The use of infrared spectrometers to predict quality parameters of cornmeal (corn grits) and differentiate between organic and conventional practices

Basit Öğe Kaydı
dc.authoridRodriguez-Saona, Luis/0000-0002-6615-1296
dc.authoridPlans Pujolras, Marcal/0000-0001-9894-2626
dc.contributor.authorAyvaz, Huseyin
dc.contributor.authorPlans, Marcal
dc.contributor.authorTowers, Brittany N.
dc.contributor.authorAuer, Angela
dc.contributor.authorRodriguez-Saona, Luis E.
dc.date.accessioned2025-01-27T20:49:56Z
dc.date.available2025-01-27T20:49:56Z
dc.date.issued2015
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractBenchtop and handheld NIR and portable mid-infrared (MIR) spectrometers were evaluated as rapid methods for differentiating between organic and conventional cornmeal and to measure quality parameters of cornmeal used for production of snack foods. Twenty-seven conventional and eleven organic cornmeal samples were obtained from a local manufacturer of grain-based products. Reference quality parameters measured included moisture content, ash content, pasting properties and particle size. Soft independent modeling of class analogy (SIMCA) analysis accurately classified between organic and conventional cornmeal samples (interclass distance > 3.7) based on differences in the C=O signal associated with side chain vibrations of acidic amino acids. Residual predictive deviation (RPD) values for partial least squares regression (PLSR) models developed, ranged between 2.3 and 9.6. Overall, our data supports the capability of infrared systems to classify between organic and conventional cornmeal, and to predict important quality attributes of cornmeal for the snack food industry. (C) 2015 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipOhio Agricultural Research and Development Center [OHOA1492]
dc.description.sponsorshipThe authors would like to acknowledge the Ohio Agricultural Research and Development Center (project OHOA1492) for their financial support of this research. We would also like to thank Wyandot Snack Company for generously providing the samples for this research, Dr. Byung-Kee Baik and Thomas Donelson from the USDA Agricultural Research Servive (Wooster, OH) for lending their RVA instrument and Prof. Sheryl Barringer for making her Particle Size Analyzer available to the research group.
dc.identifier.doi10.1016/j.jcs.2014.12.004
dc.identifier.endpage30
dc.identifier.issn0733-5210
dc.identifier.issn1095-9963
dc.identifier.scopus2-s2.0-84961328219
dc.identifier.scopusqualityQ1
dc.identifier.startpage22
dc.identifier.urihttps://doi.org/10.1016/j.jcs.2014.12.004
dc.identifier.urihttps://hdl.handle.net/20.500.12428/25363
dc.identifier.volume62
dc.identifier.wosWOS:000353600800004
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherAcademic Press Ltd- Elsevier Science Ltd
dc.relation.ispartofJournal of Cereal Science
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20250125
dc.subjectCornmeal
dc.subjectOrganic
dc.subjectHandheld and portable spectrometers
dc.subjectMultivariate analysis
dc.titleThe use of infrared spectrometers to predict quality parameters of cornmeal (corn grits) and differentiate between organic and conventional practices
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu