CN112435721A - Method for constructing Longjing green tea quality discrimination model based on partial least squares - Google Patents
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Abstract
The invention discloses a method for constructing a Longjing green tea quality discrimination model based on partial least squares, and belongs to the technical field of foods. The method provided by the invention is characterized in that physicochemical indexes such as tea polyphenol, free amino acid, ascorbic acid, catechin, chlorophyll, color difference values and aroma components in Longjing green tea are used as characteristic values for analysis, effective components related to the sensory quality of green tea are determined by combining correlation analysis and principal component analysis, characteristic variables are extracted, the adaptability of different varieties of green tea to a discrimination model is discussed, and a PLS-DA quality discrimination model with high precision and good accuracy is established based on a partial least square discrimination analysis method.
Description
Technical Field
The invention particularly relates to a method for constructing a Longjing green tea quality discrimination model based on partial least squares, and belongs to the technical field of foods.
Background
Green tea is popular globally as one of the three main non-alcoholic beverages in the world. According to data of 2018 of the Chinese agricultural information network, the annual output of green tea in China reaches 166.2 ten thousand tons, which accounts for 61.0 percent of the total output of six teas in China, and the export amount of the green tea accounts for 83 percent of the total export amount of the teas, and the tea is the main tea which can generate economic benefit. In recent years, researches on green tea mainly focus on functional researches on oxidation resistance, blood sugar reduction, blood fat reduction, cancer resistance, radiation resistance, nervous recession diseases and the like.
Quality deterioration of green tea during storage directly affects its commercial value and nutritional value, and is a key factor inhibiting industrial development, and it is difficult to evaluate quality change of green tea during storage unless a quantitative model for effectively discriminating quality change of green tea is provided. Therefore, the research on the green tea quality discrimination model is carried out, an effective discrimination model is established, the discrimination model is used for evaluating the quality of the green tea in the storage process, and the method has important significance for the development of the storage and preservation technology and the improvement of the quality benefit of the green tea.
Disclosure of Invention
The method is characterized in that a Longjing green tea quality discrimination model is established based on a partial least square discrimination analysis method, the quality change rules of different grades of Longjing green tea are researched, the relevance of sensory evaluation, physicochemical indexes and intelligent sensory analysis results determined by a traditional method is determined, effective components related to the sensory quality of the green tea are determined by a statistical method (correlation analysis and principal component analysis), and characteristic variables are extracted, so that an effective green tea quality discrimination model is established, and reference is provided for standardized, standardized and digitized green tea quality discrimination. The invention establishes a PLS-DA model, discusses the adaptability of different green tea varieties to the discrimination model, and establishes a quality discrimination model with high precision and good accuracy.
The first purpose of the invention is to provide a method for establishing a Longjing green tea quality discrimination model, which comprises the following steps:
(1) determining physical and chemical indexes of the Longjing green tea to obtain data information of the Longjing green tea, then processing the obtained data information by adopting Principal Component Analysis (PCA), removing partial information which does not contribute much to the quality of the green tea or is redundant, and extracting effective principal components; grading the corresponding Longjing green tea by adopting the measured sensory evaluation score;
(2) and (3) correlating the data information measured by the processed physical and chemical indexes of the Longjing green tea with the grade scores of the corresponding Longjing green tea, and establishing a Longjing green tea quality judgment PLS-DA model.
In one embodiment of the present invention, the physicochemical indexes of the longjing green tea include: tea polyphenols, free amino acids, ascorbic acid, catechin, chlorophyll, color difference value and aroma components.
Primarily exploring evaluation indexes related to the green tea sensory quality by Pearson (Pearson) correlation analysis on the result obtained in the step 1), and then removing partial information which does not greatly contribute to the green tea quality or is redundant by Principal Component Analysis (PCA) to extract effective principal components.
The method specifically comprises the following steps:
in one embodiment of the invention, the tea samples of the Longjing green tea are purchased from three companies respectively for different grades (super, first, second, third, fourth and fifth grades), and each company takes 10 groups of tea samples of each grade for 180 tea samples to be used in the experiment.
