Processing technology of wild honeysuckle tea

Abstract

The invention relates to a wild honeysuckle flower tea processing technology, and belongs to the technical field of wild honeysuckle flower tea processing, and the wild honeysuckle flower tea processing technology comprises the following steps: taking blooming fresh wild honeysuckle flower as a raw material, carrying out fixation on the blooming fresh wild honeysuckle flower at a fixation temperature of 200-300 DEG C for 3-7 minutes, and drying the blooming fresh wild honeysuckle flower after fixation at a drying temperature of 100-120 DEG C for 3-7 minutes, the drying time is 40-70 minutes, the optimized enzyme deactivation temperature is 250 DEG C, the enzyme deactivation time is 7 minutes, the drying temperature is 110 DEG C, and the drying time is 60 minutes; the method has the beneficial effects that the method is suitable for large-scale production, the apparent quality of the honeysuckle tea is improved, and the retention rate of effective components is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of honeysuckle tea processing, and in particular to a honeysuckle tea processing technology, which significantly improves the apparent quality, effective ingredient retention rate and processing efficiency of honeysuckle tea by optimizing the combination of fixing temperature, fixing time and drying temperature. Background Art

[0002] In the traditional processing technology of honeysuckle tea, steam-killing honeysuckle tea can easily lead to large heat energy loss, temperature fluctuations in killing green tea, deformation of honeysuckle tea when it comes into contact with water vapor, and low drying efficiency, which causes the honeysuckle tea to turn brown in color, become loose in texture, and lose the effective ingredient of chlorogenic acid.

[0003] Previous research has shown that the drying temperature for honeysuckle tea is typically set between 80-100°C or 100-200°C. Lower drying temperatures prolong the drying time (i.e., 10 minutes, exceeding the normal drying time of 3-7 minutes), reduce the tea's efficiency, and can easily cause the processed tea, namely honeysuckle tea, to deform and brown. Prior art processes lack scientific optimization of the drying temperature parameters for honeysuckle tea, making it difficult to balance processing efficiency and quality improvement. Summary of the Invention

[0004] The present invention provides a processing technology for honeysuckle tea, which is used to solve the technical problems of poor apparent quality and low effective ingredient retention rate of honeysuckle tea in traditional processes. The withering temperature, withering time and drying temperature are optimized through single-factor optimization analysis and three-factor three-level orthogonal experiment, so that the apparent quality of honeysuckle tea is improved and the effective ingredient retention rate is improved.

[0005] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0006] A processing technology for honeysuckle tea comprises the following steps:

[0007] Use fresh honeysuckle flowers as raw materials;

[0008] Fix the fresh honeysuckle flowers: the fixing temperature is 200-300℃ and the fixing time is 3-7 minutes;

[0009] The open fresh honeysuckle after withering is dried: the drying temperature is 100~120℃, and the drying time is 40~70 minutes.

[0010] Optionally, the fixing temperature is 250°C, the fixing time is 7 minutes, the drying temperature is 110°C, and the drying time is 60 minutes.

[0011] Optionally, the finished product of the obtained honeysuckle tea has a bright green color and a hard and crisp texture.

[0012] Optionally, the finished product ingredients of the obtained honeysuckle tea are: protein ≥12g / 100g, soluble sugar ≥11%, tea polyphenols ≥7%, tannin ≥624mg / kg, free amino acids ≥3mg / g, caffeine ≥1.2mg / g, and chlorogenic acid ≥5%.

[0013] Optionally, the single factor optimization analysis adopts a fixing temperature of 200-400°C, a fixing time of 1-9 minutes, and a drying temperature of 80-120°C.

[0014] Optionally, based on the results of single-factor optimization analysis, a three-factor three-level orthogonal design experiment was used to test the effects of withering temperature, withering time, and drying temperature on the quality of honeysuckle tea, and the optimal parameter combination was obtained: withering temperature of 250°C, withering time of 7 minutes, and drying temperature of 110°C.

[0015] Alternatively, use fresh open honeysuckle flowers, which have a moisture content of 88.29%.

[0016] The fresh honeysuckle flowers are fixed at a temperature of 250°C for 7 minutes. After fixing, the honeysuckle flowers are bright green, hard and crisp, and not burnt.

[0017] Dry the fresh honeysuckle flowers after they have been fixed: the drying temperature is 110°C, and the drying time is 60 minutes until the moisture content is ≤8%.

[0018] Optionally, the finished product ingredients of the obtained honeysuckle tea are: chlorogenic acid content of 5.42%, protein content of 12.77g / 100g, soluble sugar content of 15.8%, free amino acid content of 3.72mg / g, tea polyphenols content of 7.87%, caffeine content of 1.21mg / g, and tannin content of 624.33mg / kg.

