CN107462607B - A kind of detection method of the fermentation of black tea appropriateness based on electrical characteristic parameter - Google Patents
A kind of detection method of the fermentation of black tea appropriateness based on electrical characteristic parameter Download PDFInfo
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Abstract
The present invention relates to technical field of food detection, more particularly to a kind of detection method of the fermentation of black tea appropriateness based on electrical characteristic parameter, it is that the tealeaves of Various Fermenting Degree is respectively placed in the measurement that electrical characteristic parameter is carried out in electrical characteristics test system, the index of quality is detected simultaneously, carry out grade calibration, pretreatment is standardized to electrical characteristic parameter, screen the preferred feature frequency that suitable fermentation quality differentiates, filter out preferred feature electrical characteristic parameter, carry out principal component analysis, to establish prediction black tea dynamic fermentation appropriateness model, for realizing that the prediction to appropriate grade of fermenting differentiates.Detection method of the invention overcomes the deficiency of the methods of artificial sense evaluation and Physico-chemical tests, realize standardization, stabilisation, the intelligence moderately detected to fermentation of black tea, rapid and precision, has important practical significance and application prospect in the detection of fermentation of black tea appropriateness.
Description
Technical field
Appropriate the present invention relates to technical field of food detection more particularly to a kind of fermentation of black tea based on electrical characteristic parameter
Detection method.
Background technique
China is the area of origin of tea tree, is the world's largest Chan Cha state.Tea industry is in the Belt and Road national strategy
Environmental health industry in 2030 strategy of traditional advantage characteristic export-oriented industry and Health China.Spy of the black tea as China
There is tea, important position is occupied in international tea market.Fermentation is the most key process in black tea processing, directly decision at
The quality and flavor characteristic sampled tea.During the fermentation, can occur based on polyphenol compound after tea cell film is impaired
Enzymatic oxidation reaction and association response, generate based on theaflavins (TFs), thearubigin class (TRs) and theabrownin class (TBs)
A series of organic pigment substances, synthesis form the distinctive color of black tea, taste and aroma quality.Only appropriate fermentation
The black tea of high-quality could be obtained, it is thus determined that fermentation appropriateness is of crucial importance.
The method of currently used control fermentation appropriateness has sense organ determining method, measurement temperture of leaves method, biochemical indicator method, electronic nose
Method etc., while some fermentation indicating equipments are had developed, but these equipment operations are complicated, expensive.It sends out in actual production
The regulation of ferment degree is main or processing staff judges with the sense organ of oneself from the variation of the characterization of fermentated leaves, such as sees fermentated leaves
The variation etc. of the degree of red change, fragrance determines that fermentation is enough to reach appropriateness, and accuracy is easy by experience and external environment
It influences, cause fermentation partially light or excessively, directly influences product quality, the stability of flavor and uniformity, quality safety risk
Factor is significantly greatly increased.Therefore, it realizes fermentation of black tea standardization, stabilizes, is intelligent, quick, accurate judgement fermentation appropriateness has
Important meaning.
Bound charge in biology interior molecule is known as dielectric property to the response of extra electric field.Electrical characteristics detection technique is
The inner link with component content is established using the variation of test substance electromagnetic property, and then realizes food quality or the inspection of material attribute
Survey a kind of fast non-destructive detection method, major parameter include: its major parameter include: capacitor, resistance, reactance, loss because
Son and impedance etc..Uneven electrolyte of the tealeaves between conductor and insulator, when black tea fermentation process sample is placed in electric field
When middle, internal charged particle will form bio-electric field, have the effects of obstruction, receiving, loss, conduction to electric field charge, with
The change of fermented sample endoplasm ingredient, structure and physiological status, will lead to the electrically charged and quantity of electric charge of chemical substance in tissue
It changes in terms of spatial distribution and intensity, macroscopically shows the variation of electrical parameter.Electrical characteristic parameter has been widely applied
In quick, the lossless maturity for judging fruits and vegetables, cereal and meat products, nutrition condition etc., but its application in tealeaves research
Then report is few.And the application during fermentation of black tea in the detection of product property appropriateness is had not been reported.
