CN110907369A - Wuyi rock tea production place identification method fusing different detection method characteristic variables - Google Patents
Wuyi rock tea production place identification method fusing different detection method characteristic variables Download PDFInfo
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Abstract
The invention discloses a Wuyi rock tea production area identification method fusing different detection method characteristic variables, which comprises the following steps: a. collecting rock tea samples of different producing areas; b. measuring near-infrared characteristic spectrum data of rock tea samples in different producing areas; c. measuring mass spectrum data of four stable isotopes of hydrogen, oxygen, nitrogen and carbon of rock tea samples in different producing areas; d. measuring the trace element data of cesium, copper, calcium and rubidium of rock tea samples of different producing areas; e. determining amino acid data of rock tea samples of different producing areas; f. establishing different producing area rock tea identification databases by combining near infrared, stable isotope, trace element and amino acid data; g. taking a sample of an unknown production place to be detected, determining data in various methods according to the steps B, C, D and E, substituting the determined data into the PLSDA model, and if the prediction result is less than 0, judging that the sample to be detected is a sample outside the production place of the Wuyi rock tea; and if the prediction result is greater than 0, judging that the sample to be detected is a sample in the Wuyi rock tea producing area.
Description
Technical Field
The invention belongs to the technical field of identification of authenticity of geographic marking products, and particularly relates to a Wuyi rock tea production place identification method fusing different detection method characteristic variables. .
Background
At present, finished tea production place identification and identification researches are carried out at home and abroad, instrument detection is combined with a chemometrics analysis method to be the most important production place identification method, and the instrument detection method mainly comprises near infrared spectrum, isotope mass spectrum, liquid chromatogram, sensors and the like; common metrology methods include partial least squares, principal component analysis, artificial neural networks, support vector machines, and the like.
A plurality of methods for identifying geographic marking products exist at home and abroad, but a plurality of researches have defects, such as insufficient sampling, small sample quantity and incapability of ensuring the accuracy and the representativeness of the samples; the sample space selection span is large, and is often selected from different countries and different regions, so that the sample space selection span is very different; in addition, even different varieties of samples are selected for comparison, and the difference among different varieties is large, so that the identification method has little reference significance for distinguishing the production places of geographic marking products in a small range; the modeling method is carried out by combining single detection data with a metrology method, the single detection data cannot represent all origin tracing information, so that the origin identification rate is low, and the innovation and the breakthrough of the geographic marking product protection technology are seriously influenced. In order to solve the above problems, it is necessary to establish a method for identifying the production area of wuyi rock tea by combining a plurality of detection technologies, namely a method for identifying the production area of wuyi rock tea by combining near infrared, stable isotopes, trace elements and amino acid data.
When the tea leaves are detected by using near infrared, a human body needs to be avoided, and the tea leaves are irradiated by the near infrared for a long time to influence the health of the human body, particularly the skin; during near infrared spectrum detection, if a good detection environment is provided, the accuracy of a detection result can be ensured, but the environment cannot be adjusted in the existing near infrared detection, and the detection structure is influenced to a certain extent.
Disclosure of Invention
The invention provides a Wuyi rock tea production area identification method for improving the accuracy of detection results by combining multiple detection methods in order to overcome the defects of the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme: a Wuyi rock tea production area identification method for improving detection result accuracy by combining multiple detection methods comprises the following steps:
a. collecting rock tea samples of different producing areas: the number of samples outside the Wuyi rock tea production area is more than 100 parts, and the proportion of the samples in the range of 50 kilometers around the production area is more than 50 percent; the number of samples in the Wuyi rock tea production area is 2-3 times of that of samples outside the production area, the sampling range covers all production enterprises in the main production area, and each enterprise should have no less than 3 samples;
b. determining near infrared characteristic spectrum data of rock tea samples of different producing areas: near infrared detection parameters: 64 scans, the characteristic spectrum band is the average value of 64 scans, and the scanning range is 12000-4000cm-1The data points are spaced apart by 1.928 cm-1During collection, the rock tea is placed in a detection chamber, the room temperature is controlled at 25 ℃, the humidity is kept stable, and the spectrum of each sample is collected for 1 time;
c. measuring mass spectrum data of four stable isotopes of hydrogen, oxygen, nitrogen and carbon of rock tea samples of different producing areas: delta13C、δ15N、δ18O、δ2H、δ86Determining stable isotope content of Sr, repeatedly analyzing each sample for at least 3 times, and taking average value asA final result;
d. and (3) determining the cesium, copper, calcium and rubidium trace element data of rock tea samples of different producing areas: and measuring the contents of Ca, Mg and Mn elements by using an atomic absorption spectrometer, and measuring the contents of Ti, Cr, Co, Ni, Cu, Zn, Rb, Cd, Cs, Ba and Sr elements by using an inductively coupled plasma mass spectrum. Performing microwave digestion on a dry tea sample, observing whether a digestion solution is clear or not after digestion is finished, repeating the pressure digestion step if the digestion solution is turbid, and determining the volume after the volume is fixed by using the instrument if the digestion solution is completely clear;
e. determining amino acid data of rock tea samples of different producing areas: detecting 27 amino acids in rock tea samples of different producing areas by using an HPLC method, measuring twice in parallel, and taking an average value;
f. establishing different producing area rock tea identification databases by combining near infrared, stable isotope, trace element and amino acid data;
g. taking a sample of an unknown production place to be detected, determining near-infrared characteristic spectrum data, stable isotope mass spectrum data, trace element data and amino acid data according to the steps B, C, D and E, substituting the determined data into the PLSDA model, and if the prediction result is less than 0, judging that the sample to be detected is a sample outside the production place of the Wuyi rock tea; if the prediction result is greater than 0, judging that the sample to be detected is a sample in the Wuyi rock tea producing area;
a first opening is formed in the side wall of the detection chamber in the step b, a first movable chamber is arranged at the top of the first opening, a first baffle matched with the first opening is arranged in the first movable chamber, near infrared spectrum detection equipment is arranged in the detection chamber, a first movable groove is formed in the bottom of the detection chamber, an installation frame is arranged in the first movable groove, a driving motor used for driving the installation frame to horizontally move is arranged on the inner wall of the first movable groove, an installation plate is arranged at the top of the installation frame, a groove is formed in the installation plate, and a material carrying box is arranged in the groove; the side wall of the detection chamber is provided with a heating block, the top of the detection chamber is provided with a temperature sensor and a humidity sensor, the top of the detection chamber is provided with a first water pipe in a penetrating way, the bottom of the first water pipe is provided with an atomizing nozzle, the inner wall of the detection chamber is provided with a first connecting block, the first connecting block is internally provided with a first cavity, and a drying agent is arranged in the first cavity; when near-infrared detection is performed on tea, the tea is placed on the material carrying box, then the material carrying box is placed into the groove, the first baffle moves upwards, the first opening is in an open state, the driving motor drives the installation frame to move in the first movable groove, the driving material carrying box is driven to enter the detection chamber, the first baffle moves downwards after the material carrying box completely enters the detection chamber, the first opening is sealed, clear water enters the first water conveying pipe, water drops are sprayed into the detection chamber through the atomizing nozzle, the heating block heats indoor air, the temperature sensor and the humidity sensor detect the temperature and the humidity in the detection chamber, after the temperature and the humidity are in proper conditions, near-infrared spectrum detection equipment detects rock tea and collects sample spectra.