[0019] Optional: the appearance of honeysuckle tea: bright green in color, complete in shape, prickly when held and crisp when plucked.

[0020] Beneficial effects of the present invention:

[0021] The present invention optimizes the combination of the fixing temperature, the fixing time and the drying temperature, so that the finished honeysuckle tea has a bright green color and a hard and crisp texture after fixing, and the retention rate of effective ingredients such as chlorogenic acid, soluble sugar and tea polyphenols is significantly improved. The invention is suitable for large-scale production, and improves the apparent quality of honeysuckle tea and the retention rate of effective ingredients. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 is a process flow chart of the present invention;

[0024] Figure 2 This is a comparison diagram of the phenotypes of honeysuckle under the single factor test of the present invention (bright green, brown, and charred);

[0025] Figure 3 The phenotypic statistics of Lonicera japonica after the orthogonal optimization process of the present invention;

[0026] Figure 4 This is a bar chart comparing the nutritional components of various embodiments of the present invention;

[0027] Figure 5 The chlorogenic acid content of honeysuckle tea after orthogonal optimization treatment of the present invention is determined;

[0028] Figure 6 This is the fusion analysis of the ingredients of Lonicera japonica tea after orthogonal process optimization of the present invention. DETAILED DESCRIPTION

[0029] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0030] Example 1

[0031] like Figure 1 As shown, this embodiment provides a processing technology for honeysuckle tea, comprising the following steps:

[0032] Use fresh honeysuckle flowers as raw materials;

[0033] Fix the fresh honeysuckle flowers: the fixing temperature is 200-300℃ and the fixing time is 3-7 minutes;

[0034] The open fresh honeysuckle after withering is dried: the drying temperature is 100~120℃, and the drying time is 40~70 minutes.

[0035] Specifically, we first use a single-factor variance model to optimize the analysis: Data preparation: Collect observational data on different levels of a factor. For example, to study the effect of different fertilizer application rates on crop yield, fertilizer application rate is the factor, and there are multiple different fertilizer application levels, with several observations of crop yield at each level.

[0036] Calculate the sum of squares: Calculate the sum of squares between groups (SSB): ,in, is the number of levels of the factor, It is The number of observations at each level, It is The mean of the observations at each level, is the grand mean of all observations. SSB measures the degree to which the means of the different level groups differ from the grand mean.

[0037] Calculate the within-group sum of squares (SSW): ,in, It is The first level SSW reflects the degree of dispersion of observations within each level relative to the mean value of that level, that is, the size of the random error.

[0038] Calculate the total sum of squares (SST): ,and .

[0039] Calculate mean square:

[0040] Calculate the mean square between groups (MSB): , whose degrees of freedom are .

[0041] Calculate the within-group mean square (MSW): , whose degrees of freedom are ,in, , is the total number of observations.

[0042] calculate Statistics: If the different levels of the factors have a significant effect on the observed variables, then the inter-group variation will be large. The value will be greater than 1; on the contrary, if the different levels of the factor have no significant effect on the observed variable, the variation between groups is mainly caused by random errors. The value will be close to 1.

[0043] Determine the significance level And find the critical value: usually take =0.05 or =0.01, etc. According to the degree of freedom and significance level , search Distribution table to get critical value .

[0044] Make a decision: The calculated Value and critical value Compare. If , then reject the null hypothesis , it is believed that different levels of factors have a significant impact on the observed variables; if , then the null hypothesis is not rejected , that is, it is believed that the different levels of the factors have no significant effect on the observed variables.

[0045] Specific Applications: Single-factor variance model optimization analysis has a wide range of applications in fields such as agriculture, medicine, social sciences, and engineering. For example, in agriculture, it can be used to compare the yield differences between different wheat varieties; in medicine, it can be used to study the efficacy of different drugs in treating a certain disease; in social sciences, it can be used to analyze whether there are significant differences in income between people with different educational levels; and in engineering, it can be used to explore the impact of different process parameters on product quality. Single-factor variance model optimization analysis can help researchers determine whether a factor has a significant impact on the research object, providing a basis for further research and decision-making.

[0046] The optimization analysis of the single-factor variance model requires the following assumptions: Independence: Each observation is independent of each other, meaning that each observation is not affected by other observations. Normality: The observations at each level follow a normal distribution. Homogeneity of variance: The population variances at each level are equal.

[0047] In practical applications, these assumptions need to be tested. If the data do not meet these assumptions, the analysis results may be inaccurate. In this case, it is necessary to consider transforming the data or using other non-parametric test methods.

