Anti-oxidation model for evaluating anti-oxidation capability of tea brewing liquid and confirming optimal tea brewing parameters

Abstract

The invention discloses an anti-oxidation model for evaluating tea brewing oxidation resistance and confirming optimal parameters of tea brewing, the anti-oxidation model is as follows: Y = x0-a * Z1 + b * Z2 + c * Z3 + d * Z1 * Z2 + e * Z1 * Z3-f * Z2 * Z3-g * Z12-h * Z22 + i * Z32, Y is the oxidation resistance, Z1 is the volume mass ratio of water to tea, Z2 is the water temperature, Z3 is the extraction time, x0, a, b, c, d, e, f, g, h and i are constants, and a is a constant. A plurality of groups of Z1, Z2 and Z3 values of different levels are input into intelligent analysis software and are determined after data analysis and processing. According to the invention, three factors of optimal water-tea ratio, brewing temperature and brewing time can be obtained, so that tea soup brewed from the tea leaves has better oxidation resistance, and the maximum health guarantee can be obtained after long-term drinking.

Description

Technical Field

[0001] The invention relates to an antioxidant model, in particular to an antioxidant model for evaluating the antioxidant capacity of tea brewing liquid and confirming optimal parameters for tea brewing. Background Art

[0002] Free radicals play an important role in many human diseases and tissue damage. The main free radicals in the human body - reactive oxygen species such as superoxide anions, hydrogen peroxide and hydroxyl radicals, are produced by normal metabolic processes. Excessive free radicals can easily attack biological macromolecules, thus causing damage to cells or tissues. In addition to its pharmacological functions such as anti-cancer and anti-mutation, tea polyphenols, which are rich in tea, also have significant antioxidant functions. The antioxidant substances they provide can remove excessive reactive oxygen free radicals in the body, thereby delaying aging and enhancing human resistance.

[0003] Tea contains a lot of antioxidant functional ingredients such as catechins. Green tea, for example, as a type of tea that retains a lot of antioxidant functional ingredients such as catechins, has attracted attention from all parties. Tea catechins are the main polyphenols in tea, which have pharmacological effects such as antioxidant, anti-inflammatory, anti-tumor, prevention of cardiovascular and cerebrovascular diseases, and diabetes. Tea extraction involves many factors, including the solid-liquid ratio of tea and water, the control point of the medium water temperature during extraction, and the extraction time. However, what parameters can achieve the maximum antioxidant capacity requires continuous experimental determination, which is time-consuming and labor-intensive. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an antioxidant capacity model that can be used to evaluate the antioxidant capacity of tea brewing and confirm the antioxidant capacity of tea brewing parameters. The model can be used to quickly evaluate the antioxidant capacity of tea soup and determine the optimal brewing parameters corresponding to different teas, so as to quickly obtain and drink tea soup with the best antioxidant capacity.

[0005] In order to solve the above technical problems, the present invention discloses an antioxidant model for evaluating the antioxidant capacity of tea brewing and confirming the optimal parameters of tea brewing. The antioxidant model is as follows:

[0006] Y=x0-a×Z 1 +b×Z 2 +c×Z 3 +d×Z 1 ×Z 2 +e×Z 1 ×Z 3 -f×Z 2 ×Z 3 -g×Z 1 2 -h×Z 2 2 +i×Z 32 ,

[0007] Y is the antioxidant capacity, Z 1 is the volume-to-mass ratio of water to tea, Z 2 is water temperature, Z 3 is the extraction time, x0, a, b, c, d, e, f, g, h, i are constants, and multiple groups of different levels of Z are input into the intelligent analysis software. 1 , Z 2 , Z 3 The value is determined after data analysis.

[0008] Furthermore, the intelligent analysis software is MATLAB software (a combination of the two words matrix & laboratory), SAS (Statistics Analysis System) system or DPS (Data Processing System) data processing system.

[0009] Furthermore, when the tea leaves are green tea, x0, a, b, c, d, e, f, g, h, and i are 88.91, 3.02, 4.93, 0.91, 2.61, 0.76, 0.69, 1.64, 2.83, and 0.19, respectively.

[0010] Furthermore, the antioxidant model confirmed that Z 1 The best value is 15~25mL:1g, Z 2 The best value is 70~80℃, Z 3 The optimal value is 15 to 25 minutes.