In one embodiment of the invention, 180 samples of Longjing green tea of different grades from three enterprises in the money pool producing area are collected, and the sensory evaluation score, the physicochemical composition and the intelligent sensory analysis of each sample are systematically researched.
In one embodiment of the invention, the sensory evaluation process of the Longjing green tea is as follows:
and carrying out sensory evaluation on the appearance, liquor color, aroma, taste and leaf bottom of the Longjing green tea with different grades and carrying out single-factor analysis on the result. Tea samples are numbered randomly, 10 professional appraisers trained by tea evaluators score according to the comparison of the feelings and standard samples, the shape, the whole fragment, the cleanliness and the color of the green tea are firstly evaluated in a white-bottom tray, 3.0g (accurate to 0.01g) of each tea sample is accurately weighed, 150mL of boiling water is poured, after a cup cover is covered for brewing for 4min, soup is produced, and the fragrance, the soup color, the taste and the leaf bottom are evaluated. Each quality factor is scored according to 100 points of the total score, and the score of the evaluation of the tea sample is the sum of the individual scores of the factors multiplied by the scoring coefficient.
In one embodiment of the invention, the method for determining the physicochemical index of Longjing green tea comprises the following steps: the physicochemical indexes of tea polyphenol, free amino acid, ascorbic acid, catechin, chlorophyll, color difference value and aroma component of six kinds of Longjing green tea with different grades (special grade, first grade, second grade, third grade, fourth grade and fifth grade) are respectively measured.
In one embodiment of the present invention, the method for sample pretreatment at the time of physical and chemical mapping includes: accurately weighing 0.2g (accurate to 0.001g) of tea sample into a 10mL centrifuge tube, adding 5mL of preheated 70% methanol solution, stirring uniformly, immediately transferring into 70 ℃, carrying out water bath for 10min (shaking uniformly after 5min of water bath), cooling, centrifuging at 3500rpm for 10min, repeating the above operations on residues, transferring the supernatant into a 10mL volumetric flask for constant volume, and filtering by using a 0.45 mu m organic membrane to obtain a mother solution to be measured of the sample.
In one embodiment of the present invention, the method for measuring the content of tea polyphenol comprises:
diluting the mother liquor by 100 times, adding 5.0mL 10% Folin phenol reagent into 1mL, shaking, reacting for 5min, adding 4.0mL 7.5% Na2CO3The solution was left at room temperature for 60min, and then the absorbance at 765nm was measured. And (4) measuring the absorbance by taking the blank reagent as a reference, and then comparing with a standard curve (gallic acid) to obtain the content of the tea polyphenol.
In one embodiment of the present invention, the method for determining the content of free amino acids comprises:
taking 0.3g (accurate to 0.001g) of tea sample, adding 45mL of boiling water into a 50mL conical flask, carrying out boiling water bath for 45min (stirring and shaking uniformly every 10 min), filtering under reduced pressure when the solution is hot, washing residues for 2-3 times, transferring the residues into a 50mL volumetric flask, and fixing the volume to obtain a solution to be detected. Injecting 1mL of solution to be detected into a 25mL colorimetric tube, adding 0.5mL of phosphoric acid buffer solution with pH of 8.0 and 0.5mL of 2% ninhydrin solution, heating in boiling water bath for 15min, cooling, and adding water to constant volume to 25 mL. Standing for 10min, measuring absorbance at 570nm with blank reagent as reference, and comparing with standard curve (glutamic acid) to obtain content of free amino acids in folium Camelliae sinensis.
In one embodiment of the present invention, the method for determining the ascorbic acid content comprises:
weighing 0.2g (accurate to 0.001g) of tea sample into a 15mL centrifuge tube, adding 5mL of 20g/L metaphosphoric acid solution, shaking up, performing ultrasonic treatment for 5min, then centrifuging for 5min at 4000rpm, taking supernate, passing the supernate through a 0.45 mu m water-phase filter membrane, measuring the filtrate by using HPLC, wherein the flow rate of a mobile phase is 0.7mL/min, and the column temperature: 25 ℃, detection wavelength: 245nm, and a sample size of 20. mu.L.
