Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/2167
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dc.contributor.authorÖzdemir, Durmuş-
dc.date.accessioned2016-10-03T08:39:13Z
dc.date.available2016-10-03T08:39:13Z
dc.date.issued2006-12
dc.identifier.citationÖzdemir, D. (2006). Genetic multivariate calibration for near infrared spectroscopic determination of protein, moisture, dry mass, hardness and other residues of wheat. International Journal of Food Science and Technology, 41(Issue SUPPL.), 12-21. doi:10.1111/j.1365-2621.2006.01243.xen_US
dc.identifier.issn0950-5423
dc.identifier.issn0950-5423-
dc.identifier.urihttp://doi.org/10.1111/j.1365-2621.2006.01243.x
dc.identifier.urihttp://hdl.handle.net/11147/2167
dc.description.abstractDetermination of wheat flour quality parameters, such as protein, moisture, dry mass by wet chemistry analyses takes long time. Near infrared spectroscopy (NIR) coupled with multivariate calibration offers a fast and nondestructive alternative to obtain reliable results. However, due to the complexity of the spectra obtained from NIR, some wavelength selection is generally required to improve the predictive ability of multivariate calibration methods. In this study, two different wheat data sets are investigated with the aim of establishing successful calibration models using NIR spectra of wheat samples. The first data set (material 1) was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) and contained 100 NIR spectra of wheat of which wet chemical analysis of protein and moisture content were done with reference methods. The second data set (material 2) contained 176 spectra and was downloaded from http://www.spectroscopynow.com/Spy/basehtml/SpyH/1,1181, 2-1-2-0-0-newsdetail-0-74,00.html. This wheat data set was given with the quality parameters, such as protein content, moisture content, other residues, dry mass, protein content in dry mass and hardness that were determined previously. Multivariate calibration models generated with genetic inverse least squares method demonstrated very good prediction results for the parameter mentioned here. Overall, the average per cent recoveries (APR) ranged between 99.23% and 100.34% with a standard deviation (SD) ranging from 0.34 to 3.15 for all the parameters investigated, except hardness. The APR value of hardness was 103.32 with the SD of 14.97.en_US
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Inc.en_US
dc.relation.ispartofInternational Journal of Food Science and Technologyen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMoistureen_US
dc.subjectMultivariate calibrationen_US
dc.subjectNear infrared spectroscopyen_US
dc.subjectProteinsen_US
dc.subjectWheaten_US
dc.titleGenetic multivariate calibration for near infrared spectroscopic determination of protein, moisture, dry mass, hardness and other residues of wheaten_US
dc.typeArticleen_US
dc.authoridTR115516en_US
dc.institutionauthorÖzdemir, Durmuş-
dc.departmentIzmir Institute of Technology. Chemistryen_US
dc.identifier.volume41en_US
dc.identifier.issueIssue SUPPL.en_US
dc.identifier.startpage12en_US
dc.identifier.endpage21en_US
dc.identifier.wosWOS:000243005900003en_US
dc.identifier.scopus2-s2.0-33751175850en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1111/j.1365-2621.2006.01243.x-
dc.relation.doi10.1111/j.1365-2621.2006.01243.xen_US
dc.coverage.doi10.1111/j.1365-2621.2006.01243.xen_US
dc.identifier.scopusqualityQ1-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.languageiso639-1en-
crisitem.author.dept04.01. Department of Chemistry-
Appears in Collections:Chemistry / Kimya
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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