[0011] Furthermore, the antioxidant model confirmed that Z 1 The optimal value is 20mL:1g.

[0012] Furthermore, the antioxidant capacity Y obtained by the antioxidant model was verified by the luminescence inhibition rate.

[0013] Fa-Fb+Fc

[0014] Luminescence inhibition rate (%) = Fa × 100, where Fa is the luminescence intensity with luminol added but no tea soup; Fb is the luminescence intensity with both luminol and tea soup added; Fc is the luminescence intensity with tea soup added but no luminol.

[0015] The present invention studies three factors, namely, the water-to-tea ratio, brewing temperature and brewing time, which affect the leaching effect of antioxidant substances in tea, and obtains a tea antioxidant model, which is suitable for antioxidant capacity evaluation and brewing parameter confirmation of various tea brewing. Further, through three-factor analysis, constants and coefficient values ​​in the antioxidant model are obtained by analysis software for specific tea types, and finally the optimal water-to-tea ratio, brewing temperature and brewing time are obtained, so that the tea soup brewed from the tea has better antioxidant capacity, long-term drinking can obtain the greatest health protection, and tea resources can be fully utilized conveniently. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1-1 It is the residual normal probability correlation diagram of the antioxidant model of the present invention;

[0017] Figure 1-2 is the residual corresponding to the predicted value of the antioxidant model of the present invention;

[0018] Figure 1-3 is the residual corresponding to the number of times the antioxidant model experiment of the present invention is run;

[0019] Figure 1-4 It is a correlation diagram between the predicted value and the true value of the antioxidant model of the present invention;

[0020] Figure 2 is the regression curve of each single factor level and luminescence inhibition rate;

[0021] Figure 3 is the marginal effect of each single factor;

[0022] Figure 4 is the water-to-tea ratio (Z 1 ) and water temperature (Z 2 ) Contour map;

[0023] Figure 5 is the water-to-tea ratio (Z 1 ) and extraction time (Z 3 ) Contour map;

[0024] Figure 6 is the water temperature (Z 2 ) and extraction time (Z 3 ) contour map. DETAILED DESCRIPTION

[0025] The present invention is further explained below in conjunction with the examples. The following examples are only used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0026] Determination of antioxidant activity of tea samples by Fe 2+-EDTA (ethylenediaminetetraacetic acid disodium salt) solution, luminol and hydrogen peroxide composed of flow injection chemiluminescence system. In the determination of the antioxidant properties of tea soup, a certain volume of tea soup was added to the mobile phase, luminescence analysis was performed, and the luminescence inhibition rate (%) was calculated using the following formula.

[0027] Where Fa is the luminescence intensity with luminol added but without tea soup; Fb is the luminescence intensity with antioxidants added to tea soup; and Fc is the luminescence intensity with tea soup added but without luminol.

[0028] Example 1

[0029] The green tea extraction parameters were optimized by response surface method. The specific experimental design and execution are shown in Table 1 and Table 2.

[0030] Table 1 Coding values ​​of the three factors

[0031]

[0032] In Table 1, γ is the extreme point, and its specific level value is 1.682;

[0033] Factor Z 1 For example, the zero horizontal center value = (10 + 50) / 2 = 30;

[0034] Factor Z 1 For example, (50-10) / (2×1.682)=40 / 3.364≈11.89, the corresponding value of the +1 level=30+11.89=41.89, and the corresponding value of the -1 level=30-11.89=18.11.

[0035] Table 2 Implementation table of green tea response surface design and experimental results

[0036]

[0037] Establishment and testing of regression model:

[0038] The extraction rate of functional antioxidant components in green tea samples is mainly affected by water temperature, extraction time, and water-to-tea ratio. Therefore, we conducted a response surface analysis. The response surface experimental results were analyzed by regression analysis using MATLAB software. 1 , Z 2 , Z 3 The three factors were used as independent variables, and data fitting was performed on the antioxidant effect (luminescence inhibition rate), and the following multivariate quadratic regression mathematical model was established:

[0039] Y antioxidant capacity = x0-a×Z 1 +b×Z 2+c×Z 3 +d×Z 1 ×Z 2 +e×Z 1 ×Z 3 -f×Z 2 ×Z 3 -g×Z 1 2 -h×Z 2 2 +i×Z 3 2 ,Z 1 is the water-to-tea ratio (mL / g), Z 2 is water temperature (℃), Z 3 is the extraction time (min), and the values ​​of coefficients x0, a, b, c, d, e, f, g, h, and i are determined to be 88.91, 3.02, 4.93, 0.91, 2.61, 0.76, 0.69, 1.64, 2.83, and 0.19, respectively.