Summary of the invention
In view of this, the detection side of the object of the present invention is to provide a kind of fermentation of black tea appropriateness based on electrical characteristic parameter
Method, it is intended to overcome the shortcomings of artificial sense evaluation and the methods of Physico-chemical tests, realize the standardization that fermentation of black tea is moderately detected,
It stabilizes, is intelligent, rapid and precision has important practical significance and answers in the on-line checking of fermentation of black tea appropriateness
Use prospect.
The present invention solves above-mentioned technical problem by following technological means:
A kind of detection method of the fermentation of black tea appropriateness based on electrical characteristic parameter, the tealeaves of Various Fermenting Degree is set respectively
The measurement of electrical characteristic parameter is carried out in electrical characteristics test system, while detecting the index of quality, grade calibration is carried out, to electrical characteristics
Parameter carries out Screening Treatment, so that prediction black tea dynamic fermentation appropriateness model is established, for realizing to the pre- of appropriate grade of fermenting
It surveys and differentiates, comprising the following steps:
S1. the building of electrical characteristics test system, the electrical characteristics test system include bridge test instrument, test electrode, take
Sample box, operation host and acquisition software, are equipped with disperser on the sampling box, the bridge test instrument by R232 serial ports with
It runs host and carries out data exchange, and two test electrodes are connected by twisted-pair shielded wire；
S2. the measurement of sample electrical characteristic parameter dissipates the Tea Samples of different fermentations time naturally by disperser respectively
It drops into sampling box, and Tea Samples is made to flood test electrode, respectively at measuring electrical characteristic parameter under different frequency；
S3. fermentation quality detection and grade calibration, detect the index of quality of different fermentations time Tea Samples, and to fermentation
Quality carries out grade calibration；
S4. data screening processing and Model checking, are standardized pretreatment to electrical characteristic parameter, using based on phase relation
Several and principal component characteristic frequency composite index analysis method selects the preferred feature frequency that suitable fermentation quality differentiates, using nothing
Information variable null method-competitiveness adaptive weighting sampling method, which is combined, filters out preferred feature electrical characteristic parameter, to preferred feature
Each electrical characteristic parameter and preferred feature electrical characteristic parameter under frequency carry out PCA analysis respectively, using optimal principal component as input
Operating limit learning machine pattern discrimination is measured, to establish the dynamic fermentation appropriateness detection model of black tea.
S5. the quick detection of black tea dynamic fermentation appropriateness is connected to computer client, real-time Transmission fermentation by data line
The electrical characteristic parameter data of sample are analyzed in conjunction with the fermentation appropriateness detection model that acquisition software is written at software interface end in real time
The fermentation appropriateness grade of fermentation sample, realizes the qualitative quick detection of black tea dynamic fermentation appropriateness.
Further, the test frequency range of the bridge test instrument is 50Hz~200kHz, and the test electrode is copper
Parallel plate electrode plate, the area of the electrode plate are 20cm2, the bottom plate side of the sampling box is hinged, corresponding with side plate
The other side is detachably connected with corresponding side plate, and the disperser includes motor, shaft and the moving tooth being fastened around in shaft,
The shaft is connect with motor drive, and the revolving speed of the shaft is greater than 1000r/min.
The electric parameters testing circuit of bridge test instrument is divided into series, parallel equivalent-circuit model, and usual low impedance element is used
Series connection, from numerically say impedance less than 100 ohm with series connection, and middle impedance minimum value of the present invention is greater than 200 ohm, therefore selection is simultaneously
Translocation tries the electrical parameter under circuit.
Further, the Tea Samples be tealeaves after rubbing in 27 DEG C of temperature, humidity > 90% artificial gas tank in send out
Ferment 6h, in the sample that 0~6h different fermentations time sampling obtains.
Further, the electrical characteristic parameter in the S2 includes parallel equivalent capacitor, complex impedance, resistance, reactance, fissipation factor
With phase loss angle.
Tea leaf fermentation sample can be considered the interior media of capacitor, when electric current passes through black tea sample between electrode plate, i.e. structure
It at capacitor equivalent circuit, is handled by the algebra to detection signal, terminal interface can receive complex impedance Z, parallel equivalent electricity
Hold the electrical characteristic parameters values such as Cp, reactance X, fissipation factor D and phase loss angle θ.
Further, the test condition of electrical characteristic parameter is test voltage 1V, 0.05~200kHz of test frequency in the S2.