In one embodiment of the present invention, the method for measuring the content of catechin includes:
diluting the mother liquor by 5 times, passing through a 0.45 mu m organic membrane, and measuring by adopting HPLC; flow rate of mobile phase 1mL/min, column temperature: 35 ℃, detection wavelength: 278nm, and the sample injection amount is 10 mu L;
the corresponding elution conditions are as follows:
in one embodiment of the present invention, the method for determining the chlorophyll content includes:
extracting chlorophyll in the sample with mixed solution of anhydrous ethanol and acetone 1:1(v: v), measuring absorbance values at 645nm and 663nm respectively, and calculating chlorophyll content with Arnon formula.
In one embodiment of the present invention, the method for measuring the colorimetric value includes:
accurately weighing 3.0g (accurate to 0.01g) of each tea sample, pouring 150mL of boiling water, covering a cup cover to brew for 4min, discharging soup, and filtering with filter paper to be tested. In the research, a high-precision color measuring instrument of Hunterlab corporation, USA, with a wavelength range of 350 nm-1050 nm (precision of 0.1nm) is adopted, a black white board and a reference liquid are used for correction in a transmission mode (TTRAN-Total transmission) before testing, water in a glass vessel is used for deducting background influence, and then tea soup color measurement is carried out.
In one embodiment of the present invention, the method for measuring an aroma component includes:
after preparation of the tea soup for each sample (as in 2.2.1.2 sensory evaluation), 5.0mL of tea soup was taken in a 20mL headspace sample bottle for electronic nose analysis. The headspace was sampled and the measurement procedure was controlled by a computer program. The measurement phase lasts 60s, which is sufficient for the sensor to reach a stable value. The interval of data collection was 1 s. The computer records the response of the electronic nose every second. After the measurement is completed, the cleaning phase continues for 70s to clean the circuit and return the sensor to its baseline, after which PCA and DFA data processing is performed in the system.
Gas Chromatography (GC) conditions: the column was a DB-Wax capillary column (30 m.times.0.25 mm, 0.25 μm).
Temperature programming conditions: the initial temperature is 40 ℃, and the temperature is kept for 2 min; raising the temperature to 80 ℃ at the speed of 1 ℃/s, and then raising the temperature to 250 ℃ at the speed of 2 ℃/s and keeping the temperature for 1 min; temperature of the column box: 50 ℃, injection port temperature: at 200 ℃.
In one embodiment of the present invention, the process of establishing the quality discrimination model includes:
all data units were converted to mg/g. The electronic nose data processing is processed by the self-contained software of the instrument system. Single-factor variance analysis, significance analysis, correlation analysis and principal component analysis, and data statistics and analysis are carried out by using SPSS statistical analysis software. And (5) establishing a PLS-DA model, and analyzing by using Matlab 2017 software. The plots were made using Origin 8.5.
The invention has the beneficial effects that:
the invention utilizes physicochemical indexes such as tea polyphenol, free amino acid, ascorbic acid, catechin, chlorophyll, color difference value and aroma component in the Longjing green tea as characteristic values to analyze, combines correlation analysis and principal component analysis to determine effective components related to the sensory quality of the green tea, extracts characteristic variables, discusses the adaptability of different green tea varieties to a discrimination model, and establishes a quality discrimination model with high precision and good accuracy.
Drawings
FIG. 1 is a PLS-DA model of Longjing green tea constructed in example 1.
FIG. 2 shows the quality discrimination of Longjing green tea by the PLS-DA model constructed in example 1.
Fig. 3 is a graph of correlation analysis between different indexes and green tea sensory scores.
FIG. 4 is a graph showing the correlation analysis of tea polyphenols, free amino acids, phenol/ammonia ratio, crude polysaccharides and ascorbic acid.
FIG. 5 is a graph showing correlation analysis of catechins.
Fig. 6 is a correlation analysis of the colorimetric values with the rating scale.