[0040] In order to test the validity of the antioxidant model, the mathematical model of the antioxidant luminescence inhibition rate of the tea soup obtained by green tea extraction was subjected to variance analysis (the results are shown in Table 3). As shown in Table 3, the variance ratio F value of this model is 28.99, and the model is found to be extremely significant by searching the F value table. The model established by this equation has a good fit with the actual situation (as shown in Figure 1), and the lack of fit term is not significant (P>0.05). The coefficient of variation and precision are reasonable, and the model can better fit the actual antioxidant capacity of green tea extract.

[0041] Table 3 Statistical analysis of variance sources and regression significance

[0042]

[0043] Note: Each factor has 1 degree of freedom, regression has 9 degrees of freedom, error has 10 degrees of freedom, F 0.05 (1,10)=4.96; F 0.05 (9,10)=3.02.

[0044] Model Analysis

[0045] (1) Main effect analysis

[0046] From the absolute values ​​of the coefficients of the antioxidant model equation, it can be seen that (1) the order of the first-order effect is: "Z 2 ">Z 1 ">Z 3 "; (2) The order of interaction effect is: "Z 1 ×Z 2 ">Z 1 ×Z 3 ">Z 2 ×Z3 "; (3) The order of the secondary effect is: "Z 2 2 ">Z 1 2 ">Z 3 2 ". Overall, temperature has the most significant effect on the free radical scavenging rate of the extract, and the order of the effects of the experimental factors is: "extraction water temperature" > "water-to-tea ratio" > "extraction time".

[0047] (2) Single factor effect analysis

[0048] The two factors in the antioxidant model were fixed at zero level, and the single factor models of temperature (x1), time (x2), and (x3) were obtained, which are equations (1), (2), and (3), respectively. The three factors were fixed at five levels: –γ, –1, 0, +1, and +γ, and the single factor effect diagram of each factor was obtained (see Figure 2). Figure 2 shown).

[0049] Y (绿茶) =88.91-3.02×Z 1 -1.64×Z 1 2 ……(1)

[0050] Y (绿茶) =88.91+4.93×Z 2 -2.83×Z 2 2 ……(2)

[0051] Y (绿茶) =88.91+0.91×Z 3 +0.19×Z 3 2 ……(3)

[0052] from Figure 2 It can be clearly seen that the effects of the factors water-to-tea ratio and water temperature are parabolas opening downward as the independent variable (experimental factor) changes, that is, they change at various extreme points, among which the change value of temperature is the largest.

[0053] (3) Single factor marginal effect analysis

[0054] From the marginal effect equations (4), (5) (6) and marginal effect diagrams ( Figure 3)It is not difficult to see that: ① Temperature changes have the greatest impact on marginal output. As temperature increases, the marginal antioxidant scavenging efficiency decreases; ② As temperature and water-to-tea ratio increase, the marginal antioxidant scavenging efficiency decreases, but the water-to-tea ratio decreases more slowly than temperature; ③ It can also be seen intuitively from the figure that the degree of influence of various factors on antioxidant scavenging efficiency is different at different levels, which provides parameters for selecting factors and levels to improve antioxidant scavenging efficiency under different conditions.

[0055] dY (绿茶) / dx1=-3.02-3.28×Z 1 ……(4)

[0056] dY (绿茶) / dx2=4.93-5.66×Z 2 ……(5)

[0057] dY (绿茶) / dx3=0.91+0.38×Z 3 ……(6)

[0058] (4) Analysis of two-factor effects

[0059] Fix one factor in the regression model at zero level, and obtain the two-factor model of the other two factors, which are equations (7), (8), and (9) respectively. Make a contour map based on the model.