Further, the index of quality in the S3 includes sensory evaluation scores, theaflavin, thearubigin and theabrownin, and the tea is yellow
Element, thearubigin and theabrownin are measured using high performance liquid chromatography.
Further, the calibration of fermentation quality grade is to evaluate total score based on expert sensory's scoring comment calculating in the S3, is examined
Sample of the total score greater than 85 is commented to be assessed as proper fermentation, the sample before proper fermentation sample time node is slight fermentation, it
Sample afterwards is excessive fermentation.
Further, the standardization pretreatment mainly uses multiplicative scatter correction, deviation standardization, Smooth, S/G2st
Electrical characteristic parameter initial data is pre-processed with Zscore method.
Further, the characteristic frequency composite index analysis method based on related coefficient and principal component in the S4 is selected preferably
Characteristic frequency is specially established the correlation matrix of electrical parameter Yu each fermentation quality index, is led to each group matrix data
Constituent analysis obtains correlation index, is formed by array to the correlation index of each index of quality at different frequencies and carries out PCA points
The comprehensive index of correlation is calculated in analysis, and the corresponding frequency of the comprehensive index of correlation of maximum is preferred feature frequency.
Further, filter out in the S4 be suitable for the ferment preferred feature frequency that moderately differentiates is 0.2kHz.0.2kHz's
Comprehensive correlation coefficient value is up to 0.274.
Further, the extreme learning machine pattern discrimination is programmed in Matlab software, using ELM sorting algorithm, choosing
The activation primitive for being ELM with Sigmoid function ferments to three classes suitable using the number of principal components evidence of the electrical characteristic parameter extracted
The black tea sample of degree carries out discriminant classification.
Beneficial effects of the present invention:
(1) present invention specifies the changing rule of electrical characteristic parameter during the fermentation under each detection frequency.The result shows that
Electrical impedance, reactance, impedance angle and fissipation factor gradually increase in fermentation, and capacitor is gradually reduced with the extension of fermentation period, say
Hinder the substance of charge transfer more and more in bright fermentation process.
(2) it is special to specify that 0.2kHz can be used as electricity in fermentation of black tea by the comprehensive correlation index method of principal component by the present invention
The characteristic frequency of property parameter detecting.Variable optimization method based on MCUVE-CARS specifies the survey stable with each index of quality
Examination frequency is low-frequency range, and most related electrical parameters are D and X.
(3) present invention using electrical characteristic parameter combination ELM to the differentiation of fermentation of black tea quality appropriateness the result shows that, ELM mould
Type estimated performance is more satisfactory, when number of principal components is 3, when node in hidden layer is 20, and the differentiation of model calibration set and forecast set
Rate reaches 100%, shows to may be implemented using electrical characteristic parameter combination ELM discrimination model to the pre- of fermentation quality appropriateness grade
It surveys and differentiates.
(4) electrical characteristics detection technique of the invention has stable, quick, sensitive, at low cost as a kind of mature technology
Advantage, has important practical significance and application prospect in the on-line checking of fermentation of black tea appropriateness.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the detection method of the fermentation of black tea appropriateness based on electrical characteristic parameter of the present invention；
Fig. 2 is electrical characteristics test system in a kind of detection method of the fermentation of black tea appropriateness based on electrical characteristic parameter of the present invention
Structural schematic diagram；
Wherein, host 1, bridge test instrument 2, test electrode 3, sampling box 4, bottom plate 5, motor 61, shaft 62, moving tooth are run
63；
Fig. 3 is influence curve figure of the test frequency within the scope of 0.05kHz~200KHz to fermentation of black tea sample electrical parameter；
Fig. 4 is the procedure chart that MCUVE-CARS screens feature electrical parameter relevant to sensory evaluation scores；
Fig. 5 is the three-dimensional shot chart of three PCA principal components under 0.2kHz and preferred feature electrical parameter；
Fig. 6 is differentiation result of the ELM model to fermentation of black tea quality.
Specific embodiment
Below with reference to the drawings and specific embodiments, the present invention is described in detail:
As shown in Figure 1, a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter of the invention, by different hairs
The tealeaves of ferment degree is respectively placed in the measurement that electrical characteristic parameter is carried out in electrical characteristics test system, while detecting the index of quality, into
The calibration of row grade carries out Screening Treatment to electrical characteristic parameter, so that prediction black tea dynamic fermentation appropriateness model is established, for realizing
The prediction for appropriate grade of fermenting is differentiated, comprising the following steps:
S1. the building of electrical characteristics test system, electrical characteristics test system include bridge test instrument 2, test electrode 3, sampling
Box 4, operation host 1 and acquisition software, acquisition software are mainly used to acquire data, are located in operation host 1.Bridge test instrument 2
Data exchange is carried out by R232 serial ports and operation host 1, and two test electrodes 3 are connected by twisted-pair shielded wire.