The sample is placed in the detection chamber for detection in a mode of placing the sample on the material carrying box, so that the sample is detected in a closed space, the influence of near infrared radiation on a human body on the health of the human body is avoided, and the safety of sample detection is improved; by adjusting the environment of the closed space, a proper environment is provided for sample detection, the influence of the outside on the sample detection is avoided, the sample detection precision is improved, and the identification reliability is ensured; under the mutual cooperation of the driving motor and the first baffle, the material carrying box is automatically sent into the detection chamber, so that the detection operation of the sample is more convenient, and the detection efficiency of the sample is improved; the temperature during detection is adjusted through the heating block and the temperature sensor, and the humidity is adjusted through the first water delivery pipe, the drying agent and the humidity sensor, so that a required environment is formed in the detection chamber, and a proper environment is provided for the detection of the sample; when the humidity in the detection chamber is too low, water flow enters the detection chamber through the first water delivery pipe, and the water flow is diffused in the detection chamber in a water mist form under the action of the atomizing spray head, so that the humidity in the detection chamber is improved; when the humidity in the detection chamber is too high, the moisture in the detection chamber is absorbed under the action of the drying agent, the humidity in the detection chamber is reduced, and the sample is prevented from being affected by dampness in the detection process.
The detection method in the step c comprises the following steps: training and predicting Wuyi rock tea stable isotope data through SVM-RFE (support vector machine regression feature elimination), randomly repeating for 100 times, sequencing model features of all variables, and screening isotope feature variables of the rock tea origin place, wherein the sequencing sequence is hydrogen, oxygen, nitrogen, carbon and strontium; and the sensitivity, resolution and recognition rate of the model are calculated by utilizing the prediction set, the average result is repeatedly calculated for 100 times, and the recognition rate of the model consisting of four data of hydrogen, oxygen, nitrogen and carbon is the highest and reaches 93.93 percent, so that the modeling only needs to select the four data of hydrogen, oxygen, nitrogen and carbon, and the detection on the contents of other stable isotopes such as strontium is not needed.
The determination method in the step d comprises the following steps: training and predicting the trace element data by an SVM-RFE method, repeating the training and predicting randomly for 100 times, sequencing the model characteristics of all variables, screening out the trace element characteristic variables of the original producing area of the rock tea, and calculating the model dimension increasing precision after each one-dimensional variable is accumulated by a prediction set to obtain the sequencing sequence of the characteristics of cesium, copper, calcium, rubidium, strontium and barium; and then combining the characteristic variables step by step according to a natural sequence, calculating the sensitivity, resolution and recognition rate of the model by using a prediction set, wherein the model consisting of four trace elements of cesium, copper, calcium and rubidium has the highest recognition rate, so that the information among the four trace elements has complementarity, and only the four trace elements of cesium, copper, calcium and rubidium which are modeled need to be selected for detection, and other trace elements do not need to be detected.
The detection method in the step e comprises the following steps: training and predicting amino acid component data of Wuyi rock tea by an SVM-RFE method, randomly repeating for 100 times, sequencing model characteristics of all variables, screening out characteristic variables of tea origin places, calculating model dimension increasing precision after each dimension variable is accumulated by a prediction set, and determining the sequencing sequence of asparagine, proline, tryptophan, phosphoethanolamine, urea and valine; and then combining the characteristic variables step by step according to a natural sequence, calculating the sensitivity dimension-increasing precision, the resolution dimension-increasing precision and the recognition rate dimension-increasing precision of the model by utilizing a prediction set, wherein the recognition rate of the model consisting of the four amino acids of asparagine, proline, tryptophan and phosphoethanolamine is the highest, so that the information among the four amino acids has complementarity, and only the four amino acids of asparagine, proline, tryptophan and phosphoethanolamine which are modeled need to be selected for detection.
The segmentation procedure in the step e is respectively as follows: [ model1, test1] = Duplex (data1, a1) and [ model2, test2] = Duplex (data2, a2), yielding model1, test1, model2, test 2.
A first movable cavity is arranged at the bottom of the groove, a push block is arranged in the first movable cavity, a sliding groove is formed in the inner wall of the first movable cavity, and a sliding block matched with the sliding groove is arranged on the side wall of the push block; the bottom of the push block is provided with a push plate, the bottom of the push plate is provided with a connecting pipe, the bottom of the first movable cavity is provided with an air bag, the connecting pipe penetrates through the air bag, one side of the air bag is provided with a stop block, and the other side of the air bag is provided with the push block; a connecting groove is formed in the inner wall of the groove, and a sucker matched with the material loading box is arranged at the bottom of the connecting groove; after a sample is placed in the material carrying box, the material carrying box is placed in the groove, the material carrying box is pressed downwards, the bottom surface of the material carrying box is in contact with the sucker, the sucker is deformed under the action of pressure, the material carrying box is fixed on the sucker, the mounting frame drives the material carrying box to enter the detection chamber, the push block moves towards the air bag, the air bag is deformed after being extruded, airflow in the air bag is pushed into the connecting pipe, the connecting pipe is pushed to move upwards by air pressure, the connecting pipe drives the push plate to move upwards, the push plate pushes the push block to move upwards, the push block pushes the sample at the bottom of the material carrying box upwards, and then near infrared spectrum detection equipment works to detect the sample to finish spectrum detection of the sample; under the mutual matching of the push block and the stop block, the air bag in the first movable cavity is extruded, the air bag deforms and then enters air in the air bag into the connecting pipe, so that the push plate is pushed to move upwards under the action of air pressure, the push plate pushes the material loading box to move upwards together, the side wall of the material loading box is prevented from being shielded by near infrared rays, samples in the material loading box are fully detected, and detection dead angles are prevented; under the mutual matching of the sliding groove and the sliding block, the movement stroke of the push block is limited, the push block is prevented from being separated from the first movable cavity, and the connecting effect of the push block and the first movable cavity is ensured; under the mutual cooperation of sucking disc and carrier box, promote carrier box and recess connection effect, under the mutual cooperation of sucking disc and ejector pad, make carrier box bottom up for the top surface move, will be in the sample propelling movement of carrier box bottom to carrier box top to do the detection processing to the sample.