[0060] Y (绿茶) =88.91-3.02×Z 1 +4.93×Z 2 +2.61×Z 1 ×Z 2 -1.64×Z 1 2 -2.83×Z 2 2 ……(7)

[0061] Y (绿茶) =88.91-3.02×Z 1 +0.91×Z 3 +0.76×Z 1 ×Z 3 -1.64×Z 1 2 +0.19×Z 3 2 ……(8)

[0062] Y (绿茶) =88.91+4.93×Z 2 +0.91×Z 3 -0.69×Z 2 ×Z3 -2.83×Z 2 2 +0.19×Z 3 2 ……(9)

[0063] From the water-tea ratio (Z 1 ) and water temperature (Z 2 )Contour map( Figure 4 ) It can be seen that the interactive effect is very significant. From the contour line antioxidant capacity strength index diagram, it can be seen that the change of temperature factor is more sensitive to the change of water-tea ratio.

[0064] From the water-tea ratio (Z 1 ) and water temperature (Z 3 )Contour map( Figure 5 ) It can be seen that the interaction effect is weak, and the optimal point is close to the water-to-tea ratio of 20mL / g and the extraction time of 16.15min, and reaches the maximum value near these two points. From the contour line antioxidant capacity strength index diagram, it can be seen that the change of water-to-tea ratio is slightly more sensitive to the change of extraction time.

[0065] From the water temperature (Z 2 ) and extraction time (Z 3 ) Contour line antioxidant capacity strength index diagram ( Figure 6 ) It can be seen that the interaction effect between water temperature and extraction time is weak.

[0066] In summary, the results of regression data analysis show that the extraction factors that affect the dissolution rate of its antioxidant components are at different levels, that is, the water-to-tea ratio, extraction water temperature, and extraction time range from 19.06 to 50 (mL / g), 58.33 to 100°C, and 4.6 to 20 min, respectively. Finally, the optimal water-to-tea ratio is 20 mL / g, the optimal water temperature is 78.30°C, and the extraction time is 20 min, based on the derivative results of the model equation combined with the variation law between different factors. In the response surface experimental design for luminescence intensity optimization, 6 repetitions have been set (as shown in experimental numbers 15-20 in Table 3), and the coefficient of variation of the luminescence value is 0.29 to 6.33%, that is, the repeatability is good.

Claims

1. An antioxidant model for evaluating the antioxidant capacity of tea brewing liquid and determining the optimal parameters for tea brewing, characterized in that: The antioxidant model is as follows, Y=x0-a×Z1+b×Z2+c×Z3+d×Z1×Z2+e×Z1×Z3-f×Z2×Z3-g×Z1 2 -h×Z2 2 +i×Z3 2 , Y is the antioxidant capacity, Z1 is the volume-to-mass ratio of water to tea, Z2 is the water temperature, Z3 is the extraction time, x0, a, b, c, d, e, f, g, h, i are constants, and they are determined by inputting multiple groups of Z1, Z2, and Z3 values ​​of different levels into the intelligent analysis software and then processing the data for analysis.

2. The antioxidant model for evaluating the antioxidant capacity of tea brewing liquid and confirming the optimal parameters for tea brewing according to claim 1, characterized in that: The intelligent analysis software is MATLAB software, SAS system or DPS data processing system.

3. The antioxidant model for evaluating the antioxidant capacity of tea brewing liquid and confirming the optimal parameters for tea brewing according to claim 1, characterized in that: When the tea leaves are green tea, x0, a, b, c, d, e, f, g, h, and i are 88.91, 3.02, 4.93, 0.91, 2.61, 0.76, 0.69, 1.64, 2.83, and 0.19, respectively.

4. The antioxidant model for evaluating the antioxidant capacity of tea brewing liquid and confirming the optimal parameters for tea brewing according to claim 1, characterized in that: The optimal value of Z1 confirmed by the antioxidant model is 15-25 mL:1 g, the optimal value of Z2 is 70-80°C, and the optimal value of Z3 is 15-25 min.

5. The antioxidant model for evaluating the antioxidant capacity of tea brewing liquid and confirming the optimal parameters for tea brewing according to claim 4, characterized in that: The optimal value of Z1 confirmed by this antioxidant model is 20mL:1g.

6. The antioxidant model for evaluating the antioxidant capacity of tea brewing liquid and confirming the optimal parameters for tea brewing according to claim 1, characterized in that: The antioxidant capacity Y obtained from this antioxidant model was verified by the luminescence inhibition rate. Where Fa is the luminescence intensity with luminol added but no tea soup; Fb is the luminescence intensity with both luminol and tea soup added; Fc is the luminescence intensity with tea soup added but no luminol.

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