Mostrar el registro sencillo del ítem
dc.contributor.author
Bertotto, M. Mercedes
dc.contributor.author
Gastón, Analía
dc.contributor.author
Rodríguez Batiller, María Jose
dc.contributor.author
Calello, Pablo
dc.date.available
2020-01-06T14:20:33Z
dc.date.issued
2018-10
dc.identifier.citation
Bertotto, M. Mercedes; Gastón, Analía; Rodríguez Batiller, María Jose; Calello, Pablo; Comparison of mathematical models with predict glass transition temperature of rice (cultivar IRGA 424) measured by dynamic mechanical analysis; Wiley Blackwell Publishing, Inc; Food Science & Nutrition; 6; 8; 10-2018; 2199-2209
dc.identifier.issn
2048-7177
dc.identifier.uri
http://hdl.handle.net/11336/93571
dc.description.abstract
Dynamic mechanical analysis (DMA) was applied to measure the Tg of rice IRGA 424 at different moisture content values (9.3%–22.3% wet basis). To conduct temperature sweeps, the samples were heated at a rate of 2°C/min from 20 to 120°C keeping frequency to 1 Hz. Tg was measured both from the E″ peak temperature (Tgmidpoint) and from the tan (δ) peak temperature (Tgendset). Tgmidpoint and Tgendset increased from 31.8 to 86.6°C and 42.1 to 104.7°C, respectively, as moisture content decreased from 22.3 to 9.3%. Six models were tested for their ability to predict Tg as a function of the moisture content. As all residuals were normally distributed and homoskedastic, standard metrics were used to assess the fitted models. Goodness of fit by these models was established by comparing the coefficient of determination (R2), standard error of the estimate (SEE), and mean relative deviation (MRD). The Gordon–Taylor linearized equation was the most accurate in predicting Tg. To predict Tg from the moisture content of the rice samples, a new expression was proposed. For the conditions considered in this work, the developed equation satisfactorily predicts the Tg of rice IRGA 424 without needing prior linearization.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Wiley Blackwell Publishing, Inc
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
dynamic mechanical analysis
dc.subject
food processing
dc.subject
glass transition
dc.subject
mathematical modeling
dc.subject.classification
Otras Ciencias Químicas
dc.subject.classification
Ciencias Químicas
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Comparison of mathematical models with predict glass transition temperature of rice (cultivar IRGA 424) measured by dynamic mechanical analysis
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-10-16T15:25:00Z
dc.journal.volume
6
dc.journal.number
8
dc.journal.pagination
2199-2209
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Bertotto, M. Mercedes. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina. Ministerio de Agricultura, Ganadería, Pesca y Alimento. Servicio Nacional de Sanidad y Calidad Agroalimentaria; Argentina
dc.description.fil
Fil: Gastón, Analía. Universidad Nacional de Rosario; Argentina
dc.description.fil
Fil: Rodríguez Batiller, María Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnología en Polímeros y Nanotecnología. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnología en Polímeros y Nanotecnología; Argentina
dc.description.fil
Fil: Calello, Pablo. Ministerio de Agricultura, Ganadería, Pesca y Alimento. Servicio Nacional de Sanidad y Calidad Agroalimentaria; Argentina
dc.journal.title
Food Science & Nutrition
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://doi.wiley.com/10.1002/fsn3.785
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1002/fsn3.785
Archivos asociados