Determination of Thiamine Hcl and Pyridoxine Hcl in Pharmaceutical Preparations Using Uv-Visible Spectrophotometry and Genetic Algorithm Based Multivariate Calibration Methods
dc.contributor.author | Özdemir, Durmuş | |
dc.contributor.author | Dinç, Erdal | |
dc.contributor.other | 04.01. Department of Chemistry | |
dc.contributor.other | 04. Faculty of Science | |
dc.contributor.other | 01. Izmir Institute of Technology | |
dc.coverage.doi | 10.1248/cpb.52.810 | |
dc.date.accessioned | 2016-06-09T08:54:32Z | |
dc.date.available | 2016-06-09T08:54:32Z | |
dc.date.issued | 2004-07 | |
dc.description.abstract | Simultaneous determination of binary mixtures pyridoxine hydrochloride and thiamine hydrochloride in a vitamin combination using UV-visible spectrophotometry and classical least squares (CLS) and three newly developed genetic algorithm (GA) based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The sample data set contains the UV-visible spectra of 30 synthetic mixtures (8 to 40 μg/ml) of these vitamins and 10 tablets containing 250 mg from each vitamin. The spectra cover the range from 200 to 330 nm in 0.1 nm intervals. Several calibration models were built with the four methods for the two components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of <0.01 and 0.43 μg/ml for all the four methods. The SEP values for the tablets were in the range of 2.91 and 11.51 mg/tablets. A comparison of genetic algorithm selected wavelengths for each component using GR method was also included | en_US |
dc.identifier.citation | Özdemir, D., and Dinç, E. (2004). Determination of thiamine HCl and pyridoxine HCl in pharmaceutical preparations using UV-Visible spectrophotometry and genetic algorithm based multivariate calibration methods. Chemical and Pharmaceutical Bulletin, 52(7), 810-817. doi:10.1248/cpb.52.810 | en_US |
dc.identifier.doi | 10.1248/cpb.52.810 | en_US |
dc.identifier.doi | 10.1248/cpb.52.810 | |
dc.identifier.issn | 0009-2363 | |
dc.identifier.issn | 0009-2363 | |
dc.identifier.issn | 1347-5223 | |
dc.identifier.scopus | 2-s2.0-16544365257 | |
dc.identifier.uri | http://doi.org/10.1248/cpb.52.810 | |
dc.identifier.uri | https://hdl.handle.net/11147/4746 | |
dc.language.iso | en | en_US |
dc.publisher | Pharmaceutical Society of Japan | en_US |
dc.relation.ispartof | Chemical and Pharmaceutical Bulletin | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Classical Least Squares | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Genetic regression | en_US |
dc.subject | Inverse Least Squares | en_US |
dc.subject | Multivariate calibration | en_US |
dc.title | Determination of Thiamine Hcl and Pyridoxine Hcl in Pharmaceutical Preparations Using Uv-Visible Spectrophotometry and Genetic Algorithm Based Multivariate Calibration Methods | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
gdc.author.id | TR115516 | |
gdc.author.institutional | Özdemir, Durmuş | |
gdc.author.institutional | Özdemir, Durmuş | |
gdc.author.yokid | 115516 | |
gdc.bip.impulseclass | C5 | |
gdc.bip.influenceclass | C4 | |
gdc.bip.popularityclass | C5 | |
gdc.coar.access | open access | |
gdc.coar.type | text::journal::journal article | |
gdc.description.department | İzmir Institute of Technology. Chemistry | en_US |
gdc.description.endpage | 817 | en_US |
gdc.description.issue | 7 | en_US |
gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
gdc.description.scopusquality | Q3 | |
gdc.description.startpage | 810 | en_US |
gdc.description.volume | 52 | en_US |
gdc.description.wosquality | Q3 | |
gdc.identifier.openalex | W2087371580 | |
gdc.identifier.pmid | 15256701 | |
gdc.identifier.wos | WOS:000222411700006 | |
gdc.oaire.accesstype | GOLD | |
gdc.oaire.diamondjournal | false | |
gdc.oaire.impulse | 4.0 | |
gdc.oaire.influence | 4.2239887E-9 | |
gdc.oaire.isgreen | true | |
gdc.oaire.keywords | Genetic regression | |
gdc.oaire.keywords | Multivariate calibration | |
gdc.oaire.keywords | Classical Least Squares | |
gdc.oaire.keywords | Pyridoxine | |
gdc.oaire.keywords | Genetic algorithms | |
gdc.oaire.keywords | Pharmaceutical Preparations | |
gdc.oaire.keywords | Calibration | |
gdc.oaire.keywords | Multivariate Analysis | |
gdc.oaire.keywords | Spectrophotometry, Ultraviolet | |
gdc.oaire.keywords | Thiamine | |
gdc.oaire.keywords | Inverse Least Squares | |
gdc.oaire.keywords | Algorithms | |
gdc.oaire.popularity | 3.115273E-9 | |
gdc.oaire.publicfunded | false | |
gdc.oaire.sciencefields | 01 natural sciences | |
gdc.oaire.sciencefields | 0104 chemical sciences | |
gdc.openalex.fwci | 0.879 | |
gdc.openalex.normalizedpercentile | 0.82 | |
gdc.opencitations.count | 21 | |
gdc.plumx.crossrefcites | 15 | |
gdc.plumx.mendeley | 11 | |
gdc.plumx.scopuscites | 26 | |
gdc.scopus.citedcount | 26 | |
gdc.wos.citedcount | 27 | |
relation.isAuthorOfPublication | 451421f9-0bfe-4cc9-9c73-6252ce7a8a27 | |
relation.isAuthorOfPublication.latestForDiscovery | 451421f9-0bfe-4cc9-9c73-6252ce7a8a27 | |
relation.isOrgUnitOfPublication | 9af2b05f-28ac-4011-8abe-a4dfe192da5e | |
relation.isOrgUnitOfPublication | 9af2b05f-28ac-4005-8abe-a4dfe193da5e | |
relation.isOrgUnitOfPublication | 9af2b05f-28ac-4003-8abe-a4dfe192da5e | |
relation.isOrgUnitOfPublication.latestForDiscovery | 9af2b05f-28ac-4011-8abe-a4dfe192da5e |