Fig. 7 is a correlation analysis of the main component analysis of the aroma component and the classification of the grade.
Detailed Description
The instruments, samples and reagents related to the present invention:
the instrument comprises the following steps:
EL204 electronic balance (shanghai mettler-toledo instruments ltd); DK-S14 electric heating constant temperature digital display water bath (Shanghai Senxin experiment instrument Co., Ltd.); heracles II flash gas chromatography e-nose (french Alpha MOS s.a. limited); UltraScan Pro1166 model high-precision spectrocolorimeter (Hunterlab, USA); UV-1800 type UV spectrophotometer (Shimadzu corporation, Japan); HPLC-high performance liquid chromatography (Agilent technologies, Inc., USA); high speed tissue masher (IKA, germany); TDL-16G desk-top high speed centrifuge (Shanghai' an pavilion scientific instruments factory).
Sample and reagent:
dragon well green tea (produced in Hangzhou Qianjin pond area, variety 43#, purchased from Hangzhou Xiaofu agriculture development Co., Ltd, Hangzhou Fuyang tea Co., Ltd, Hangzhou Yufeng tea industry Co., Ltd), Anji white tea (Song Ming white tea Co., Ltd, Zhejiang province), and Biluochun (Suzhou Jinting tea village, Jiangsu province).
The glutamic acid standard substance, the gallic acid standard substance, the catechin standard substance (C, EC, EGC, EGCG, ECG) and the ascorbic acid standard substance are HPLC chromatographic pure with the purity of more than or equal to 99 percent and are purchased from Chishiai (Shanghai) Chengcheng Industrial development Co., Ltd (TCI). Chromatographic grade methanol was purchased from the national pharmaceutical group. Sodium carbonate, forinophenol, metaphosphoric acid, ninhydrin, acetone, absolute ethanol, sulfuric acid, phenol and other common chemical reagents are analytically pure and purchased from the national medicine group.
Example 1 construction of green tea quality discrimination model
The method comprises the steps of collecting Longjing green tea purchased in different grades (superfine grade, first grade, second grade, third grade, fourth grade and fifth grade) in three companies respectively, taking 10 groups of tea samples in each grade for each company, and using 180 tea samples for experiments. Systematic study was performed on sensory evaluation scores, physicochemical components, and intelligent sensory analysis of each sample.
(1) Sensory evaluation results and single factor analysis results
And carrying out sensory evaluation on the appearance, liquor color, aroma, taste and leaf bottom of the Longjing green tea with different grades and carrying out single-factor analysis on the result. Tea samples are numbered randomly, 10 professional appraisers trained by tea evaluators score according to the comparison of the feelings and standard samples, the shape, the whole fragment, the cleanliness and the color of the green tea are firstly evaluated in a white-bottom tray, 3.0g (accurate to 0.01g) of each tea sample is accurately weighed, 150mL of boiling water is poured, after a cup cover is covered for brewing for 4min, soup is produced, and the fragrance, the soup color, the taste and the leaf bottom are evaluated. Each quality factor is scored according to 100 points of the total score, and the score of the evaluation of the tea sample is the sum of the individual scores of the factors multiplied by the scoring coefficient. The results are shown in tables 1 and 2.
TABLE 1 sensory evaluation results of different grades of Longjing green tea
Note: represents a significant difference in longitudinal direction (P < 0.05); the number of samples for each grade was 30, for a total of 180 tea samples, 10 panelists.
TABLE 2 Single factor analysis results for different grades of Longjing green tea
Under the evaluation of professional tea evaluators, the appearance, liquor color, aroma, taste, leaf bottom and total score of green tea with different grades have very significant difference (P is less than 0.01), and the total score is in a standard scoring range. Thus, these 180 samples can be used as known classes (six classes) for quality discrimination analysis, and the discrimination function is established from the data obtained from these tea samples and the sensory scores for longjing green tea quality discrimination.