The Tea Samples of different fermentations time are separately added by disperser and are taken by the S2. measurement of sample electrical characteristic parameter
In sample box 4, and test electrode 3 is flooded, respectively at measuring electrical characteristic parameter under different frequency.
S3. fermentation quality detection and grade calibration, detect the index of quality of different fermentations time Tea Samples, and to fermentation
Quality carries out grade calibration.
S4. data screening processing and Model checking, are standardized pretreatment to electrical characteristic parameter, using based on phase relation
Several and principal component characteristic frequency composite index analysis method selects the preferred feature frequency that suitable fermentation quality differentiates, using nothing
Information variable null method-competitiveness adaptive weighting sampling method, which is combined, filters out preferred feature electrical characteristic parameter, to preferred feature
Each electrical characteristic parameter and preferred feature electrical characteristic parameter under frequency carry out PCA analysis respectively, using optimal principal component as input
Operating limit learning machine pattern discrimination is measured, to establish the dynamic fermentation appropriateness detection model of black tea.
S5. the quick detection of black tea dynamic fermentation appropriateness is connected to computer client, real-time Transmission fermentation by data line
The electrical characteristic parameter data of sample are analyzed in conjunction with the fermentation appropriateness detection model that acquisition software is written at software interface end in real time
The fermentation appropriateness grade of fermentation sample, realizes the qualitative quick detection of black tea dynamic fermentation appropriateness.
Detection of the specific embodiment to a kind of fermentation of black tea appropriateness based on electrical characteristic parameter of the invention will be passed through below
Method is described in detail, the detection method of fermentation of black tea appropriateness specific steps are as follows:
Step 1, the building of electrical characteristics test system
As shown in Fig. 2, the electrical characteristics test system of the present embodiment include bridge test instrument 2, test electrode 3, sampling box 4,
Run host 1 and acquisition software.The test frequency range of bridge test instrument 2 is 50Hz~200kHz, selects test circuit in parallel
Under electrical parameter, bridge test instrument 2 by R232 serial ports and operation host 1 carry out data exchange, and by twisted-pair shielded wire company
Connect two test electrodes 3.Test electrode 3 is red copper parallel plate electrode plate, and the area of electrode plate is 20cm2, grow and wide
Respectively 5cm, 4cm.5 side of bottom plate of sampling box 4 and side plate be hinged, the corresponding other side detachably connects with corresponding side plate
It connects, such structure rotate bottom plate 5 can around side, and the sample through detecting can take out from sampling box bottom, install on sampling box 4
There is disperser, disperser includes motor 61, shaft 62 and the moving tooth 63 being fastened around in shaft 62, and shaft 62 and motor 61 pass
Dynamic connection, the rotation of motor 61 drive shaft 62 to rotate.The present embodiment has customized terminal acquisition system and interface, realizes test data
Automatically record.
Step 2, the measurement of sample electrical characteristic parameter
One leaf of a bud of picking Fuding great Bai kind is used to ferment to prepare black tea, and the tealeaves of picking is spread naturally in time to water
When point content about 60%, using 40 type rolling machines, rubbed according to sky, after gently pressure, middle pressure and each alternation method of weight are rubbed,
Temperature is 27 DEG C, ferment 6h in growth cabinet of the fermentation humidity greater than 90%.
It will be scattered naturally, be added in sampling box 4, until Tea Samples flood test after disperser of the Tea Samples by rotation
Electrode 3, measure 0.05~200kHz frequency range in 0.05kHz, 0.06kHz, 0.08kHz, 0.1kHz, 0.2kHz,
0.3kHz、0.4kHz、0.5kHz、0.6kHz、0.8kHz、1kHz、2kHz、3kHz、4kHz、6kHz、8kHz、10kHz、50kHz、
100kHz, 150kHz and 200kHz27 Frequency points, the sine wave that voltage is 1 volt, measurement Tea Samples ferment 0~6h time
The electrical characteristic parameter of sample in range, including parallel equivalent capacitor Cp, complex impedance Z, resistance R, reactance X, fissipation factor D and phase
Loss angle θ.Being placed in sampling box 4 every 0.5h sampling measures primary, and when measurement, each sample was repeated 6 times, then by each parameter
Measured value of the mean value of value as each electrical parameter, the result of measurement are as shown in Figure 3.