A first driving wheel is arranged on an output shaft of the driving motor, a connecting shaft is rotatably connected to the inner wall of the first movable groove, a second driving wheel matched with the first driving wheel is arranged on the connecting shaft, driving teeth in transmission fit with the second driving wheel are arranged on the inner wall of the mounting frame, the first driving wheel is an incomplete gear, and the diameter of the first driving wheel is far larger than that of the second driving wheel; a through cavity is formed in the top of the first cavity, a second movable cavity is formed in the inner wall of the through cavity, a second baffle matched with the through cavity is arranged in the second movable cavity in a penetrating mode, a connecting spring is arranged on the side wall of the second baffle, and an electromagnet matched with the second baffle is arranged in the second movable cavity; when the material loading box is placed into the groove, the first baffle moves upwards to enable the first opening to be in an open state, the driving motor drives the first driving wheel to rotate, the first driving wheel rotates to drive the second driving wheel to rotate, the second driving wheel drives the mounting frame to move, and the mounting frame drives the material loading box to enter the detection chamber; when the humidity in the detection chamber is insufficient, clear water enters from the first water conveying pipe, enters the detection chamber through the atomizing nozzle, and increases the humidity in the detection chamber; when the internal humidity is too high during detection, the electromagnet is electrified to enable the second baffle to enter the second movable cavity, the second through cavity is in an open state, and water vapor enters the first cavity and contacts with the drying agent to absorb excessive water vapor so as to reduce the humidity in the detection chamber; under the arrangement of incomplete teeth of the first transmission teeth, the first transmission wheel can finish the back-and-forth movement of the mounting frame when rotating towards one direction, so that the mounting frame drives the material loading box to automatically enter and exit the detection chamber, and the use convenience of the detection chamber is improved; the rotating turns of the second driving wheel are increased through the arrangement of different tooth diameters of the first driving wheel and the second driving wheel, so that the mounting frame has enough displacement distance under the action of the second driving wheel to send the material loading box into the detection chamber; the opening and closing of the through cavity are controlled by the second baffle plate, when the humidity in the detection chamber is normal or too low, the through cavity is closed by the second baffle plate, and the contact between water vapor in the detection chamber and a drying agent is avoided; when the humidity in the detection chamber is too high, the electromagnet is electrified to suck the second baffle into the second movable cavity, the through cavity is opened to enable water vapor to be directly contacted with the drying agent, and the water vapor in the detection chamber is absorbed so as to adjust the humidity in the detection chamber.
The invention has the following advantages: based on a partial least square discrimination model, fusing near-infrared characteristic spectrum data, stable isotope data, trace element data and amino acid data of rock tea (including rock tea inside and outside geographical production places) of different production places together to establish an analysis model, and objectively and accurately determining the production places of the rock tea by using the model after extracting samples, wherein the recognition rate is the highest and can reach 100.0 percent and is higher than the discrimination result of single data PLSDA; the sample is placed in the detection chamber for detection in a mode of placing the sample on the material loading box, so that the sample is detected in a closed space, the influence of near infrared radiation on a human body on the health of the human body is avoided, and the safety of sample detection is improved; through the adjustment to the environment in the detection room, for the detection of sample provides good environment, promote sample detection precision, for data analysis provides accurate data support, increase the judgement rate of accuracy of rock tea place of production.
Drawings
FIG. 1 is a schematic view of the structure of the detection chamber of the present invention.
FIG. 2 is a first cross-sectional view of a detection chamber according to the present invention.
Fig. 3 is an enlarged view of a portion a in fig. 2.
Fig. 4 is an enlarged view of fig. 2 at B.
Fig. 5 is an enlarged view of fig. 2 at C.
Fig. 6 is an enlarged view of fig. 2 at D.
FIG. 7 is a schematic cross-sectional view of a second embodiment of the detection chamber of the present invention.
Fig. 8 is an enlarged view of fig. 7 at E.
Fig. 9 is an enlarged view of fig. 7 at F.
FIG. 10 is a third schematic sectional view of the detection chamber of the present invention.
Fig. 11 is an enlarged view at G in fig. 10.
FIG. 12 is a fourth schematic cross-sectional view of a detection chamber of the present invention.
Fig. 13 is an enlarged view of fig. 12 at H.
