本文選題：近紅外光譜技術(shù) + 抹茶�。� 參考：《安徽農(nóng)業(yè)大學(xué)》2017年碩士論文

【摘要】：抹茶是茶葉深加工產(chǎn)品之一,因其良好的品質(zhì)特點而展現(xiàn)出良好的經(jīng)濟效益。這也導(dǎo)致了目前市場上抹茶產(chǎn)品良莠不齊,出現(xiàn)了往抹茶中添加非茶成分,或以次充好的現(xiàn)象。這不僅損害了消費者的合法權(quán)益,也破壞了抹茶的市場秩序,為此建立快速可靠的抹茶摻偽檢測方法對維護抹茶的市場秩序和品質(zhì)安全具有重要意義。本研究主要針對市場上常見的抹茶摻偽物(白砂糖、麥芽糊精、桑葉粉、大麥苗粉)為研究對象,以近紅外光譜技術(shù)為基礎(chǔ),并結(jié)合化學(xué)計量學(xué)方法(主成分分析結(jié)合線性判別分析、K最近鄰法、偏最小二乘法),分別建立了純抹茶與摻偽抹茶、4種摻偽抹茶的定性判別模型及其定量分析模型。(1)抹茶樣品的前處理對定量模型結(jié)果的影響。在對抹茶進行壓餅和未壓餅的定量模型中,以添加白砂糖、麥芽糊精的抹茶為研究對象,壓餅和未壓餅的定量判別模型結(jié)果表明,未壓餅的模型結(jié)果優(yōu)于壓餅的。這對于超微粉的近紅外光譜技術(shù)分析有借鑒意義。(2)采用近紅外光譜技術(shù)結(jié)合主成分分析和線性判別分析(PCA-LDA)、K最近鄰法,對采集的42條純抹茶樣品與150條摻偽抹茶樣品光譜(30條摻偽白砂糖抹茶光譜、30條摻偽麥芽糊精抹茶光譜、40條摻偽桑葉粉抹茶光譜、50條摻偽大麥苗粉抹茶光譜)建立定性判別分析來判別抹茶是否摻偽和摻偽類型,通過比較,PCA-LDA的結(jié)果優(yōu)于K最近鄰法。純抹茶與摻偽抹茶、純抹茶與摻偽白砂糖抹茶、純抹茶與摻麥芽糊精抹茶、純抹茶與摻桑葉粉抹茶、純抹茶與摻大麥苗粉抹茶以及四種摻偽抹茶的定性分析模型的校正集識別率為98.3%、100%、91.7%、100%、100%,100%;預(yù)測集識別率96.5%、100%、87.5%、95.8%、90.3%、95.3%。由此可知,通過PCA-LDA建立的定性判別模型準確度和穩(wěn)定性都很好,能夠快速、準確的對抹茶中是否摻偽進行定性判別。(3)近紅外光譜技術(shù)結(jié)合偏最小二乘法,使用四種光譜預(yù)處理方法對光譜預(yù)處理,并建立抹茶中4種摻偽物含量的定量模型,對添加白砂糖、桑葉粉、0~50%大麥苗粉、50~100%大麥苗粉的抹茶的光譜預(yù)處理方法以平滑處理的結(jié)果最好,麥芽糊精的以最大最小歸一化預(yù)處理結(jié)果最好,所建立定量模型的校正集相關(guān)系數(shù)(Rc)分別為0.9910、0.9984、0.9975、0.9976、0.9975,RMSECV分別為0.391、1.60、1.11、2.44、0.66;預(yù)測集相關(guān)系數(shù)(Rv)分別為0.9992、0.9984、0.9976、0.9925、0.9977,RMSEP分別為0.365、1.99、1.13、1.93、0.761。由此可知,所建立的定量分析模型能夠?qū)δú柚袚絺挝锏暮窟M行定量分析,且模型的準確度和穩(wěn)定性能夠滿足一般的檢測需求。
[Abstract]:Matcha is one of the deep processing products of tea, which shows good economic benefits because of its good quality. This also led to the current market for tea products mixed, the emergence of tea to add non-tea ingredients, or substandard phenomenon. This not only damages the legitimate rights and interests of consumers, but also destroys the market order of matcha. Therefore, it is of great significance to establish a fast and reliable method to detect the adulteration of matcha in order to maintain the market order and quality safety of matcha. In this study, the common adulterated matcha products (white sugar, maltodextrin, mulberry leaf powder, wheat seedling powder) were studied, based on near infrared spectroscopy (NIR). Combined with chemometrics (principal component analysis and linear discriminant analysis), (1) the effects of pretreatment on the quantitative model results were analyzed. (1) the qualitative discriminant model and the quantitative analysis model of four kinds of tea adulterated with pure and fake matcha were established, respectively. (1) the effect of pretreatment on the results of the quantitative model. In the quantitative model of pressing cake and unpressed cake of matcha, taking the tea with white granulated sugar and maltodextrin as the research object, the quantitative discriminant model of pressed cake and unpressed cake shows that the model of unpressed cake is better than that of cake. It is useful for the analysis of ultrafine powder by near infrared spectroscopy. (2) the near infrared spectroscopy combined with principal component analysis and linear discriminant analysis (PCA-LDA) is used. The spectrum of 42 samples of pure matcha and 150 samples of adulterated matcha (30 spectrum of adulterated white granulated tea and 30 spectrum of adulterated maltodextrin) were established. Qualitative discriminant analysis is used to determine whether or not matcha is adulterated and the type of adulteration. The results of PCA-LDA are better than that of K-nearest neighbor method. Pure matcha and adulterated matcha, pure matcha and adulterated white granulated tea, pure matcha and maltodextrin matcha, pure matcha and mulberry leaf powder matcha, The correct set recognition rate of qualitative analysis models of pure matcha, adulterated wheat seed powder and four kinds of adulterated matcha were 98.3 / 100 and 91.7 / 100 and 100 / 100, respectively, and the predictive recognition rate was 96.57.595 / 90.33 / 100 and 90.33 / 90.3 / 100, respectively. It can be seen that the qualitative discriminant model established by PCA-LDA has good accuracy and stability, and can quickly and accurately determine whether or not adulterated tea is adulterated. (3) Near-infrared spectroscopy combined with partial least square method. Four spectral pretreatment methods were used to pretreat the spectrum, and a quantitative model of the content of four adulterated compounds in mash tea was established. The spectral pretreatment of mash with 50% wheat seedling powder of 50% mulberry leaf powder and 100% wheat seedling powder with smooth treatment was the best, and that of maltodextrin with maximum and minimum normalization was the best. The calibration set correlation coefficient (RC) of the established quantitative model was 0.9910 / 0.9984 / 0.99755 / 0.99765 / 0.9975 / 0.9975 / 0. The RMSECV was 0.391U 1.601.111.111.44 / 0.66, respectively, and the correlation coefficient (Rv) of the prediction set was 0.99920.99840.99764 / 0.99725 / 0.9977N RMSEP was 0.3651.9ng1.131.93n / 0.761respectively, and the correlation coefficient (RV) of the prediction set was 0.99920.9984U 0.9976U (0.99725) and 0.99775 (0.99775), respectively. It can be seen that the established quantitative analysis model can quantitatively analyze the content of adulterate in tea, and the accuracy and stability of the model can meet the general needs of detection.
【學(xué)位授予單位】：安徽農(nóng)業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：O657.33;TS272.7

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