[0048] like Figure 1 Shown is the technical route for processing honeysuckle tea.

[0049] The present invention adopts single factor optimization analysis: that is, adopting single factor variance model analysis. Single factor variance model analysis is based on the idea of ​​variance decomposition, which decomposes the total variance (total sum of squares) into inter-group variance (inter-group sum of squares) and intra-group variance (intra-group sum of squares). Inter-group variance reflects the influence of factors of different levels on the observed variables, while intra-group variance reflects the influence of random errors. By comparing the size of the inter-group mean square and the intra-group mean square, the constructed Statistics are used to determine whether different levels of factors have a significant impact on the mean of the observed variable.

[0050] The optimization analysis of the single-factor variance model is as follows: the fixing temperature is set at 200~400℃, the fixing time is 1~9min, the drying temperature is 80℃~120℃, and the middle value of each experiment is taken as fixing temperature 300℃, fixing time 5min, and drying temperature 100℃. Using the data in Table 1, the appearance of the processed honeysuckle samples is significantly different from that of the fresh samples.

[0051] Table 1 / Single factor experimental design table

[0052]

[0053] like Figure 2 As shown, the colors are bright green, brown, and burnt yellow, and the textures are soft, hard, and crisp. ( Figure 2 In the sample, A: fresh sample, B: browned sample, C: charred sample, D: qualified sample). Qualified products are characterized by bright green color, firm texture, prickly texture, and crispness when touched. Test results from the fixation temperature test showed that after fixation at 200°C, 250°C, and 300°C, the honeysuckle samples had a bright green appearance, meeting the process requirements of "prickly texture and crispness when touched." Samples fixed at 350°C and 400°C charred and easily became powdery, failing to meet production requirements. Therefore, subsequent tests were conducted at 200°C, 250°C, and 300°C. Test results from the fixation time test showed that samples fixed for 1 minute failed to set, while samples fixed for 3, 5, and 7 minutes met the process requirements. The sample fixed for 9 minutes charred. Therefore, subsequent tests were conducted at 3, 5, and 7 minutes. The results of the drying temperature test showed that there was no obvious difference in the appearance of honeysuckle within the design temperature range, and the drying temperature was inversely proportional to the time to meet the process requirements. Therefore, 100℃, 110℃ and 120℃ were selected for subsequent tests.

[0054] Re-orthogonal optimization: According to the results of single factor analysis, a three-factor three-level orthogonal design based on extreme value model analysis was used to explore the effects of withering temperature, withering time and drying temperature on the quality of honeysuckle tea.

[0055] Extreme value models are often used to analyze extreme values ​​in data. For example, in fields such as engineering, the environment, and finance, the focus may be on rare extreme events or data points. For example, in structural engineering, it is necessary to consider the response of buildings under extreme loads (such as strong winds and earthquakes); in finance, extreme fluctuations in asset prices may be of interest. Extreme value models can be used to model and analyze these extreme conditions, assessing their probability, trends, and impact on the system, providing a basis for risk management and design standard development.

[0056] Extreme value model related formula:

[0057] Generalized Extreme Value Distribution (GEV) formula: In extreme value model analysis, generalized extreme value distribution is often used to describe the distribution law of extreme values. Its probability density function is ,in, , , is a positional parameter, is the scale parameter, is the shape parameter. Different The values ​​correspond to different distribution types. = 0, the generalized extreme value distribution degenerates into the Gumbel distribution; when >0, corresponding to the Frechet distribution; when <0, corresponding to Weibull distribution. By fitting the observed data, we can estimate 、 and The distribution can be used to predict the probability of extreme values.

[0058] Threshold model (POT) formula: Another commonly used extreme value model is the peak value model (POT) based on the threshold. is the threshold, and the data exceeding the threshold is recorded as ,in, is the number of data exceeding the threshold. Assume It obeys the generalized Pareto distribution (GPD), and its probability density function is , , ;when hour, Similarly, by fitting the data, we can estimate the values ​​of σ and ξ, and then analyze and predict the extreme values ​​that exceed the threshold, for example, we can calculate the probability of an extreme event that exceeds a certain threshold.

[0059] In practical applications, other related formulas may also be involved, such as the maximum likelihood estimation formula for model parameter estimation. These formulas together constitute a research method system based on extreme value model analysis and using a three-factor, three-level orthogonal design. They help researchers extract valuable information from experimental data and gain a deeper understanding of the influence of factors on extreme values.