Detailed Description
A Wuyi rock tea production place identification method fusing different detection method characteristic variables comprises the following steps:
(A) collecting rock tea samples of different producing areas:
the number of samples outside the Wuyi rock tea production area is more than 100 parts, and the proportion of the samples in the range of 50 kilometers around the production area is more than 50 percent; the number of samples in the Wuyi rock tea production area is 2-3 times of that of samples outside the production area, the sampling range covers all production enterprises in the main production area, and each enterprise should have no less than 3 samples;
(B) determining near infrared characteristic spectrum data of rock tea samples of different producing areas:
near infrared detection parameters: 64 times of scanning, wherein the characteristic spectrum band is the average value of 64 times of scanning, the scanning range is 12000-4000cm < -1 >, the data point interval is 1.928 cm < -1 >, the room temperature is controlled at 25 ℃ during the collection, the humidity is kept stable, and the spectrum of each sample is collected for 1 time;
(C) measuring mass spectrum data of four stable isotopes of hydrogen, oxygen, nitrogen and carbon of rock tea samples of different producing areas:
δ13C、δ15N、δ18O、δ2H、δ86determining the content of stable isotopes such as Sr, repeatedly analyzing each sample for at least more than 3 times, and taking the average value as the final result;
training and predicting Wuyi rock tea stable isotope data through SVM-RFE (support vector machine regression feature elimination), randomly repeating for 100 times, sequencing model features of all variables, and screening isotope feature variables of the rock tea origin place, wherein the sequencing sequence is hydrogen, oxygen, nitrogen, carbon and strontium; the sensitivity, resolution and recognition rate of the model are calculated by utilizing the prediction set, the average result is repeatedly calculated for 100 times, and the recognition rate of the model consisting of four data of hydrogen, oxygen, nitrogen and carbon is the highest and reaches 93.93 percent, so that the modeling only needs to select the four data of hydrogen, oxygen, nitrogen and carbon, and the detection on the contents of other stable isotopes such as strontium is not needed;
(D) measuring cesium, copper, calcium and rubidium trace element data of rock tea samples of different producing areas
And measuring the contents of Ca, Mg and Mn elements by using an atomic absorption spectrometer, and measuring the contents of Ti, Cr, Co, Ni, Cu, Zn, Rb, Cd, Cs, Ba and Sr elements by using an inductively coupled plasma mass spectrum. Performing microwave digestion on a dry tea sample, observing whether a digestion solution is clear or not after digestion is finished, repeating the pressure digestion step if the digestion solution is turbid, and determining the volume after the volume is fixed by using the instrument if the digestion solution is completely clear;
training and predicting the trace element data by an SVM-RFE method, repeating the training and predicting randomly for 100 times, sequencing the model characteristics of all variables, screening out the trace element characteristic variables of the original producing area of the rock tea, and calculating the model dimension increasing precision after each one-dimensional variable is accumulated by a prediction set to obtain the sequencing sequence of the characteristics of cesium, copper, calcium, rubidium, strontium and barium; then combining the characteristic variables step by step according to a natural sequence, calculating the sensitivity, resolution and recognition rate of the model by utilizing a prediction set, wherein the model consisting of four trace elements of cesium, copper, calcium and rubidium has the highest recognition rate, so that the information among the four trace elements has complementarity, and only the four trace elements of cesium, copper, calcium and rubidium which are modeled need to be selected for detection without measuring other trace elements;
(E) determining amino acid data of rock tea samples of different producing areas:
detecting 27 amino acids in rock tea samples of different producing areas by using an HPLC method, measuring twice in parallel, and taking an average value;
training and predicting amino acid component data of Wuyi rock tea by an SVM-RFE method, randomly repeating for 100 times, sequencing model characteristics of all variables, screening out characteristic variables of tea origin places, calculating model dimension increasing precision after each dimension variable is accumulated by a prediction set, and determining the sequencing sequence of asparagine, proline, tryptophan, phosphoethanolamine, urea and valine; then combining the characteristic variables step by step according to a natural sequence, calculating the sensitivity dimension-increasing precision, the resolution dimension-increasing precision and the recognition rate dimension-increasing precision of the model by utilizing a prediction set, wherein the recognition rate of the model consisting of four amino acids, namely asparagine, proline, tryptophan and phosphoethanolamine is the highest, so that the information among the four amino acids has complementarity, and only four amino acids, namely asparagine, proline, tryptophan and phosphoethanolamine, which are modeled need to be selected for detection;
(F) establishing different producing area rock tea identification database by combining near infrared, stable isotope, trace element and amino acid data
(1) Splicing each piece of near-infrared data (Y-axis data) in an Excel data table, wherein all lines of data in each row form each piece of near-infrared data;
(2) splicing the stable isotope data of each sample with near infrared data according to the sequence of hydrogen, oxygen, nitrogen and carbon, splicing the trace element data with the stable isotope data according to cesium, copper, calcium and rubidium, splicing the amino acid data with the trace element data according to the sequence of asparagine, proline, tryptophan and phosphoethanolamine, and naming the Excel data table formed by the samples in the Wuyi rock tea production area by data 1; an Excel data sheet composed of samples outside the Wuyi rock tea producing area is named by data 2;
(3) running an edge function in MATLAB software, opening data1.xls and data2.xls, and storing in a Mat file format, wherein the file names are corresponding to data1.Mat and data2. Mat;
(4) data segmentation: randomly selecting 65-70% of the total number in the Wuyi rock tea production area as an in-situ model number A1, randomly selecting 65-70% of the exterior of the Wuyi rock tea production area as an out-of-situ model number A2, and establishing a Duplex segmentation program;
(5) k-fold interactive verification method: dividing a sample data set into K subsets (generally, equal division) at random, taking one subset as a verification set, and taking the rest K-1 groups of subsets as a training set; taking K subsets as verification sets in turn, repeating the verification sets for K times in a crossed manner to obtain K results, and taking the average value of the K results as the performance index of a classifier or a model;
(6) establishing a partial least square method identification model: analyzing the fused near infrared, stable isotope, trace element and amino acid data obtained after the data segmentation in the steps (4) and (5) by adopting a partial least square method and establishing a PLSDA model;
(G) taking a sample of an unknown production place to be detected, determining near-infrared characteristic spectrum data, stable isotope mass spectrum data, trace element data and amino acid data according to the steps B, C, D and E, substituting the determined data into the PLSDA model, and if the prediction result is less than 0, judging that the sample to be detected is a sample outside the production place of the Wuyi rock tea; and if the prediction result is greater than 0, judging that the sample to be detected is a sample in the Wuyi rock tea producing area.
The segmentation procedure in the step (E) is respectively as follows: [ model1, test1] = Duplex (data1, a1) and [ model2, test2] = Duplex (data2, a2), yielding model1, test1, model2, test 2; the process of establishing the partial least square method identification model in the step (E) is as follows:
(a) merging training sets: xxxc = [ data1(model 1); data2(model 2) ];
(b) merging the prediction sets: xxxp = [ data1(test 1); data2(test 2) ];
(c) calculating the average spectrum of the training set: mx = mean (xxxc);
(d) training set minus average spectrum: xxxc = xxxc-ones (a,1) × mx;
a is as follows: a1+ a 2;
(e) prediction set minus average spectrum: xxxp = xxxp-ons (B,1) ×;
b is as follows: the sum of the number of in-place test sets B1 and the number of out-of-place test sets B2;
(f) response variable: yyc = -ones (a, 2); yyc (1: a1,1) = 1; yyc (a1+1: a,2) = 1;
the sum of A1 and B1 is the total number of samples C1 in the origin;
the sum of A2 and B2 is the total number of samples C2 outside the original place;
(g) and (3) verifying by K-fold interaction:
indices=crossvalidation('Kfold',x,k);
(h) modeling process:
[betattt,www,BETAPLS1]=plsbasetotal(xxxc,yyc(:,1),lvp1);
[betattt,www,BETAPLS2]=plsbasetotal(xxxc,yyc(:,2),lvp2);
cy=[xxxc*BETAPLS1(:,lvp1),xxxc*BETAPLS2(:,lvp2)];
py=[xxxp*BETAPLS1(:,lvp1),xxxp*BETAPLS2(:,lvp2)];
[rrt,cyy]=max(cy');
[rwwrt,pyy]=max(py');
(i) calculating the sensitivity and resolution of the model in the training process:
err01=length(find(cyy(1:A1)==1))/A1；
err02=length(find(cyy(A1+1:A1+A2)==2))/110；
(j) calculating the sensitivity and resolution of the model in the process of predicting the unknown sample:
err1a=length(find(pyy(1:B1)==1))/B1；
err1b=1-length(find(pyy(B1+1:B1+B2)==1))/B2；
(k) and (4) saving a prediction result: save cyy cyy; save pyy pyy;
(l) The first column of py is the prediction.