Wherein, Fig. 3-A is influence curve figure of the frequency to complex impedance, and Fig. 3-B is influence curve figure of the frequency to resistance, figure
3-C is influence curve figure of the frequency to impedance angle, and Fig. 3-D is influence curve figure of the frequency to reactance, and Fig. 3-E is frequency to capacitor
Influence curve figure, Fig. 3-F is the influence curve figure of the frequency versus path loss factor, and Fig. 3-G is test frequency to resistance-reactance shadow
Ring curve graph.
Show that detecting frequency has apparent influence to fermentation of black tea sample electrical parameter, ferments by the data analysis result of Fig. 3
Time has larger impact to the low frequency characteristic of electrical parameter.Electrical impedance, reactance, impedance angle and fissipation factor be gradually in fermentation
Increase, capacitor is gradually reduced with the extension of fermentation period, illustrates to hinder the substance of charge transfer more and more in fermentation process.
Step 3, fermentation quality detection and grade calibration
During fermentation of black tea while 0.5h carries out electrical characteristic parameter measurement, take 100g with fermentation time node
Fermented sample in liquid nitrogen, be repeated 3 times, after freeze-dried processing, be placed in -20 DEG C of refrigerator storage to detecting.According to
National Standard Method " measurement-high performance liquid chromatography of theaflavin in GB/T 30483-2013 tealeaves " measures dark brown cellulose content, i.e. tea is yellow
The content of element, thearubigin, theabrownin and catechin.In addition take the fermented sample of each same fermentation time node in 120 DEG C of gross fire,
After 90 DEG C of final firings are dried, form is evaluated according to GB/T 23776-2009 " tealeaves organoleptic evaluation method " and password, by
Expert carries out sensory evaluation to fermented tea sample, evaluates the organoleptic quality of the produced black tea under each fermentation time node, and count
Total score is evaluated in calculation.
Expert sensory evaluation is the overall merit to tealeaves color and shape, and different fermentations journey can be embodied from flavour
Sample biochemical composition is spent to the intrinsic stimuli of sense organ, and can be from characterization is fermented on the external performances such as sample soup look, shape, tea residue
Externality of the biochemical products to quality.Total score is evaluated based on expert sensory's scoring comment calculating and carries out ranking, is evaluated total
The sample greater than 85 is divided to be assessed as proper fermentation, the sample before proper fermentation sample time node is slight fermentation, later
Sample is excessive fermentation.The results are shown in Table 1 for ranking.
The sensory evaluation of 1 fermentation of black tea process sample of table
Step 4, data screening processing and model foundation
All data processings are completed under Matlab 2016a and Microsoft Windows7 platform.Due to each test
The dimension, magnitude of each electrical parameter, susceptibility are different under frequency, therefore need first to make standardization pretreatment to each electrical parameter data, go
Except the influence of dimension.
1. being standardized pretreatment to electrical parameter initial data
Multiplicative scatter correction MSC, deviation standardization Min-Max, Smooth, S/G2 is respectively adopted in the present embodimentstWith
Zscore method pre-processes electrical characteristic parameter initial data, is then based on processing data and establishes PLS model, each model
It can be as shown in table 2:
The different preprocess method of table 2 influences the performance of PLS sense organ model
The result shows that Zscore is best electrical characteristic parameter preprocess method, Rp value is mentioned from the 0.172 of initial data
Up to 0.842, and it is apparently higher than other preprocess methods；RMSEP is 2.194 and Bias is 0.232, also significantly lower than other pre-
Processing method.In addition, the difference of the RMSECV and RMSEP of Zscore model are 1.157, it is minimum in all preprocess methods,
Model is set to have preferable Generalization Capability after showing Zscore standardization.Therefore, in actual operation, it is possible to use only
Zscore method is standardized pretreatment to electrical characteristic parameter initial data.