(2) Factor analysis and characteristic variable extraction:
pretreatment of Longjing green tea samples: accurately weighing 0.2g (accurate to 0.001g) of tea sample into a 10mL centrifuge tube, adding 5mL of preheated 70% methanol solution, stirring uniformly, immediately transferring into 70 ℃, carrying out water bath for 10min (shaking uniformly after 5min of water bath), cooling, centrifuging at 3500rpm for 10min, repeating the above operations on residues, transferring the supernatant into a 10mL volumetric flask for constant volume, and filtering by using a 0.45 mu m organic membrane to obtain a mother solution to be measured of the sample.
And (3) measuring the content of tea polyphenol: diluting the mother liquor by 100 times, adding 5.0mL 10% Folin phenol reagent into 1mL, shaking, reacting for 5min, adding 4.0mL 7.5% Na2CO3Solutions ofAfter standing at room temperature for 60min, the absorbance at 765nm was measured. And (4) measuring the absorbance by taking the blank reagent as a reference, and then comparing with a standard curve (gallic acid) to obtain the content of the tea polyphenol.
Determination of the content of free amino acids: taking 0.3g (accurate to 0.001g) of tea sample, adding 45mL of boiling water into a 50mL conical flask, carrying out boiling water bath for 45min (stirring and shaking uniformly every 10 min), filtering under reduced pressure when the solution is hot, washing residues for 2-3 times, transferring the residues into a 50mL volumetric flask, and fixing the volume to obtain a solution to be detected. Injecting 1mL of solution to be detected into a 25mL colorimetric tube, adding 0.5mL of phosphoric acid buffer solution with pH of 8.0 and 0.5mL of 2% ninhydrin solution, heating in boiling water bath for 15min, cooling, and adding water to constant volume to 25 mL. Standing for 10min, measuring absorbance at 570nm with blank reagent as reference, and comparing with standard curve (glutamic acid) to obtain content of free amino acids in folium Camelliae sinensis.
Determination of ascorbic acid content: weighing 0.2g (accurate to 0.001g) of tea sample into a 15mL centrifuge tube, adding 5mL of 20g/L metaphosphoric acid solution, shaking up, performing ultrasonic treatment for 5min, then centrifuging for 5min at 4000rpm, taking supernate, passing the supernate through a 0.45 mu m water-phase filter membrane, measuring the filtrate by using HPLC, wherein the flow rate of a mobile phase is 0.7mL/min, and the column temperature: 25 ℃, detection wavelength: 245nm, and a sample size of 20. mu.L.
Measurement of catechin content: diluting the mother liquor by 5 times, passing through a 0.45 mu m organic membrane, and measuring by adopting HPLC; flow rate of mobile phase 1mL/min, column temperature: 35 ℃, detection wavelength: 278nm, and the sample injection amount is 10 mu L;
the corresponding elution conditions are as follows:
determination of chlorophyll content:
extracting chlorophyll in the sample with mixed solution of anhydrous ethanol and acetone 1:1(v: v), measuring absorbance values at 645nm and 663nm respectively, and calculating chlorophyll content with Arnon formula.
Measurement of colorimetric values: accurately weighing 3.0g (accurate to 0.01g) of each tea sample, pouring 150mL of boiling water, covering a cup cover to brew for 4min, discharging soup, and filtering with filter paper to be tested. In the research, a high-precision color measuring instrument of Hunterlab corporation, USA, with a wavelength range of 350 nm-1050 nm (precision of 0.1nm) is adopted, a black white board and a reference liquid are used for correction in a transmission mode (TTRAN-Total transmission) before testing, water in a glass vessel is used for deducting background influence, and then tea soup color measurement is carried out.
Measurement of aroma component: after preparation of the tea soup for each sample (method in the same sense of opinion), 5.0mL of tea soup was taken in a 20mL headspace sample bottle for electronic nose analysis. The headspace was sampled and the measurement procedure was controlled by a computer program. The measurement phase lasts 60s, which is sufficient for the sensor to reach a stable value. The interval of data collection was 1 s. The computer records the response of the electronic nose every second. After the measurement is completed, the cleaning phase continues for 70s to clean the circuit and return the sensor to its baseline, after which PCA and DFA data processing is performed in the system.
