Validation of a sampling plan to generate food composition data

Autores
Samman, Norma Cristina; Gimenez, M. A.; Bassett, Maria Natalia; Lobo, Manuel Oscar; Marcoleri, Maria Elena
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A methodology to develop systematic plans for food sampling was proposed. Long life whole and skimmed milk, and sunflower oil were selected to validate the methodology in Argentina. Fatty acid profile in all foods, proximal composition, and calcium’s content in milk were determined with AOAC methods. The number of samples (n) was calculated applying Cochran’s formula with variation coefficients ⩽12% and an estimate error (r) maximum permissible ⩽5% for calcium content in milks and unsaturated fatty acids in oil. n were 9, 11 and 21 for long life whole and skimmed milk, and sunflower oil respectively. Sample units were randomly collected from production sites and sent to labs. Calculated r with experimental data was ⩽10%, indicating high accuracy in the determination of analyte content of greater variability and reliability of the proposed sampling plan. The methodology is an adequate and useful tool to develop sampling plans for food composition analysis.
Fil: Samman, Norma Cristina. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina
Fil: Gimenez, M. A.. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina
Fil: Bassett, Maria Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina
Fil: Lobo, Manuel Oscar. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina
Fil: Marcoleri, Maria Elena. Universidad Nacional de Jujuy; Argentina
Materia
Sampling Plan
Methodology Validation
Food Composition
Variability
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/48163
Acceder
id CONICETDig_e50cb7d975c4b7b18b00cb155fefed86
oai_identifier_str oai:ri.conicet.gov.ar:11336/48163
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Validation of a sampling plan to generate food composition dataSamman, Norma CristinaGimenez, M. A.Bassett, Maria NataliaLobo, Manuel OscarMarcoleri, Maria ElenaSampling PlanMethodology ValidationFood CompositionVariabilityhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2A methodology to develop systematic plans for food sampling was proposed. Long life whole and skimmed milk, and sunflower oil were selected to validate the methodology in Argentina. Fatty acid profile in all foods, proximal composition, and calcium’s content in milk were determined with AOAC methods. The number of samples (n) was calculated applying Cochran’s formula with variation coefficients ⩽12% and an estimate error (r) maximum permissible ⩽5% for calcium content in milks and unsaturated fatty acids in oil. n were 9, 11 and 21 for long life whole and skimmed milk, and sunflower oil respectively. Sample units were randomly collected from production sites and sent to labs. Calculated r with experimental data was ⩽10%, indicating high accuracy in the determination of analyte content of greater variability and reliability of the proposed sampling plan. The methodology is an adequate and useful tool to develop sampling plans for food composition analysis.Fil: Samman, Norma Cristina. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Gimenez, M. A.. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Bassett, Maria Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Lobo, Manuel Oscar. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Marcoleri, Maria Elena. Universidad Nacional de Jujuy; ArgentinaElsevier2016-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/48163Samman, Norma Cristina; Gimenez, M. A.; Bassett, Maria Natalia; Lobo, Manuel Oscar; Marcoleri, Maria Elena; Validation of a sampling plan to generate food composition data; Elsevier; Food Chemistry; 193; 2-2016; 141-1470308-8146CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.foodchem.2015.03.083info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0308814615004550?via%3Dihubinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:32:25Zoai:ri.conicet.gov.ar:11336/48163instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:32:26.248CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Validation of a sampling plan to generate food composition data
title Validation of a sampling plan to generate food composition data
spellingShingle Validation of a sampling plan to generate food composition data
Samman, Norma Cristina
Sampling Plan
Methodology Validation
Food Composition
Variability
title_short Validation of a sampling plan to generate food composition data
title_full Validation of a sampling plan to generate food composition data
title_fullStr Validation of a sampling plan to generate food composition data
title_full_unstemmed Validation of a sampling plan to generate food composition data
title_sort Validation of a sampling plan to generate food composition data
dc.creator.none.fl_str_mv Samman, Norma Cristina
Gimenez, M. A.
Bassett, Maria Natalia
Lobo, Manuel Oscar
Marcoleri, Maria Elena
author Samman, Norma Cristina
author_facet Samman, Norma Cristina
Gimenez, M. A.
Bassett, Maria Natalia
Lobo, Manuel Oscar
Marcoleri, Maria Elena
author_role author
author2 Gimenez, M. A.
Bassett, Maria Natalia
Lobo, Manuel Oscar
Marcoleri, Maria Elena
author2_role author
author
author
author
dc.subject.none.fl_str_mv Sampling Plan
Methodology Validation
Food Composition
Variability
topic Sampling Plan
Methodology Validation
Food Composition
Variability
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv A methodology to develop systematic plans for food sampling was proposed. Long life whole and skimmed milk, and sunflower oil were selected to validate the methodology in Argentina. Fatty acid profile in all foods, proximal composition, and calcium’s content in milk were determined with AOAC methods. The number of samples (n) was calculated applying Cochran’s formula with variation coefficients ⩽12% and an estimate error (r) maximum permissible ⩽5% for calcium content in milks and unsaturated fatty acids in oil. n were 9, 11 and 21 for long life whole and skimmed milk, and sunflower oil respectively. Sample units were randomly collected from production sites and sent to labs. Calculated r with experimental data was ⩽10%, indicating high accuracy in the determination of analyte content of greater variability and reliability of the proposed sampling plan. The methodology is an adequate and useful tool to develop sampling plans for food composition analysis.
Fil: Samman, Norma Cristina. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina
Fil: Gimenez, M. A.. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina
Fil: Bassett, Maria Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina
Fil: Lobo, Manuel Oscar. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina
Fil: Marcoleri, Maria Elena. Universidad Nacional de Jujuy; Argentina
description A methodology to develop systematic plans for food sampling was proposed. Long life whole and skimmed milk, and sunflower oil were selected to validate the methodology in Argentina. Fatty acid profile in all foods, proximal composition, and calcium’s content in milk were determined with AOAC methods. The number of samples (n) was calculated applying Cochran’s formula with variation coefficients ⩽12% and an estimate error (r) maximum permissible ⩽5% for calcium content in milks and unsaturated fatty acids in oil. n were 9, 11 and 21 for long life whole and skimmed milk, and sunflower oil respectively. Sample units were randomly collected from production sites and sent to labs. Calculated r with experimental data was ⩽10%, indicating high accuracy in the determination of analyte content of greater variability and reliability of the proposed sampling plan. The methodology is an adequate and useful tool to develop sampling plans for food composition analysis.
publishDate 2016
dc.date.none.fl_str_mv 2016-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/48163
Samman, Norma Cristina; Gimenez, M. A.; Bassett, Maria Natalia; Lobo, Manuel Oscar; Marcoleri, Maria Elena; Validation of a sampling plan to generate food composition data; Elsevier; Food Chemistry; 193; 2-2016; 141-147
0308-8146
CONICET Digital
CONICET
url http://hdl.handle.net/11336/48163
identifier_str_mv Samman, Norma Cristina; Gimenez, M. A.; Bassett, Maria Natalia; Lobo, Manuel Oscar; Marcoleri, Maria Elena; Validation of a sampling plan to generate food composition data; Elsevier; Food Chemistry; 193; 2-2016; 141-147
0308-8146
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.foodchem.2015.03.083
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0308814615004550?via%3Dihub
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844612989179658240
score 13.069144

Publicaciones similares