2. screening the preferred feature frequency that suitable fermentation quality differentiates
After being standardized pretreatment to electrical characteristic parameter initial data, using the feature based on related coefficient and principal component
Frequency synthesis index analysis method filters out the preferred feature frequency that suitable fermentation quality differentiates, specially establishes electrical parameter and each
The correlation matrix of fermentation quality index carries out principal component analysis to each group matrix data, and the results are shown in Table 3.
The principal component analysis of electrical parameter and index of quality related coefficient under 3 different frequency of table
Using characteristic value corresponding to each principal component as flexible strategy, with preceding 3 principal component scores (score-1, score-2,
Score-3 the comprehensive Principal component of correlation can be obtained by) being multiplied, referred to as correlation index CI, its calculation formula is: CI=(LATENT
(1,:)*score(:,1)+LATENT(2,:)*score(:,2)+LATENT(3,:)*score(:,3))/(LATENT(1,:)+
LATENT (2 :)+LATENT (3 :)), score-principal component scores matrix in formula, LATENT-eigenvectors matrix.Thus
The CI of each frequency calculated is shown in Table 4.By the synthesis correlation of table 4 available each index of quality and 6 electrical parameters, each quality
The CI value of index, increasing CI with frequency is totally in the changing rule for first increasing and dropping afterwards.
TFs content is 0.474 in the CI absolute value of 0.2kHz, is ranked the first；CI absolute value of the TRs activity in 0.1kHz be
0.429, it ranks the first；TBs is 0.432 in the CI absolute value of 0.5kHz, is ranked the first；CI of the sensory evaluation scores in 0.2kHz is absolute
Value is 0.274, is ranked the first；Although each index of quality is corresponding with the best Frequency point of comprehensive correlation, its optimal frequency is simultaneously
Do not unify.Therefore array is formed by the CI value of each index of quality in table 4 at different frequencies and carries out secondary PCA analysis, and
It calculates it and integrates index of correlation CCI, the CCI of each frequency and overall ranking are as shown in most right two column of table 4.
Electrical parameter and the comprehensive index of correlation CCI of the index of quality under the different test frequencies of table 4
As can be seen from Table 4, CCI value is greater than Frequency point totally 7 of 0, wherein and the CCI value of 0.2kHz is up to 0.274,
Therefore 0.2kHz can be used as the characteristic frequency that electrical characteristic parameter is tested in fermentation of black tea.
3. filtering out preferred feature electrical characteristic parameter
Variable using Monte Carlo without information variable null method MCUVE and competitive adaptive weighting sampling method CARS is excellent
Choosing method carries out 162 (27 × 6) electrical characteristic parameters under 27 frequencies preferably, to reject useless characteristic variable.The side MCUVE
Method is by calculating the index of stability RI value of each variable come the importance of variable each in evaluation model, according to RI value size to change
Amount is ranked up, and establishes new variables collection, and then 1 variable that gradually adds up establishes PLS model respectively, most with forecast set
Evaluation index of the small RMSEP value as variable encumbrance, MCUVE feature electrical parameter selection result are as shown in table 5:
Table 5MCUVE feature electrical parameter selection result
It is above-mentioned statistics indicate that, the RI of sensory evaluation scores selection is concentrated mainly on 0.06~0.4kHz of low-frequency range greater than 4 frequency,
The high variable of stability is the fissipation factor D and reactance X of electrical parameter, and wherein the RI value of D variable is up under 0.4kHz frequency
4.53.Frequency of the RI greater than 2 of TFs selection is concentrated mainly on middle 0.1~5kHz of low-frequency range, and the high variable of stability is electrical parameter
Fissipation factor D and reactance X, wherein the RI value of X variable is up to 3.17 under 1kHz frequency.The index of stability RI of TRs selection is big
Frequency in 2.5 is concentrated mainly on middle 0.1~5kHz of low-frequency range, and the high variable of stability is the fissipation factor D and electricity of electrical parameter
Anti- X, wherein the RI value of X variable is up to 3.47 under 0.6kHz frequency.The index of stability RI of TBs selection is greater than 3.7 frequency
It is concentrated mainly on 0.05~0.1kHz of low-frequency range, the high variable of stability is the fissipation factor D and reactance X of electrical parameter, wherein
The RI value of X variable is up to 4.51 under 0.1kHz frequency.Comprehensive analysis is low frequency with the stable test frequency of each index of quality
Section, maximally related feature electrical parameter is D and X.
