Chemometrics for resolving spectral data of cephalosporines and tracing their residue in waste water samples

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dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorYehia A.M.
dc.contributor.authorElbalkiny H.T.
dc.contributor.authorRiad S.M.
dc.contributor.authorElsaharty Y.S.
dc.contributor.otherAnalytical Chemistry Department
dc.contributor.otherFaculty of Pharmacy
dc.contributor.otherCairo University
dc.contributor.otherKasr-El Aini 13 Street
dc.contributor.otherCairo
dc.contributor.other11562
dc.contributor.otherEgypt; Chemistry Department
dc.contributor.otherSchool of Pharmacy and Pharmaceutical Industries
dc.contributor.otherBadr University in Cairo
dc.contributor.otherBadr City
dc.contributor.otherCairo 11829
dc.contributor.otherEgypt; Analytical Chemistry Department
dc.contributor.otherFaculty of Pharmacy
dc.contributor.otherOctober University for Modern Sciences and Arts (MSA)
dc.contributor.other6th of October City
dc.contributor.other11787
dc.contributor.otherEgypt
dc.date.accessioned2020-01-09T20:40:34Z
dc.date.available2020-01-09T20:40:34Z
dc.date.issued2019
dc.descriptionScopus
dc.description.abstractChemometrics approaches have been used in this work to trace cephalosporins in aquatic system. Principal component regression (PCR), partial least squares (PLS), multivariate curve resolution-alternating least squares (MCR-ALS), and artificial neural networks (ANN) were compared to resolve the severally overlapped spectrum of three selected cephalosporins; cefprozil, cefradine and cefadroxil. The analytical performance of chemometric methods was compared in terms of errors. Artificial neural networks provide good recoveries with lowest error. Satisfactory results were obtained for the proposed chemometric methods whereas ANN showed better analytical performance. The qualitative meaning in MCR-ALS transformation provided very well correlations between the pure and estimated spectra of the three components. This multivariate processing of spectrophotometric data could successfully detect the studied antibiotics in waste water samples and compared favorably to alternative costly chromatographic methods. � 2019en_US
dc.description.urihttps://www.scimagojr.com/journalsearch.php?q=24530&tip=sid&clean=0
dc.identifier.doihttps://doi.org/10.1016/j.saa.2019.04.081
dc.identifier.doiPubMed ID 31063958
dc.identifier.issn13861425
dc.identifier.otherhttps://doi.org/10.1016/j.saa.2019.04.081
dc.identifier.otherPubMed ID 31063958
dc.identifier.urihttps://t.ly/dObOL
dc.language.isoEnglishen_US
dc.publisherElsevier B.V.en_US
dc.relation.ispartofseriesSpectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
dc.relation.ispartofseries219
dc.subjectOctober University for Modern Sciences and Arts
dc.subjectUniversity for Modern Sciences and Arts
dc.subjectMSA University
dc.subjectجامعة أكتوبر للعلوم الحديثة والآداب
dc.subjectArtificial neural networksen_US
dc.subjectCephalosporinsen_US
dc.subjectMultivariate Curve Resolution-Alternating Least Squaresen_US
dc.subjectWater samplesen_US
dc.subjectAntibioticsen_US
dc.subjectChromatographic analysisen_US
dc.subjectChromatographyen_US
dc.subjectLeast squares approximationsen_US
dc.subjectNeural networksen_US
dc.subjectAnalytical performanceen_US
dc.subjectCephalosporinsen_US
dc.subjectChromatographic methodsen_US
dc.subjectMultivariate curve resolution alternating least-squaresen_US
dc.subjectOverlapped spectraen_US
dc.subjectPartial least square (PLS)en_US
dc.subjectPrincipal component regressionen_US
dc.subjectWater samplesen_US
dc.subjectData handlingen_US
dc.subjectantiinfective agenten_US
dc.subjectcephalosporin derivativeen_US
dc.subjectartificial neural networken_US
dc.subjectleast square analysisen_US
dc.subjectmultivariate analysisen_US
dc.subjectproceduresen_US
dc.subjectspectrophotometryen_US
dc.subjectwaste wateren_US
dc.subjectwater pollutanten_US
dc.subjectAnti-Bacterial Agentsen_US
dc.subjectCephalosporinsen_US
dc.subjectLeast-Squares Analysisen_US
dc.subjectMultivariate Analysisen_US
dc.subjectNeural Networks (Computer)en_US
dc.subjectSpectrophotometryen_US
dc.subjectWaste Wateren_US
dc.subjectWater Pollutants, Chemicalen_US
dc.titleChemometrics for resolving spectral data of cephalosporines and tracing their residue in waste water samplesen_US
dc.typeArticleen_US
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