The detailed results can be plotted:
bar(cy(:,1));
figure
bar(py(:,1))
the Partial Least Squares (PLSDA) modeling method is used for modeling and analyzing the fusion data of near infrared, stable isotopes, trace elements and amino acids, the recognition rate of the model is the highest and reaches 100.0 percent, and the model is far higher than the PLSDA discrimination result of single data; the detection and identification rate reaches 100.0% for 20, 60 and 100 blind samples, and the method can be used as a source tracing identification technical method for the production area of the Wuyi rock tea.
As shown in fig. 1-13, a first opening is formed in a side wall of the detection chamber 1 in the step b, a first movable cavity is formed in the top of the first opening, a first baffle 121 matched with the first opening is arranged in the first movable cavity, near infrared spectrum detection equipment is arranged in the detection chamber 1, a first movable groove is formed in the bottom of the detection chamber 1, an installation frame 2 is arranged in the first movable groove, a driving motor for driving the installation frame 2 to horizontally move is arranged on the inner wall of the first movable groove, an installation plate 21 is arranged at the top of the installation frame 2, a groove is formed in the installation plate 21, and a material loading box 27 is arranged in the groove; the side wall of the detection chamber 1 is provided with a heating block 15, the top of the detection chamber 1 is provided with a temperature sensor 16 and a humidity sensor, the top of the detection chamber 1 is provided with a first water pipe 14 in a penetrating manner, the bottom of the first water pipe 14 is provided with an atomizing nozzle 141, the inner wall of the detection chamber 1 is provided with a first connecting block 120, a first cavity is arranged in the first connecting block 120, and a drying agent is arranged in the first cavity; when near-infrared detection is performed on tea, the tea is placed on the material carrying box 27, then the material carrying box 27 is placed in the groove, the first baffle 121 moves upwards to enable the first opening to be in an open state, the driving motor drives the installation frame 2 to move in the first movable groove, the material carrying box 27 is driven to enter the detection chamber 1, after the material carrying box 27 completely enters the detection chamber 1, the first baffle 121 moves downwards to seal the first opening, clear water enters the first water conveying pipe 14, water drops are sprayed into the detection chamber 1 through the atomizing nozzle 141, the heating block 15 heats air in the detection chamber, the temperature sensor 16 and the humidity sensor detect the temperature and humidity in the detection chamber, after the temperature and the humidity are in proper conditions, the near-infrared spectrum detection equipment performs detection processing on rock tea, and collects sample spectra.
The sample is placed in the detection chamber for detection in a mode of placing the sample on the material carrying box, so that the sample is detected in a closed space, the influence of near infrared radiation on a human body on the health of the human body is avoided, and the safety of sample detection is improved; by adjusting the environment of the closed space, a proper environment is provided for sample detection, the influence of the outside on the sample detection is avoided, the sample detection precision is improved, and the identification reliability is ensured; under the mutual cooperation of the driving motor and the first baffle, the material carrying box is automatically sent into the detection chamber, so that the detection operation of the sample is more convenient, and the detection efficiency of the sample is improved; the temperature during detection is adjusted through the heating block and the temperature sensor, and the humidity is adjusted through the first water delivery pipe, the drying agent and the humidity sensor, so that a required environment is formed in the detection chamber, and a proper environment is provided for the detection of the sample; when the humidity in the detection chamber is too low, water flow enters the detection chamber through the first water delivery pipe, and the water flow is diffused in the detection chamber in a water mist form under the action of the atomizing spray head, so that the humidity in the detection chamber is improved; when the humidity in the detection chamber is too high, the moisture in the detection chamber is absorbed under the action of the drying agent, the humidity in the detection chamber is reduced, and the sample is prevented from being affected by dampness in the detection process.
The top of the detection chamber is provided with an air cylinder 12, the top of the first opening is provided with a third movable cavity, an air cylinder piston rod is arranged in the third movable cavity in a penetrating manner, and a first baffle plate is arranged on the air cylinder piston rod; the cylinder controls the lifting motion of the first baffle; a third baffle plate 11 is arranged on the side wall of the detection chamber, and one end of the third baffle plate is rotatably connected to the side wall of the detection chamber; when the near infrared spectrum detection equipment is maintained, the third baffle is rotated to open the detection chamber, so that the near infrared spectrum detection equipment can be directly taken out from the detection chamber, and the maintenance cost of the equipment is reduced.
A second opening matched with the first cavity is formed in the side wall of the detection chamber, a fourth baffle 110 is arranged at the second opening, one end of the fourth baffle is hinged to the inner wall of the second opening, a storage box 130 is arranged in the first cavity, and a drying agent is placed in the storage box and can be lime as the drying agent; the fourth baffle and the storage box are arranged so that the drying agent can be replaced, and the water vapor absorption effect of the drying agent is ensured; when the drying agent absorbs moisture, lime and water generate a combined reaction to generate heat, the temperature of the detection chamber is raised, and the auxiliary heating block works so as to reduce the energy consumption of the equipment and adjust the temperature in the detection chamber.