The electrical parameter that MCUVE has been selected is advanced optimized using CARS, sets CARS algorithm continuous sampling number as 50
With 10 times of validation-cross, chooses variable subset corresponding to RMSECV minimum value and be characterized variable, it is the smallest to obtain synteny
Validity feature variable.As shown in figure 4, by taking the MCUVE-CARS feature electrical parameter screening process of sensory evaluation scores prediction model as an example,
When sampling number is 8 times, RMSECV reaches minimum value 1.235, and corresponding feature electrical parameter is 10.Similarly obtain
The feature electrical parameter of TFs, TRs, TBs are respectively 8,5,6, and the results are shown in Table 6:
Table 6MCUVE-CARS feature electrical parameter selection result
4. principal component analysis
By under preferred 0.2kHz 6 electrical parameters and MCUVE-CARS method screened from full rate preferred feature electricity ginseng
Number, carries out PCA analysis respectively, and the three-dimensional load diagram of preceding 3 principal components is as shown in Figure 5.Fig. 5-A is 6 under 0.2kHz frequency
Electrical characteristic parameter principal component load diagram, Fig. 5-B are characterized electrical characteristic parameter principal component load diagram.As shown in Figure 5, each sample is pressed
Fermentation time difference is gathered in different area of space, and there is also certain intersections between each area of space, it is still necessary in conjunction with mould
Formula method of discrimination makees further differentiation.
5. extreme learning machine pattern discrimination
Using optimal principal component as input quantity operating limit learning machine ELM pattern discrimination, the dynamic of quick predict black tea is sent out
Ferment degree.It is programmed in Matlab software, using ELM sorting algorithm, selecting Sigmoid function is the activation primitive of ELM, is utilized
The number of principal components evidence of the electrical characteristic parameter extracted carries out discriminant classification to the black tea sample of three classes fermentation appropriateness.Because of hidden layer
Number N and principal component make N and PCs in the range of selection because estimated performance of the subnumber PCs to discrimination model is affected
Further parameter collaboration optimizing processing.Choose respectively 10 Φ values (5~50, step-length 5) and 10 PCs numbers (1~10, walk
It is a length of 1), determine that preferred parameter, Fig. 6 show different principal components because subnumber is to ELM mould with the differentiation accuracy of training pattern
The differentiation result of type calibration set.When it is 20 that PCs, which is 3, N, the differentiation rate of model calibration set and forecast set reaches 100%, mould
Type better performances.Table 7 shows ELM model to the differentiation of different fermentations quality appropriateness grade black tea as a result, knowing that electrical characteristics are joined
Number combines ELM discrimination model that the differentiation of the prediction to fermentation quality appropriateness grade may be implemented.
Differentiation result of the table 7ELM model to different fermentations quality appropriateness grade black tea
Step 5, the quick detection of black tea dynamic fermentation appropriateness
Computer client, the electrical characteristic parameter data of real-time Transmission fermented sample, in conjunction with acquisition are connected to by data line
The fermentation appropriateness detection model of software write-in is analyzed the fermentation appropriateness grade of fermentation sample at software interface end in real time, is realized red
The qualitative quick detection of tea dynamic fermentation appropriateness.
As can be seen from the above embodiments, the present invention has using the method for electrical characteristics technology detection fermentation of black tea quality appropriateness
There have the advantages that be rapid, efficient, convenient, and probe is inserted into fermentation of black tea sample, to realize the reality of fermentation of black tea appropriateness
When online and on-site test.
The above examples are only used to illustrate the technical scheme of the present invention and are not limiting, although referring to preferred embodiment to this hair
It is bright to be described in detail, those skilled in the art should understand that, it can modify to technical solution of the present invention
Or equivalent replacement should all cover without departing from the objective and range of technical solution of the present invention in claim of the invention
In range.Technology not described in detail in the present invention, shape, construction portion are well-known technique.
