDate 2018
dc.date.none.fl_str_mv 2018-03-01
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=S1806-66902018000100062
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902018000100062
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.5935/1806-6690.20180007
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 Universidade Federal do Ceará
publisher.none.fl_str_mv Universidade Federal do Ceará
dc.source.none.fl_str_mv Revista Ciência Agronômica v.49 n.1 2018
reponame:Revista ciência agronômica (Online)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Revista ciência agronômica (Online)
collection Revista ciência agronômica (Online)
repository.name.fl_str_mv Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv ||alekdutra@ufc.br|| ccarev@ufc.br
_version_ 1750297488976248832