Detection of adulteration in camellia seed oilses
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Anelectronicnosewasusedforthedetectionofmaizeoiladulterationincamelliaseedoilandsesameoil.Theresultsofmultivariateanalysisofvarianceshowedthatthesensorsignalsofdifferentkindsofoilaresignificantlydifferentfromeachother.Prin-cipalcomponentanalysisPCAcannotbeusedtodiscriminatetheadulterationofcamelliaseedoil,butcanbeusedinthediscriminationofadulterationinsesameoil.LineardiscriminantanalysisLDAismoreeffectivethanPCAandcanbeusedinadulterationdiscriminationforbothcamelliaseedoilandsesameoil.InordertocheckthediscriminativepowerofLDA,canonicaldiscriminantanalysiswasperformedaswell.Acceptableresultswerealsoobtained:Theaccuracyofpredictionwas83.6%forcamelliaseedoiland94.5%forsesameoil.TheartificialneuralnetworkANNmodelwasusedtodetectthepercentageofadulterationincamelliaseedoilandsesameoil.Theresultsshowedthat,basedonANNasitspatternrecognitiontechnique,theelec-tronicnosecannotpredictthepercentageofadulterationincamelliaseedoil,butcanbeusedinthequantitativedeterminationofadulterationinsesameoil.
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