Gas Chromatography (GC) conditions: the column was a DB-Wax capillary column (30 m.times.0.25 mm, 0.25 μm).
Temperature programming conditions: the initial temperature is 40 ℃, and the temperature is kept for 2 min; raising the temperature to 80 ℃ at the speed of 1 ℃/s, and then raising the temperature to 250 ℃ at the speed of 2 ℃/s and keeping the temperature for 1 min; temperature of the column box: 50 ℃, injection port temperature: at 200 ℃.
Before modeling the original data, the physicochemical components and color difference value data of 180 tea samples are normalized, and after the normalization processing, principal component analysis is carried out to extract effective principal components. The results show that 6 principal components can be extracted according to principal component analysis, wherein the characteristic root of the first principal component is 7.317, 37.47% of the total variation is accounted, the characteristic root of the second principal component is 3.315, 21.47% of the total variation is accounted, the characteristic roots of the 6 principal components are all greater than 1, and the cumulative contribution rate is 97.95%. The specific results are shown in Table 3.
TABLE 3 principal Components analysis results
Analysis of the pearson correlation (fig. 3) revealed that the b/a value in the ratio and the chromaticity value of tea polyphenol, free amino acids, phenol/ammonia ratio, ascorbic acid, ester catechin and non-ester catechin was significantly correlated with the total score of green tea, and was a main component of the total score of green tea.
(3) Establishment of PLS-DA model
The PLS-DA is firstly grouped according to the grade of the collected tea sample, and then grade discrimination is carried out, and the obtained result is grade. As can be seen from FIG. 1, the correlation coefficient of the PLS-DA model is greater than 0.95, and the prediction set samples are very close to the 45 ° line, indicating that the model can effectively predict the green tea quality.
As can be seen from fig. 2, the prediction error of each sample predicted by the PLS-DA model is within 0-0.5 (the error is more than 0.5, i.e., the judgment error), so that the PLS-DA model has a good effect on predicting the quality of green tea, and therefore, the PLS-DA model is used in the embodiment to judge the quality of longjing green tea.
Example 2 results of measurement of various physicochemical Components and correlation analysis with scores
(1) Correlation of tea polyphenols, free amino acids, phenol to ammonia ratio, crude polysaccharide and ascorbic acid:
in conjunction with fig. 4, it can be found that: the content of tea polyphenol and free amino acid does not show obvious regularity along with the reduction of the grade, but has obvious difference (P <0.05), the regularity of the phenol-ammonia ratio is obvious, and the phenol-ammonia ratio is continuously increased along with the reduction of the grade. The content of phenol and ammonia can reflect the quality of green tea better than the content of two single indexes of tea polyphenol and free amino acid.
As the grade decreases, the ascorbic acid content also decreases significantly, reflecting the quality grade of green tea.
Chlorophyll has no significant rule among grades, but the contents of special grade, first grade and other grades have significant difference (P < 0.05).
The content analysis of crude polysaccharide showed a downward trend with decreasing grade, with significant differences between each grade (P < 0.05).
As can be seen from the correlation analysis of the sensory evaluation and each physicochemical component in table 4, the tea polyphenols, free amino acids, phenol-ammonia ratio, crude polysaccharide and ascorbic acid all have significant correlation with the sensory total fraction, with the correlation of ascorbic acid being the most significant (r: 0.9550).
TABLE 4 correlation analysis of sensory evaluation and physicochemical Components
(2) Determination of catechins and correlation analysis with scores:
the proportion of the non-ester catechin in the catechin is small, but the grades have significant difference (P is less than 0.05), and the non-ester catechin contributes to the sensory quality of the Longjing green tea. Referring to fig. 5, the non-ester catechin accounts for a relatively small amount of green tea, the ester catechin is the main component of green tea catechins and is the main component in the longjing green tea sample, and particularly, EGCG has the highest content in catechins. Ester catechin is a main flavor substance of green tea with astringency and bitterness, but the regularity between the content and grade is not significant. This indicates that the single content of ester catechin or the content of non-ester catechin cannot directly characterize the quality of green tea. However, the ratio of ester catechin to non-ester catechin decreases significantly as the grade decreases. The proportion of ester catechin to non-ester catechin is important in green tea sense, and the proper proportion of ester catechin to non-ester catechin can present better green tea taste. The total amount of catechins was as low as that of non-ester catechins, and no significant tendency was observed.
