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目的采用电子舌技术研究羟丙基-β-环糊精(HP-β-CD)质量浓度(C)变化对苦味化合物及苦味中药的抑苦规律。方法以盐酸小檗碱、氧化苦参碱、苦参水煎液、穿心莲水煎液为苦味载体,基于口尝评价结果(ΔI)和电子舌信息(ΔI_e),分别建立ΔI-C、ΔI_e-C 2个抑苦规律模型、探索ΔI-ΔI_e两者的抑苦效果预测模型,并使用交叉验证和残差分析法对预测模型的拟合精度和优度进行评价。结果对4种苦味载体均建立了良好的ΔI-C威布尔抑苦规律模型,决定系数(R~2)依次为0.999 6、0.987 9、0.996 4、0.998 4(P<0.01);盐酸小檗碱、苦参水煎液和穿心莲水煎液的6个(每个载体2根传感器)ΔI_e-C威布尔抑苦规律模型的R~2依次为0.996 5、0.991 6、0.997 3、0.989 3、0.999 6、0.999 1(P<0.01);相应的6个ΔI-ΔI_e线性抑苦效果预测模型的R~2依次为0.989 1、0.968 3、0.989 0、0.982 0、0.977 9、0.986 1(P<0.01);上述6个预测模型交叉验证的相关系数(R)依次为0.986 0、0.997 3、0.988 4、0.960 8、0.980 2、0.983 9(P<0.01)。测试质量浓度范围内的氧化苦参碱对电子舌4根传感器均无随浓度变化的差异性响应,因此未能建立各类模型。结论基于电子舌方法得到了随HP-β-CD质量浓度变化的抑苦规律,建立了以HP-β-CD质量浓度或电子舌数据为基础的预测模型,可用于相关抑苦效果预测。部分苦味化合物对电子舌的响应没有相关规律,有待电子舌技术的进一步研发。
OBJECTIVE To study the inhibition of bitterness compounds and bitter herbs by using electronic tongue technology to study the changes of mass concentration (C) of hydroxypropyl-β-cyclodextrin (HP-β-CD) Methods Based on the results of mouth-taste evaluation (ΔI) and electronic tongue information (ΔI_e), berberine hydrochloride, oxymatrine, sophora liquid and water extract of Andrographis paniculata were used as bitter carrier to establish ΔI-C and ΔI_e- C 2 depressive rule model to explore the ΔI-ΔI_e depressive effect prediction model of both, and the use of cross-validation and residual analysis of the prediction model to evaluate the accuracy and goodness of fit. Results A good ΔI-C Weibull inhibition model was established for all four bitter vectors. The determination coefficients (R ~ 2) were 0.999 6,0.987 9,0.996 4,0.998 4 (P <0.01) 6 (2 sensors per carrier) of alkali, kushen Decoction and Andrographis paniculata were 0.996 5,0.991 6,0.997 3,0.989 3, 0.999 6,0.999 1 (P <0.01). The R 2 of the 6 prediction models of ΔI-ΔI_e were as follows: 0.989 1, 0.968 3, 0.989 0, 0.982 0, 0.977 9, 0.9861 (P < 0.01). The correlation coefficients (R) of the cross validation of the above six prediction models were 0.986 0,0.997 3,0.988 4,0.960 8,0.980 2,0.983 9 (P <0.01). Oxymatrine within the test mass concentration showed no difference in concentration response to the four sensors of the electronic tongue, and various models could not be established. Conclusion Based on the electronic tongue method, the inhibition of the HP-β-CD mass concentration was obtained. The prediction model based on HP-β-CD mass concentration or electronic tongue data was established, which could be used to predict the effect of depressing pain. Some bitter compounds on the electronic tongue response no relevant rules, electronic tongue technology to be further developed.