Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans

Detalhes bibliográficos
Autor(a) principal: Pivoto,Dieisson
Data de Publicação: 2016
Outros Autores: Becker,João Mathias, Bremm,Carolina, Albano,Filipe de Medeiros
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência Rural
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016000400599
Resumo: ABSTRACT: The study aimed to i) quantify the measurement uncertainty in the physical tests of rice and beans for a hypothetical defect, ii) verify whether homogenization and sample reduction in the physical classification tests of rice and beans is effective to reduce the measurement uncertainty of the process and iii) determine whether the increase in size of beans sample increases accuracy and reduces measurement uncertainty in a significant way. Hypothetical defects in rice and beans with different damage levels were simulated according to the testing methodology determined by the Normative Ruling of each product. The homogenization and sample reduction in the physical classification of rice and beans are not effective, transferring to the final test result a high measurement uncertainty. The sample size indicated by the Normative Ruling did not allow an appropriate homogenization and should be increased.
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spelling Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beansISO / IEC 17025grain classificationquality controlprecisionABSTRACT: The study aimed to i) quantify the measurement uncertainty in the physical tests of rice and beans for a hypothetical defect, ii) verify whether homogenization and sample reduction in the physical classification tests of rice and beans is effective to reduce the measurement uncertainty of the process and iii) determine whether the increase in size of beans sample increases accuracy and reduces measurement uncertainty in a significant way. Hypothetical defects in rice and beans with different damage levels were simulated according to the testing methodology determined by the Normative Ruling of each product. The homogenization and sample reduction in the physical classification of rice and beans are not effective, transferring to the final test result a high measurement uncertainty. The sample size indicated by the Normative Ruling did not allow an appropriate homogenization and should be increased.Universidade Federal de Santa Maria2016-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016000400599Ciência Rural v.46 n.4 2016reponame:Ciência Ruralinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM10.1590/0103-8478cr20150328info:eu-repo/semantics/openAccessPivoto,DieissonBecker,João MathiasBremm,CarolinaAlbano,Filipe de Medeiroseng2016-03-30T00:00:00ZRevista
dc.title.none.fl_str_mv Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans
title Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans
spellingShingle Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans
Pivoto,Dieisson
ISO / IEC 17025
grain classification
quality control
precision
title_short Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans
title_full Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans
title_fullStr Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans
title_full_unstemmed Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans
title_sort Uncertainty measurement in the homogenization and sample reduction in the physical classification of rice and beans
author Pivoto,Dieisson
author_facet Pivoto,Dieisson
Becker,João Mathias
Bremm,Carolina
Albano,Filipe de Medeiros
author_role author
author2 Becker,João Mathias
Bremm,Carolina
Albano,Filipe de Medeiros
author2_role author
author
author
dc.contributor.author.fl_str_mv Pivoto,Dieisson
Becker,João Mathias
Bremm,Carolina
Albano,Filipe de Medeiros
dc.subject.por.fl_str_mv ISO / IEC 17025
grain classification
quality control
precision
topic ISO / IEC 17025
grain classification
quality control
precision
description ABSTRACT: The study aimed to i) quantify the measurement uncertainty in the physical tests of rice and beans for a hypothetical defect, ii) verify whether homogenization and sample reduction in the physical classification tests of rice and beans is effective to reduce the measurement uncertainty of the process and iii) determine whether the increase in size of beans sample increases accuracy and reduces measurement uncertainty in a significant way. Hypothetical defects in rice and beans with different damage levels were simulated according to the testing methodology determined by the Normative Ruling of each product. The homogenization and sample reduction in the physical classification of rice and beans are not effective, transferring to the final test result a high measurement uncertainty. The sample size indicated by the Normative Ruling did not allow an appropriate homogenization and should be increased.
publishDate 2016
dc.date.none.fl_str_mv 2016-04-01
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=S0103-84782016000400599
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016000400599
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-8478cr20150328
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 de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Rural v.46 n.4 2016
reponame:Ciência Rural
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Rural
collection Ciência Rural
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repository.mail.fl_str_mv
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