As can be seen from the correlation analysis between the green tea score and various catechins in table 5, EC and C in the non-ester catechins have no significant correlation with the sensory scores of green tea, EGC has significant negative correlation with the sensory scores, EGCG and ECG in the ester catechins have significant correlation with the sensory scores, and the correlation coefficients are consistent (r ═ 0.5290), and total catechins also have significant correlation with the sensory scores, but the highest correlation coefficient is the ratio between the ester catechins and the non-ester catechins, and the correlation coefficient with the sensory scores is-0.9120, so that the ratio between the ester catechins and the non-ester catechins can better reflect the quality of green tea to a certain extent than the single catechin index.
TABLE 5 correlation of green tea scores with various Catechin Categories
(3) Determination of the colorimetric values and their correlation with the scores:
as can be seen from fig. 6, as the levels decrease, the L, a, b and Δ E values have no significant difference between the levels. However, as the grade is reduced, the b/a is obviously reduced (the green color is lightened), which indicates that the tea soup is continuously changed from greenish to yellowish, and can reflect the quality relation among the grades.
Correlation analysis (table 6) is carried out on chroma values of 180 tea samples and soup color, aroma, taste and total ingredients in sensory evaluation, and the a value and the b/a are obviously correlated with the soup color, the aroma, the taste and the total ingredients, wherein the a value and the b/a are obviously positively correlated with each sensory factor (r is 0.323), and the b/a with obvious difference is obviously negatively correlated (r is-0.304), namely, the sensory score is lower along with the larger value of the b/a, which shows that certain pigment components in green tea can also be important factors influencing the aroma and the taste of the green tea, particularly, substances which are yellow in the green tea soup can cause negative effects on various sensory aspects of the green tea soup, and the research provides data support for establishing a quality discrimination analysis technology by combining data obtained by a color measuring instrument or processed data with physicochemical indexes, electronic nose data and the like.
TABLE 6 correlation analysis of color value and soup color, aroma, taste and total components in sensory evaluation
(4) The measurement results of the aroma components and the correlation analysis with the scores:
and (3) analyzing the aroma components of the green tea, and performing main component analysis on the aroma of green tea of different grades by utilizing PCA (principal component analysis) and DFA (DFA) processing data carried by an electronic nose. The results are shown in FIG. 7.
The initial value is used as a characteristic value for analysis, the special grade and the first grade, the second grade and the third grade, the fourth grade and the fifth grade obtained by PCA are partially overlapped by the Longjing green tea, and different grades cannot be distinguished well, but the contribution rates of PC1 and PC2 are 92.49% and 4.21%, the variance is cumulatively explained to be 96.70%, and the extracted main component is a component with a high contribution rate.
Therefore, factor discriminant analysis can be performed after classification according to grades, after discriminant analysis, the contribution rates of DF1 and DF2 are 93.80% and 5.92% respectively, the cumulative interpretation of the variance is 99.72%, the green tea discrimination between the grades is obviously improved, but the green tea discrimination of the second and third grades is general.
Comparative example 1 discrimination effect of PLS-DA model of different kinds of green tea
The PLS-DA model is used for predicting that the absolute value of prediction errors of 13 samples in the prediction values of the Anji white tea and the Biluochun tea exceeds 0.5 (the error exceeds 0.5 is misjudgment, see a middle dotted line mark), and the discrimination rate of the prediction error absolute value within 0-0.5 is 56.67%, so that the PLS-DA model has poor effect on the two kinds of green tea, and the effect is related to various factors such as green tea varieties, processes, production places and the like.