A first movable cavity is arranged at the bottom of the groove, a push block 22 is arranged in the first movable cavity, a sliding groove is formed in the inner wall of the first movable cavity, and a sliding block matched with the sliding groove is arranged on the side wall of the push block 22; a push plate 23 is arranged at the bottom of the push block 22, a connecting pipe 231 is arranged at the bottom of the push plate 23, an air bag 24 is arranged at the bottom of the first movable cavity, the connecting pipe 231 penetrates through the air bag 24, a stop block is arranged on one side of the air bag 24, and a push block 251 is arranged on the other side of the air bag; a connecting groove is arranged on the inner wall of the groove, and a sucking disc 28 matched with the material loading box 27 is arranged at the bottom of the connecting groove; after a sample is placed in the material carrying box 27, the material carrying box 27 is placed in the groove, the material carrying box 27 is pressed downwards to enable the bottom surface of the material carrying box 27 to be in contact with the sucking disc 28, the sucking disc 28 is deformed under the action of pressure, the material carrying box 27 is fixed on the sucking disc 28, the mounting frame 2 drives the material carrying box 27 to enter the detection chamber 1, the push block 251 moves towards the air bag 24, the air bag 24 is deformed after being extruded, air flow in the air bag (24) is pushed into the connecting pipe 231, the connecting pipe 231 is pushed upwards by air pressure, the connecting pipe 231 drives the push plate 23 to move upwards to enable the push plate 23 to push the push block 22 to move upwards, the push block 22 pushes a sample at the bottom of the material carrying box 27 upwards, then the near infrared spectrum detection equipment works to detect the sample to complete spectrum detection of the sample, the air bag in the first movable cavity is extruded under the mutual matching of the push block and the stop block, and air in the air bag enters the connecting pipe after the air bag is deformed, the push plate is pushed to move upwards under the action of air pressure, so that the push plate pushes the material loading box to move upwards together, the side wall of the material loading box is prevented from shielding near infrared rays, samples in the material loading box are fully detected, and detection dead angles are prevented; under the mutual matching of the sliding groove and the sliding block, the movement stroke of the push block is limited, the push block is prevented from being separated from the first movable cavity, and the connecting effect of the push block and the first movable cavity is ensured; under the mutual cooperation of sucking disc and carrier box, promote carrier box and recess connection effect, under the mutual cooperation of sucking disc and ejector pad, make carrier box bottom up for the top surface move, will be in the sample propelling movement of carrier box bottom to carrier box top to do the detection processing to the sample.
The material carrying box comprises a top plate, a connecting ring 271 arranged at the bottom of the top plate and a bottom plate 272 arranged at the bottom of the connecting ring, wherein the connecting ring is made of cloth, when the push block moves upwards to contact with the bottom plate, the push block pushes the bottom plate to move upwards, the connecting ring is stressed and folded, so that the bottom plate rises to the height of the top plate, the bottom plate and the top plate are positioned on the same plane, a sample is lifted, the connecting ring is prevented from shielding near infrared rays, and the detection effect on the sample is improved.
A fourth movable cavity is arranged on the side wall of the first movable cavity, a push rod 25 is arranged in the fourth movable cavity, the push block is provided with a push rod bottom, a limiting block is arranged at one end of the push rod, and a limiting spring is arranged on the limiting block; when the installation piece drives the material loading box and moves towards the detection chamber, the push rod is contacted with the inner wall of the first movable groove, the push rod is pushed to move towards the fourth movable cavity, the push rod drives the push block to move, the push block extrudes the air bag to enable the air bag to deform, the air in the air bag is pushed into the connecting pipe to enable the push plate to move upwards, and the bottom plate is pushed upwards to enable the sample to rise.
A second cavity is arranged on the mounting plate, a first through hole communicated with the sucker is formed in the top of the second cavity, the second cavity extends to one side of the mounting plate, a second through hole is formed in the top of the second cavity, a second movable groove matched with the second through hole is formed in the mounting plate, and a sealing block 26 matched with the second through hole is arranged in the second movable groove; when the material loading box is placed into the groove, the sealing block is positioned at the top of the second through hole to seal the second through hole, the material loading box is placed down to deform the sucking disc, and the material loading box is fixed on the sucking disc; after the sample is detected, the mounting frame drives the material carrying box to move out of the detection chamber, the second movable groove is pushed, the sealing block is moved away from the top of the second through hole, the second cavity is communicated with the outside, and the sucker loses the fixing force on the material carrying box so as to directly take the material carrying box down from the mounting plate.
A first driving wheel 18 is arranged on an output shaft of the driving motor, a connecting shaft is rotatably connected to the inner wall of the first movable groove, a second driving wheel 19 matched with the first driving wheel 18 is arranged on the connecting shaft, driving teeth in transmission fit with the second driving wheel 19 are arranged on the inner wall of the mounting frame 2, the first driving wheel 18 is an incomplete gear, and the diameter of the first driving wheel 18 is far larger than that of the second driving wheel 19; a through cavity is formed in the top of the first cavity, a second movable cavity is formed in the inner wall of the through cavity, a second baffle 140 matched with the through cavity penetrates through the second movable cavity, a connecting spring is arranged on the side wall of the second baffle 140, and an electromagnet matched with the second baffle 140 is arranged in the second movable cavity; after the material loading box 27 is placed in the groove, the first baffle plate 121 moves upwards to enable the first opening to be in an open state, the driving motor drives the first driving wheel 18 to rotate, the first driving wheel 18 rotates to drive the second driving wheel 19 to rotate, the second driving wheel 19 drives the mounting frame 2 to move, and the mounting frame 2 drives the material loading box 27 to enter the detection chamber 1; when the humidity in the detection chamber 1 is insufficient, clean water enters from the first water delivery pipe 14, enters into the detection chamber 1 through the atomizing nozzle 141, and increases the humidity in the detection chamber 1; when the humidity in the detection chamber 1 is too high, the electromagnet is electrified to enable the second baffle 140 to enter the second movable cavity, the second through cavity is in an open state, and water vapor enters the first cavity to be in contact with the drying agent, so that the redundant water vapor is absorbed, and the humidity in the detection chamber 1 is reduced; under the arrangement of incomplete teeth of the first transmission teeth, the first transmission wheel can finish the back-and-forth movement of the mounting frame when rotating towards one direction, so that the mounting frame drives the material loading box to automatically enter and exit the detection chamber, and the use convenience of the detection chamber is improved; the rotating turns of the second driving wheel are increased through the arrangement of different tooth diameters of the first driving wheel and the second driving wheel, so that the mounting frame has enough displacement distance under the action of the second driving wheel to send the material loading box into the detection chamber; the opening and closing of the through cavity are controlled by the second baffle plate, when the humidity in the detection chamber is normal or too low, the through cavity is closed by the second baffle plate, and the contact between water vapor in the detection chamber and a drying agent is avoided; when the humidity in the detection chamber is too high, the electromagnet is electrified to suck the second baffle into the second movable cavity, the through cavity is opened to enable water vapor to be directly contacted with the drying agent, and the water vapor in the detection chamber is absorbed so as to adjust the humidity in the detection chamber.