[0060] Three-factor three-level orthogonal design:

[0061] Factors and Levels:

[0062] Factors are variables that can influence the outcome of an experiment or study. The three factors mentioned here are three such variables. For example, when studying a chemical reaction, temperature, reactant concentration, and reaction time might be three factors.

[0063] Levels: The different states or values ​​that each factor can take. Three levels means each factor can take three different values. For example, the temperature factor might have three levels: 50°C, 60°C, and 70°C; the reactant concentration factor might have three levels: 10%, 20%, and 30%; and the reaction time factor might have three levels: 1 hour, 2 hours, and 3 hours.

[0064] About three-factor three-level orthogonal design orthogonal design:

[0065] It is a scientific and rational experimental design method that uses an orthogonal array to arrange experiments, resulting in a relatively small number of experiments while fully reflecting the impact of various factors and their interactions on the experimental results. For a three-factor, three-level orthogonal design, a specific orthogonal array is used to guide the experimental arrangement. For example, according to the requirements of the orthogonal array, nine experiments (combinations of different factor levels) may be arranged. This allows for a more efficient study of the impact of the three factors at different levels on the results, without having to conduct all possible combinations (3×3×3=27 experiments), significantly saving experimental costs and time.

[0066] Orthogonal design related formula: Determine the number of experiments: For a three-factor three-level orthogonal design, the orthogonal table commonly used is ,here represents the orthogonal array, 9 is the number of experiments, 3 is the number of factor levels, and 4 is the maximum number of factors that can be arranged (including interaction columns). Therefore, the determination of the number of experiments is based on the characteristics of the orthogonal array, and its formula can be simply understood as , which is the square of the number of levels. This is because in the case of three factors and three levels, through the reasonable design of the orthogonal array, only nine experiments are needed to fully examine the impact of different level combinations of each factor on the results.

[0067] Calculate the range of factors: The range is an indicator used to measure the degree of influence of factors on experimental results. For the Each factor in The sum of experimental indicators at the level, For the The factor in The number of experiments under the level. The first factor Mean of the levels . Then The range of factors The larger the range, the more significant the impact of this factor on the experimental results.

[0068] Combination of the two:

[0069] Extreme value model analysis employs a three-factor, three-level orthogonal design. This utilizes the efficient experimental design method of orthogonal design to arrange experiments, obtain data from different factor level combinations, and then analyze the extreme values ​​within these data using the extreme value model to understand the patterns of occurrence of extreme values ​​under the influence of different factor levels, the influencing factors, and the potential impact on the entire system or process. For example, when studying the mechanical properties of a material under different environmental conditions (temperature, humidity, and pressure, each at three levels), an orthogonal design experiment is conducted, followed by an extreme value model to analyze the material's performance under extreme stress conditions, providing a reference for the material's safe use and design.

[0070] The factor level coding provided by the present invention is obtained based on extreme value model analysis and adopts a three-factor three-level orthogonal design, specifically as shown in Table 2:

[0071] Table 2 / Factor level coding table

[0072]

[0073] The experimental design and implementation plan based on extreme value model analysis and three-factor three-level orthogonal design are shown in Table 3:

[0074] Table 3 / Orthogonal experiment design and specific implementation table

[0075]

[0076] Among them, L5, L6 and L8 are bright green, hard and crisp after processing. Figure 3 The results are shown in Table 1, which are the orthogonal test L1 to L9 treatments. The nutritional indicators of protein, tea polyphenols, tannins, and free amino acids are all very high, and the chlorogenic acid content exceeds 5.0% (e.g. Figure 4-Figure 6 ). Figure 4 This is the orthogonal treatment of honeysuckle nutrient detection, Figure 5 The content of chlorogenic acid in honeysuckle was determined by high performance liquid chromatography. Figure 6 It is a multi-dimensional fusion analysis.

[0077] Therefore, the optimal parameter combination is obtained: L6, that is, the fixing temperature is 250℃, the fixing time is 7 minutes, and the drying temperature is 110℃.

[0078] The honeysuckle tea of ​​the present invention has a bright green color and a hard and crisp texture; the chlorogenic acid content is ≥5%,

[0079] Protein ≥12 g / 100g, soluble sugar ≥11%, tea polyphenols ≥7%, tannin ≥624 mg / kg, free amino acids ≥3 mg / g, caffeine ≥1.2 mg / g.