Claims (10)
1. A method for establishing a Longjing green tea quality discrimination model is characterized by comprising the following steps:
(1) determining physical and chemical indexes of the Longjing green tea to obtain data information of the Longjing green tea, analyzing and processing the obtained data information by adopting main components, and extracting effective main components; and the corresponding Longjing green tea is graded and graded by adopting measured sensory evaluation grading;
(2) and carrying out grade grading construction association on the data information measured by the processed physical and chemical indexes of the Longjing green tea and the corresponding Longjing green tea, and establishing a Longjing green tea quality judgment PLS-DA model.
2. The method according to claim 1, wherein the physicochemical indices of Longjing green tea comprise: tea polyphenols, free amino acids, ascorbic acid, catechin, chlorophyll, color difference value and aroma components.
3. The method of claim 1, wherein the physico-chemical mapping is performed by pre-treating longjing green tea as follows: accurately weighing every 0.2g of tea sample in a 10mL centrifuge tube, adding into preheated methanol solution, mixing uniformly, then moving to 70-80 ℃, stirring for 10min, then cooling, centrifuging, collecting supernatant, and repeating the above operations on residues; and collecting the supernatant, fixing the volume, and filtering by using a membrane to obtain the mother liquor to be detected of the sample.
4. The method of claim 3, wherein the method for measuring the content of tea polyphenols comprises:
diluting the mother liquor to be tested by 100 times, taking 1mL, adding 5.0mL 10% Folin phenol reagent, shaking up, reacting for 5min, adding 4.0mL 7.5% Na2CO3Standing the solution at room temperature for 60min, and measuring the absorbance at 765 nm; and (4) measuring the absorbance by taking the blank reagent as a reference, and then comparing the standard curve to obtain the content of the tea polyphenol.
5. The method according to claim 1, wherein the determination of the free amino acid content comprises:
putting 0.3g of tea sample into 45mL of boiling water, carrying out boiling water bath for 45min, filtering under reduced pressure when the tea sample is hot, washing residues for 2-3 times, collecting clear liquid, and transferring the clear liquid into a volumetric flask for constant volume to obtain a solution to be detected; mixing 1mL of solution to be detected with phosphoric acid buffer solution with pH of 8.0 and ninhydrin solution in boiling water bath, heating for 15min, cooling, adding water to constant volume, standing for 10min, measuring absorbance at 570nm with blank reagent as reference, and comparing with standard curve to obtain content of free amino acids in tea.
6. The method according to claim 1, wherein the determination of the ascorbic acid content comprises:
weighing 0.2g to 5mL of tea sample into 20g/L metaphosphoric acid solution, uniformly mixing, centrifuging, taking supernate, and filtering with a water-phase filter membrane to obtain filtrate to be detected; the filtrate was measured by HPLC.
7. The method according to claim 3, wherein the method for measuring the content of catechins comprises:
diluting the mother liquor by 5 times, passing through an organic membrane, and measuring by adopting HPLC; flow rate of mobile phase 1mL/min, column temperature: 35 ℃, detection wavelength: 278nm, sample size 10. mu.L.
8. The method according to claim 1, wherein the method for determining the chlorophyll content comprises:
extracting Longjing green tea with mixed solution of anhydrous ethanol and acetone to obtain sample solution, respectively measuring absorbance values at 645nm and 663nm, and calculating chlorophyll content with Arnon formula.
9. The method of claim 1, wherein the determining the colorimetric values comprises:
weighing 3.0g to 150mL of boiling water for each tea sample, covering a cup cover to brew for 4min, discharging soup, and filtering by using filter paper to obtain tea soup to be tested; and (3) measuring the colorimetric value of the tea soup by using a high-precision colorimeter with the wavelength range of 350-1050 nm.
10. The method according to claim 1, wherein the method of measuring aroma components comprises:
weighing 3.0g to 150mL of boiling water for each tea sample, covering a cup cover to brew for 4min, discharging soup, and filtering by using filter paper to obtain tea soup to be tested; and then analyzing the aroma components of the tea soup to be detected by using an electronic nose.
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