The top of the detection chamber is provided with a water storage cavity 17, a first water delivery pipe penetrates through the water storage cavity, the side wall of the first water delivery pipe is provided with a third opening matched with the water storage cavity, a sealing ring 15 matched with the first water delivery pipe is arranged in the water storage cavity, the sealing ring is provided with a fourth opening matched with the third opening, and the sealing ring is sleeved on the first water delivery pipe; a drain pipe 13 is arranged on the side wall of the water storage cavity; when the temperature in the detection process is overhigh, the sealing ring rotates to align the third opening and the fourth opening, water flow in the first water delivery pipe enters the water storage cavity through the third opening, so that the water storage cavity is filled with clean water, the detection chamber is cooled under the action of the clean water, and the temperature in the detection chamber is rapidly reduced; when the temperature in the detection chamber is reduced to a designated temperature, the drain pipe is opened to discharge water flow in the water storage cavity, and the temperature in the detection chamber is kept constant.
Claims (7)
1. A Wuyi rock tea production place identification method fusing different detection method characteristic variables is characterized in that: the method comprises the following steps:
a. collecting rock tea samples of different producing areas: the number of samples outside the Wuyi rock tea production area is more than 100 parts, and the proportion of the samples in the range of 50 kilometers around the production area is more than 50 percent; the number of samples in the Wuyi rock tea production area is 2-3 times of that of samples outside the production area, the sampling range covers all production enterprises in the main production area, and each enterprise should have no less than 3 samples;
b. determining near infrared characteristic spectrum data of rock tea samples of different producing areas: near infrared detection parameters: 64 scans, the characteristic spectrum band is the average value of 64 scans, and the scanning range is 12000-4000cm-1The data points are spaced apart by 1.928 cm-1During collection, the rock tea is placed in a detection chamber, the room temperature is controlled at 25 ℃, the humidity is kept stable, and the spectrum of each sample is collected for 1 time;
c. measuring mass spectrum data of four stable isotopes of hydrogen, oxygen, nitrogen and carbon of rock tea samples of different producing areas: delta13C、δ15N、δ18O、δ2H、δ86Determining the content of the Sr stable isotope, repeatedly analyzing each sample for at least more than 3 times, and taking an average value as a final result;
d. and (3) determining the cesium, copper, calcium and rubidium trace element data of rock tea samples of different producing areas: measuring the contents of Ca, Mg and Mn elements by using an atomic absorption spectrometer, and measuring the contents of Ti, Cr, Co, Ni, Cu, Zn, Rb, Cd, Cs, Ba and Sr elements by using an inductively coupled plasma mass spectrum; performing microwave digestion on a dry tea sample, observing whether a digestion solution is clear or not after digestion is finished, repeating the pressure digestion step if the digestion solution is turbid, and determining the volume after the volume is fixed by using the instrument if the digestion solution is completely clear;
e. determining amino acid data of rock tea samples of different producing areas: detecting 27 amino acids in rock tea samples of different producing areas by using an HPLC method, measuring twice in parallel, and taking an average value;
f. establishing different producing area rock tea identification databases by combining near infrared, stable isotope, trace element and amino acid data;
g. taking a sample of an unknown production place to be detected, determining near-infrared characteristic spectrum data, stable isotope mass spectrum data, trace element data and amino acid data according to the steps B, C, D and E, substituting the determined data into the PLSDA model, and if the prediction result is less than 0, judging that the sample to be detected is a sample outside the production place of the Wuyi rock tea; if the prediction result is greater than 0, judging that the sample to be detected is a sample in the Wuyi rock tea producing area;
a first opening is formed in the side wall of the detection chamber (1) in the step b, a first movable cavity is formed in the top of the first opening, a first baffle (121) matched with the first opening is arranged in the first movable cavity, near infrared spectrum detection equipment is arranged in the detection chamber (1), a first movable groove is formed in the bottom of the detection chamber (1), an installation frame (2) is arranged in the first movable groove, a driving motor used for driving the installation frame (2) to move horizontally is arranged on the inner wall of the first movable groove, an installation plate (21) is arranged at the top of the installation frame (2), a groove is formed in the installation plate (21), and a material carrying box (27) is arranged in the groove; the side wall of the detection chamber (1) is provided with a heating block (15), the top of the detection chamber is provided with a temperature sensor (16) and a humidity sensor, the top of the detection chamber (1) is provided with a first water pipe (14) in a penetrating manner, the bottom of the first water pipe (14) is provided with an atomizing nozzle (141), the inner wall of the detection chamber (1) is provided with a first connecting block (120), a first cavity is arranged in the first connecting block (120), and a drying agent is arranged in the first cavity; when the tea leaves are subjected to near-infrared detection, the tea leaves are placed on a material carrying box (27), then the material carrying box (27) is placed in a groove, the material carrying box (27) is placed in the groove, a first baffle plate (121) moves upwards to enable a first opening to be in an open state, a driving motor drives a mounting frame (2) to move in a first movable groove to drive the material carrying box (27) to enter a detection chamber (1), when the material carrying box (27) completely enters the detection chamber (1), the first baffle plate (121) moves downwards to seal the first opening, clear water enters from a first water conveying pipe (14), water drops are sprayed into the detection chamber (1) through an atomizing nozzle (141), a heating block (15) heats air in the detection chamber, a temperature sensor (16) and a humidity sensor are used for detecting the temperature and the humidity in the detection chamber, and when the temperature and the humidity are in proper conditions, and (5) detecting the rock tea by using near infrared spectrum detection equipment, and collecting a sample spectrum.
2. The method for identifying the Wuyi rock tea production area for improving the accuracy of the detection result by combining multiple detection methods according to claim 1, wherein the method comprises the following steps: the detection method in the step c comprises the following steps: training and predicting Wuyi rock tea stable isotope data through SVM-RFE (support vector machine regression feature elimination), randomly repeating for 100 times, sequencing model features of all variables, and screening isotope feature variables of the rock tea origin place, wherein the sequencing sequence is hydrogen, oxygen, nitrogen, carbon and strontium; and the sensitivity, resolution and recognition rate of the model are calculated by utilizing the prediction set, the average result is repeatedly calculated for 100 times, and the recognition rate of the model consisting of four data of hydrogen, oxygen, nitrogen and carbon is the highest and reaches 93.93 percent, so that the modeling only needs to select the four data of hydrogen, oxygen, nitrogen and carbon, and the detection on the contents of other stable isotopes such as strontium is not needed.