[0080] Example 2

[0081] Based on Example 1, the optimal parameter combination: L6 process:

[0082] Raw material processing: open fresh honeysuckle, moisture content 88.29%;

[0083] Fixing: Fixing temperature is 250℃, fixing time is 7 minutes, after fixing, the color of Shan Yin Hua is bright green, the texture is hard and crisp, without scorch;

[0084] Drying: Drying temperature is 110℃, drying to moisture content ≤8%, taking 60 minutes;

[0085] Finished product features:

[0086] Appearance: Bright green in color, intact in shape, feels firm when held and brittle when touched;

[0087] Ingredients: Chlorogenic acid content is 5.42%, protein content is 12.77 g / 100g, soluble sugar content is 15.8%, free amino acid content is 3.72 mg / g, tea polyphenols content is 7.87%, caffeine content is 1.21 mg / g, and tannin content is 624.33 mg / kg.

[0088] Example 3

[0089] Auxiliary parameter combination: L5 process:

[0090] Raw material processing: open fresh honeysuckle, moisture content 88.29%;

[0091] Fixing: temperature 250℃, time 3 minutes;

[0092] Drying: temperature 120℃, time 55 minutes;

[0093] Finished product features:

[0094] Appearance: light green in color, slightly soft in texture;

[0095] Ingredients: Chlorogenic acid 4.72%, soluble sugar 18%, tea polyphenols 7.17%, tannin 624.33 mg / kg, free amino acid 3.79 mg / g, caffeine 1.29 mg / g, protein 12.73g / 100g.

[0096] Example 4

[0097] Raw material processing: open fresh honeysuckle, moisture content 88.29%;

[0098] Fixing: temperature 300℃, time 5 minutes;

[0099] Drying: temperature 120℃, time 55 minutes;

[0100] Finished product features:

[0101] Appearance: yellow-green in color, hard and brittle in texture;

[0102] Ingredients: Chlorogenic acid 5.0%, soluble sugar 11.87%, tea polyphenols 8.2%, tannin 624.33mg / kg, free amino acid 3.84mg / g, caffeine 1.22mg / g, protein 12.7g / 100g.

[0103] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope of the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A processing technology for honeysuckle tea, characterized by: The following steps are involved: Use fresh honeysuckle flowers as raw materials; Fix the fresh honeysuckle flowers: the fixing temperature is 200-300℃ and the fixing time is 3-7 minutes; The open fresh honeysuckle after withering is dried: the drying temperature is 100~120℃, and the drying time is 40~70 minutes.

2. The processing technology of honeysuckle tea according to claim 1, characterized in that: The fixing temperature is 250° C., the fixing time is 7 minutes, the drying temperature is 110° C., and the drying time is 60 minutes.

3. The processing technology of honeysuckle tea according to claim 2, characterized in that: The obtained finished product of honeysuckle tea has bright green color and hard and crisp texture.

4. The processing technology of honeysuckle tea according to claim 2, characterized in that: The finished product ingredients of the obtained honeysuckle tea are: protein ≥12g / 100g, soluble sugar ≥11%, tea polyphenols ≥7%, tannin ≥624mg / kg, free amino acids ≥3mg / g, caffeine ≥1.2mg / g, and chlorogenic acid ≥5%.

5. The processing technology of honeysuckle tea according to claim 1, characterized in that: The single factor optimization analysis adopted was a fixing temperature of 200-400℃, a fixing time of 1-9 minutes, and a drying temperature of 80-120℃.

6. The processing technology of honeysuckle tea according to claim 5, characterized in that: According to the results of the single-factor optimization analysis, a three-factor three-level orthogonal experiment was used to test the effects of withering temperature, withering time and drying temperature on the quality of honeysuckle tea, and the optimal parameter combination was obtained: withering temperature of 250℃, withering time of 7 minutes and drying temperature of 110℃.

7. The processing technology of honeysuckle tea according to claim 5, characterized in that: Use fresh honeysuckle flowers that are open, the moisture content of which is 88.29%; The fresh honeysuckle flowers are fixed at a temperature of 250°C for 7 minutes. After fixing, the honeysuckle flowers are bright green, hard and crisp, and not burnt. The open fresh honeysuckle flowers after withering are dried: the drying temperature is 110°C, and the drying time is 60 minutes until the moisture content is ≤8%.

8. The processing technology of honeysuckle tea according to claim 7, characterized in that: The finished product ingredients of the obtained honeysuckle tea are: chlorogenic acid content of 5.42%, protein content of 12.77g / 100g, soluble sugar content of 15.8%, free amino acid content of 3.72mg / g, tea polyphenol content of 7.87%, caffeine content of 1.21mg / g, and tannin content of 624.33mg / kg.

9. The processing technology of honeysuckle tea according to claim 8, characterized in that: The appearance of the honeysuckle tea is: bright green in color, complete in shape, prickly when held and crisp when plucked.

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