Detection of adulteration in camellia seed oil and s

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• Detection of adulteration in camellia seed oil and s

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  2011-03-09 00:00

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• Detection of adulteration in camellia seed oil and s

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  2024-09-28 00:08

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• Detection of adulteration in camellia seed oilses

  Anelectronicnosewasusedforthedetectionofmaizeoiladulterationincamelliaseedoilandsesameoil.Theresultsofmultivariateanalysisofvarianceshowedthatthesensorsignalsofdifferentkindsofoilaresignificantlydifferentfromeachother.Prin-cipalcomponentanalysisPCAcannotbeusedtodiscriminatetheadulterationofcamelliaseedoil,butcanbeusedinthediscriminationofadulterationinsesameoil.LineardiscriminantanalysisLDAismoreeffectivethanPCAandcanbeusedinadulterationdiscriminationforbothcamelliaseedoilandsesameoil.InordertocheckthediscriminativepowerofLDA,canonicaldiscriminantanalysiswasperformedaswell.Acceptableresultswerealsoobtained:Theaccuracyofpredictionwas83.6%forcamelliaseedoiland94.5%forsesameoil.TheartificialneuralnetworkANNmodelwasusedtodetectthepercentageofadulterationincamelliaseedoilandsesameoil.Theresultsshowedthat,basedonANNasitspatternrecognitiontechnique,theelec-tronicnosecannotpredictthepercentageofadulterationincamelliaseedoil,butcanbeusedinthequantitativedeterminationofadulterationinsesameoil.[详细]

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• ISOLATION OF PCB’S FROM TRANSFORMER OIL

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  an!°electronicnose!±hasbeenusedforthedetectionofadulterationsofsesameoil.thesystem,comprising10metaloxidesemiconductsensors,wasusedtogenerateapatternofthevolatilecompoundspresentinthesamples.priortodifferentsupervisedpatternrecognitiontreatments,featureextractiontechniqueswereemployedtochooseasetofoptimaldiscriminantvariables.principalcomponentanalysispca,fisherlineartransformationflt,stepwiselineardiscriminantanalysisstep-lda,se-lectionbyfisherweightssfwwereused,respectively.andthen,lineardiscriminantanalysislda,probabilisticneuralnetworkspnn,backpropagationneuralnetworksbpnnandgeneralregressionneuralnetworkgrnnwereappliedaspatternrecognitiontechniquesfortheelectronicnose.asforldaandpnn,fltwasthemosteffectivefeatureextractionmethod,whilestep-ldawasthemosteffectivewayforbpnnandfltwasmoresuitableforgrnn.withonlyonesamplemisclassi?edinourexperiment,ldaismorepowerfulthanpnn.excellentresultswereobtainedinthepredictionofpercentageofadulterationinsesameoilbybpnnandgrnn.aftertrainingforsometime,bpnncouldpredicttheadulterationquantitativelymorepreciselythangrnn,whereaswithfltasitsfeatureextractionmethodandwithoutiterativetraining,grnncouldalsoyieldratheracceptableresults.?2006elsevierb.v.allrightsreserved.[详细]

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