3. The method for identifying the Wuyi rock tea production area for improving the accuracy of the detection result by combining multiple detection methods according to claim 1, wherein the method comprises the following steps: the determination method in the step d comprises the following steps: training and predicting the trace element data by an SVM-RFE method, repeating the training and predicting randomly for 100 times, sequencing the model characteristics of all variables, screening out the trace element characteristic variables of the original producing area of the rock tea, and calculating the model dimension increasing precision after each one-dimensional variable is accumulated by a prediction set to obtain the sequencing sequence of the characteristics of cesium, copper, calcium, rubidium, strontium and barium; and then combining the characteristic variables step by step according to a natural sequence, calculating the sensitivity, resolution and recognition rate of the model by using a prediction set, wherein the model consisting of four trace elements of cesium, copper, calcium and rubidium has the highest recognition rate, so that the information among the four trace elements has complementarity, and only the four trace elements of cesium, copper, calcium and rubidium which are modeled need to be selected for detection, and other trace elements do not need to be detected.
4. The method for identifying the Wuyi rock tea production area for improving the accuracy of the detection result by combining multiple detection methods according to claim 1, wherein the method comprises the following steps: the detection method in the step e comprises the following steps: training and predicting amino acid component data of Wuyi rock tea by an SVM-RFE method, randomly repeating for 100 times, sequencing model characteristics of all variables, screening out characteristic variables of tea origin places, calculating model dimension increasing precision after each dimension variable is accumulated by a prediction set, and determining the sequencing sequence of asparagine, proline, tryptophan, phosphoethanolamine, urea and valine; and then combining the characteristic variables step by step according to a natural sequence, calculating the sensitivity dimension-increasing precision, the resolution dimension-increasing precision and the recognition rate dimension-increasing precision of the model by utilizing a prediction set, wherein the recognition rate of the model consisting of the four amino acids of asparagine, proline, tryptophan and phosphoethanolamine is the highest, so that the information among the four amino acids has complementarity, and only the four amino acids of asparagine, proline, tryptophan and phosphoethanolamine which are modeled need to be selected for detection.
5. The method for identifying the Wuyi rock tea production area for improving the accuracy of the detection result by combining multiple detection methods according to claim 1, wherein the method comprises the following steps: the segmentation procedure in the step e is respectively as follows: [ model1, test1] = Duplex (data1, a1) and [ model2, test2] = Duplex (data2, a2), yielding model1, test1, model2, test 2.
6. The method for identifying the Wuyi rock tea production area for improving the accuracy of the detection result by combining multiple detection methods according to claim 1, wherein the method comprises the following steps: a first movable cavity is arranged at the bottom of the groove, a push block (22) is arranged in the first movable cavity, a sliding groove is formed in the inner wall of the first movable cavity, and a sliding block matched with the sliding groove is arranged on the side wall of the push block (22); a push plate (23) is arranged at the bottom of the push block (22), a connecting pipe (231) is arranged at the bottom of the push plate (23), an air bag (24) is arranged at the bottom of the first movable cavity, the connecting pipe (231) penetrates through the air bag (24), a stop block is arranged on one side of the air bag (24), and a push block (251) is arranged on the other side of the air bag; a connecting groove is arranged on the inner wall of the groove, and a sucking disc (28) matched with the material loading box (27) is arranged at the bottom of the connecting groove; after a sample is placed in the material carrying box (27), the material carrying box (27) is placed in the groove, the material carrying box (27) is pressed down, the bottom surface of the material carrying box (27) is in contact with the sucking disc (28), the sucking disc (28) deforms under the action of pressure, the material carrying box (27) is fixed on the sucking disc (28), the material carrying box (27) is driven by the mounting frame (2) to enter the detection chamber (1), the push block (251) moves towards the air bag (24), the air bag (24) deforms after being extruded, air flow in the air bag (24) is pushed into the connecting pipe (231), the connecting pipe (231) is pushed to move upwards by air pressure, the push plate (23) is driven by the connecting pipe (231) to move upwards, the push block (22) is driven by the push plate (23) to move upwards, the push block (22) pushes the sample at the bottom of the material carrying box (27) upwards, and then the near infrared spectrum detection device works to detect the sample, and completing the spectral detection of the sample.
7. The method for identifying the Wuyi rock tea production area for improving the accuracy of the detection result by combining multiple detection methods according to claim 1, wherein the method comprises the following steps: a first driving wheel (18) is arranged on an output shaft of the driving motor, a connecting shaft is rotatably connected to the inner wall of the first movable groove, a second driving wheel (19) matched with the first driving wheel (18) is arranged on the connecting shaft, driving teeth in transmission fit with the second driving wheel (19) are arranged on the inner wall of the mounting frame (2), the first driving wheel (18) is an incomplete gear, and the diameter of the first driving wheel (18) is far larger than that of the second driving wheel (19); a through cavity is formed in the top of the first cavity, a second movable cavity is formed in the inner wall of the through cavity, a second baffle (140) matched with the through cavity penetrates through the second movable cavity, a connecting spring is arranged on the side wall of the second baffle (140), and an electromagnet matched with the second baffle (140) is arranged in the second movable cavity; after the material loading box (27) is placed into the groove, the first baffle (121) moves upwards to enable the first opening to be in an open state, the driving motor drives the first driving wheel (18) to rotate, the first driving wheel (18) rotates to drive the second driving wheel (19) to rotate, the second driving wheel (19) drives the mounting frame (2) to move, and the mounting frame (2) drives the material loading box (27) to enter the detection chamber (1); when the humidity in the detection chamber (1) is insufficient, clear water enters from the first water conveying pipe (14), enters into the detection chamber (1) through the atomizing nozzle (141), and increases the humidity in the detection chamber (1); when the humidity in the detection chamber (1) is too high, the electromagnet is electrified to enable the second baffle (140) to enter the second movable cavity, the second through cavity is in an open state, and water vapor enters the first cavity and contacts with the drying agent to absorb redundant water vapor and reduce the humidity in the detection chamber (1).
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| CN112362827A (en) * | 2020-11-25 | 2021-02-12 | 上海海关动植物与食品检验检疫技术中心 | Method for tracing milk producing area |
| CN113358599A (en) * | 2021-06-07 | 2021-09-07 | 浙江育英职业技术学院 | West lake Longjing traceability technology based on new retail mode |
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