Claims (9)
1. a kind of detection method of the fermentation of black tea appropriateness based on electrical characteristic parameter, which is characterized in that by Various Fermenting Degree
Tealeaves is respectively placed in the measurement that electrical characteristic parameter is carried out in electrical characteristics test system, while detecting the index of quality, carries out grade mark
It is fixed, Screening Treatment is carried out to electrical characteristic parameter, so that prediction black tea dynamic fermentation appropriateness model is established, it is suitable to fermentation for realizing
The prediction for spending grade differentiates, comprising the following steps:
S1. the building of electrical characteristics test system, the electrical characteristics test system include bridge test instrument, test electrode, sampling box,
Host and acquisition software are run, disperser is installed on the sampling box, the bridge test instrument passes through R232 serial ports and operation
Host carries out data exchange, and connects two test electrodes by twisted-pair shielded wire；
The Tea Samples of different fermentations time are spilled by disperser by the S2. measurement of sample electrical characteristic parameter naturally respectively
Enter in sampling box, and Tea Samples is made to flood test electrode, respectively at measuring electrical characteristic parameter under different frequency；
S3. fermentation quality detection and grade calibration, detect the index of quality of different fermentations time Tea Samples, and to fermentation quality
Carry out grade calibration；
S4. data screening processing and Model checking, pretreatment is standardized to electrical characteristic parameter, using based on related coefficient with
The characteristic frequency composite index analysis method of principal component selects the preferred feature frequency that suitable fermentation quality differentiates, using no information
Variable elimination method-competitiveness adaptive weighting sampling method, which is combined, filters out preferred feature electrical characteristic parameter, to preferred feature frequency
Under each electrical characteristic parameter and preferred feature electrical characteristic parameter carry out PCA analysis respectively, make using optimal principal component as input quantity
With extreme learning machine pattern discrimination, to establish the dynamic fermentation appropriateness detection model of black tea；
S5. the quick detection of black tea dynamic fermentation appropriateness is connected to computer client, real-time Transmission fermented sample by data line
Electrical characteristic parameter data, in conjunction with acquisition software be written fermentation appropriateness detection model, analyze fermentation in real time at software interface end
The fermentation appropriateness grade of sample realizes the qualitative quick detection of black tea dynamic fermentation appropriateness.
2. a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter according to claim 1, feature exist
In the test frequency range of the bridge test instrument is 50Hz~200kHz, and the test electrode is copper parallel plate electrode
Plate, the area of electrode plate are 20cm2, the disperser includes motor, shaft and the moving tooth being fastened around in shaft, shaft with
The revolving speed of motor drive connection, the shaft is greater than 1000r/min.
3. a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter according to claim 1, feature exist
In the electrical characteristic parameter in the S2 includes parallel equivalent capacitor, complex impedance, resistance, reactance, fissipation factor and phase loss
Angle.
4. a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter according to claim 3, feature exist
In the test condition of electrical characteristic parameter is test voltage 1V, 0.05~200kHz of test frequency in the S2.
5. a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter according to claim 1, feature exist
In the index of quality in the S3 includes sensory evaluation scores, theaflavin, thearubigin and theabrownin, the theaflavin, thearubigin and tea
Brown element is measured using high performance liquid chromatography.
6. a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter according to claim 5, feature exist
In the calibration of fermentation quality grade is to evaluate total score based on expert sensory's scoring comment calculating in the S3, evaluates total score greater than 85
Sample be assessed as proper fermentation, the sample before proper fermentation sample time node is slight fermentation, and sample later was
Degree fermentation.
7. a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter according to claim 1, feature exist
In the characteristic frequency composite index analysis method based on related coefficient and principal component in the S4 selects preferred feature frequency, tool
Body is the correlation matrix for establishing electrical parameter Yu each fermentation quality index, carries out principal component analysis to each group matrix data, obtains
To correlation index, array is formed by the correlation index of each index of quality at different frequencies and carries out PCA analysis, is calculated
The comprehensive index of correlation, the corresponding frequency of the comprehensive index of correlation of maximum is preferred feature frequency.
8. a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter according to claim 7, feature exist
In filtering out in the S4 be suitable for the ferment preferred feature frequency that moderately differentiates is 0.2kHz.
9. a kind of detection method of fermentation of black tea appropriateness based on electrical characteristic parameter according to claim 8, feature exist
In the extreme learning machine pattern discrimination is programmed in Matlab software, using ELM sorting algorithm, selects Sigmoid function
For the activation primitive of ELM, using the number of principal components evidence of the electrical characteristic parameter extracted, to the black tea sample of three classes fermentation appropriateness into
Row discriminant classification.
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