NIRS在爐甘石及其炮制品質量控制中的應用研究NIRS在爐甘石及其炮制品質量控制中的應用研究

摘要：爐甘石及其炮制品是傳統(tǒng)中藥材和制劑中的重要組成部分，其質量控制對于保證中藥的療效和安全性具有重要意義。然而，傳統(tǒng)的質量控制方法往往需要耗費大量時間和資源。因此，本研究采用近紅外光譜技術（NIRS）作為一種快速、非破壞性的分析方法，對爐甘石及其炮制品的質量控制進行了深入研究。

NIRS原理：近紅外光譜技術是一種基于物質分子的振動與轉動引起的光譜變化的分析方法。通過對物質在近紅外波段的吸收光譜進行采集和分析，可以快速獲得樣品的化學組成、質量參數(shù)等信息。

實驗設計：本研究選取了10批不同產地、不同炮制工藝的爐甘石樣品作為實驗對象。首先，對樣品進行了傳統(tǒng)的質量控制指標測定，包括總灰分、揮發(fā)分、水分、微生物限度等；然后，使用NIRS儀器對樣品進行了近紅外光譜掃描，獲取吸收光譜數(shù)據(jù)；最后，使用多元回歸分析方法建立了各個質量指標與近紅外光譜數(shù)據(jù)之間的定量模型。

結果與討論：通過對爐甘石樣品的傳統(tǒng)質量控制指標測定，我們發(fā)現(xiàn)不同炮制工藝對爐甘石的化學成分和質量參數(shù)有顯著影響。而通過NIRS分析發(fā)現(xiàn)，爐甘石及其炮制品在近紅外波段的光譜特征明顯不同。進一步的多元回歸分析表明，通過建立各個質量指標與近紅外光譜數(shù)據(jù)之間的定量模型，可以準確預測樣品的質量參數(shù)。其中，總灰分和揮發(fā)分與近紅外光譜的吸收光譜峰強度有較強的相關性，水分和微生物限度則與吸收光譜峰位的變化關系密切。

結論：本研究結果表明，NIRS技術在爐甘石及其炮制品質量控制中具有良好的應用前景。相較于傳統(tǒng)的質量分析方法，NIRS具有非破壞性、高效快速、經(jīng)濟實用等優(yōu)點。通過建立定量模型，可以準確預測樣品的質量參數(shù)，提高質量控制的準確性和效率。然而，由于爐甘石及其炮制品樣品的復雜性和差異性，仍需要進一步優(yōu)化NIRS方法以提高預測精度。另外，為確保質量控制的可靠性，還需結合傳統(tǒng)分析方法，綜合分析結果。

關鍵詞：爐甘石；炮制品；質量控制；NIRS；近紅外光譜

Abstract:LugenShihanditsprocessedproductsareimportantcomponentsintraditionalChinesemedicine.ThequalitycontrolofLugenShihisofgreatsignificanceforensuringthetherapeuticefficacyandsafetyoftraditionalChinesemedicine.However,traditionalqualitycontrolmethodsoftenrequirealotoftimeandresources.Therefore,inthisstudy,near-infraredspectroscopy(NIRS)wasusedasafastandnon-destructiveanalyticalmethodtoconductin-depthresearchonthequalitycontrolofLugenShihanditsprocessedproducts.

PrincipleofNIRS:Near-infraredspectroscopyisananalyticalmethodbasedonthespectralchangescausedbythevibrationandrotationofmolecularsubstances.Bycollectingandanalyzingtheabsorptionspectraofsubstancesinthenear-infraredwavelengthrange,informationsuchasthechemicalcompositionandqualityparametersofthesamplecanbequicklyobtained.

Experimentaldesign:Inthisstudy,10batchesofLugenShihsampleswithdifferentoriginsandprocessedtechnologieswereselectedastheexperimentalobjects.Firstly,thetraditionalqualitycontrolindicatorsofthesamplesweredetermined,includingtotalashcontent,volatilecontent,moisturecontent,microbiallimit,etc.Then,thesampleswerescannedbyaNIRSinstrumenttoobtaintheabsorptionspectradata.Finally,multivariateregressionanalysiswasusedtoestablishquantitativemodelsbetweeneachqualityindicatorandthenear-infraredspectraldata.

Resultsanddiscussion:ThroughthedeterminationofthetraditionalqualitycontrolindicatorsofLugenShihsamples,itwasfoundthatdifferentprocessingtechniqueshadsignificanteffectsonthechemicalcompositionandqualityparametersofLugenShih.ThroughNIRSanalysis,itwasfoundthatthespectralcharacteristicsofLugenShihanditsprocessedproductsinthenear-infraredwavelengthrangeweresignificantlydifferent.Furthermultivariateregressionanalysisshowedthatbyestablishingquantitativemodelsbetweeneachqualityindicatorandthenear-infraredspectraldata,thequalityparametersofthesamplescouldbeaccuratelypredicted.Amongthem,thetotalashcontentandvolatilecontentshowedastrongcorrelationwiththepeakintensityoftheabsorptionspectruminthenear-infraredwavelengthrange,whilethemoisturecontentandmicrobiallimitwerecloselyrelatedtothechangesinthepeakpositionoftheabsorptionspectrum.

Conclusion:TheresultsofthisstudyindicatethatNIRStechnologyhaspromisingapplicationsinthequalitycontrolofLugenShihanditsprocessedproducts.Comparedwithtraditionalqualityanalysismethods,NIRShasadvantagessuchasnon-destructive,efficient,fast,andcost-effective.Byestablishingquantitativemodels,thequalityparametersofthesamplescanbeaccuratelypredicted,improvingtheaccuracyandefficiencyofqualitycontrol.However,duetothecomplexityanddiversityofLugenShihanditsprocessedproducts,theNIRSmethodstillneedstobefurtheroptimizedtoimprovethepredictionaccuracy.Inaddition,toensurethereliabilityofqualitycontrol,itisnecessarytocombinetraditionalanalysismethodsandcomprehensivelyanalyzetheresults.

Keywords:LugenShih;processedproducts;qualitycontrol;