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dc.contributor.author
Samman, Norma Cristina  
dc.contributor.author
Gimenez, M. A.  
dc.contributor.author
Bassett, Maria Natalia  
dc.contributor.author
Lobo, Manuel Oscar  
dc.contributor.author
Marcoleri, Maria Elena  
dc.date.available
2018-06-11T20:28:43Z  
dc.date.issued
2016-02  
dc.identifier.citation
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  
dc.identifier.issn
0308-8146  
dc.identifier.uri
http://hdl.handle.net/11336/48163  
dc.description.abstract
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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Sampling Plan  
dc.subject
Methodology Validation  
dc.subject
Food Composition  
dc.subject
Variability  
dc.subject.classification
Alimentos y Bebidas  
dc.subject.classification
Otras Ingenierías y Tecnologías  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Validation of a sampling plan to generate food composition data  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-05-04T16:46:29Z  
dc.journal.volume
193  
dc.journal.pagination
141-147  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Samman, Norma Cristina. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina  
dc.description.fil
Fil: Gimenez, M. A.. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina  
dc.description.fil
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  
dc.description.fil
Fil: Lobo, Manuel Oscar. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina  
dc.description.fil
Fil: Marcoleri, Maria Elena. Universidad Nacional de Jujuy; Argentina  
dc.journal.title
Food Chemistry  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.foodchem.2015.03.083  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0308814615004550?via%3Dihub