CN113567390A - Method and system for evaluating black tea based on near infrared spectrum technology - Google Patents
Method and system for evaluating black tea based on near infrared spectrum technology Download PDFInfo
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Abstract
The invention belongs to the technical field of black tea evaluation, and discloses a method and a system for evaluating black tea based on a near infrared spectrum technology. The brightness of the spectrogram is adjusted according to the adjustment coefficient, so that the overall brightness of each graph is ensured to be consistent, and distortion and radiation distortion are reduced; by acquiring the main component data of the black tea, the calculation amount in the subsequent matching process can be obviously reduced, and meanwhile, the relative position information in the spectrogram is reserved by utilizing a segmented extraction method in the sampling process, so that the matching precision is improved; the method utilizes principal component analysis, partial least square and other linear transformation methods to construct the black tea evaluation model, and can realize scientific, accurate, rapid and simple judgment of the quality characteristics of the black tea.
Description
Technical Field
The invention belongs to the technical field of black tea evaluation, and particularly relates to a method and a system for evaluating black tea based on a near infrared spectrum technology.
Background
At present, tea leaf evaluation (sensory evaluation) is a practical technology for identifying the quality of tea leaves through sensory evaluation, the quality of tea leaves is mainly identified by human senses (vision, smell, taste and touch), and the method is still a universal method at home and abroad at present. The sensory evaluation of the tea comprises five items of appearance, liquor color, aroma, taste and leaf bottom, which are called five factors for short, and tea evaluation personnel carry out evaluation according to GB/T23776-2009 tea sensory evaluation method. However, the sensory evaluation is easily influenced by the physiological conditions, the working experience, the environmental conditions, the personal preferences and other factors of the evaluation personnel, and the results obtained by evaluating the same tea sample by different evaluation personnel or the same evaluation personnel under different physiological and environmental conditions often have certain differences, so that the accuracy of tea quality evaluation is finally influenced. The tea evaluation process is also limited by the evaluation site, the number of tea evaluators and the number of samples, and meanwhile, each evaluation takes longer time. Meanwhile, no report is found on the technical scheme of black tea evaluation by the near infrared spectrum technology in the existing tea evaluation technology.
Through the above analysis, the problems and defects of the prior art are as follows:
(1) the sensory evaluation is easily influenced by the physiological conditions, the working experience, the environmental conditions, the personal preferences and other factors of the evaluation personnel, and the results obtained by evaluating the same tea sample by different evaluation personnel or the same evaluation personnel under different physiological and environmental conditions often have certain difference, so that the accuracy of tea quality evaluation is finally influenced.
(2) In the sensory evaluation process, the tea evaluation is also limited by the evaluation site, the number of tea evaluators and the number of samples, and meanwhile, the time consumption of each evaluation is long.
(3) The technical scheme about black tea evaluation by a near infrared spectrum technology in the existing tea evaluation technology is not reported yet.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method and a system for evaluating black tea based on a near infrared spectrum technology.
The invention is realized in such a way that a system for evaluating black tea based on near infrared spectrum technology comprises:
the system comprises a black tea sample preparation module, a sample division module, a spectrum information acquisition module, a central control module, a spectrum preprocessing module, a principal component data acquisition module, an evaluation model construction module, a black tea evaluation module, a data storage module and an updating display module.
The black tea sample preparation module is connected with the central control module and used for selecting representative black tea in different time sequences in the raw black tea or the products according to standards through sample preparation equipment to serve as a black tea evaluation sample;
the sample dividing module is connected with the central control module and used for randomly dividing black tea evaluation sample data into a training set and a prediction set through a sample dividing program;
the spectrum information acquisition module is connected with the central control module and is used for scanning the diffuse reflection spectrum of the raw black tea or the product by the spectrum analyzer through an information acquisition program to obtain the data of the near infrared spectrogram of the black tea;
the central control module is connected with the black tea sample preparation module, the sample division module, the spectrum information acquisition module, the spectrum preprocessing module, the main component data acquisition module, the evaluation model construction module, the black tea evaluation module, the data storage module and the updating display module and is used for coordinating and controlling the normal operation of each module of the system for evaluating the black tea based on the near infrared spectrum technology through the central processing unit;
the spectrum preprocessing module is connected with the central control module and used for preprocessing the acquired black tea near infrared spectrum spectrogram data through a spectrum preprocessing program;
the main component data acquisition module is connected with the central control module and used for carrying out dimensionality reduction on the preprocessed near infrared spectrogram data by using a main component analysis method through a main component data acquisition program to acquire main component data of the black tea;
the evaluation model building module is connected with the central control module and used for building a black tea evaluation model according to the obtained black tea main component data through a model building program and training the black tea evaluation model by utilizing a training set and a prediction set;
the black tea evaluation module is connected with the central control module and used for evaluating a black tea sample through the black tea evaluation model obtained through training;
the data storage module is connected with the central control module and used for storing the obtained black tea evaluation sample data, sample division results, black tea near infrared spectrogram data, spectrum preprocessing results, black tea main component data, a black tea evaluation model and black tea evaluation results through a memory;
and the updating display module is connected with the central control module and is used for updating and displaying the acquired black tea evaluation sample data, the sample division result, the black tea near infrared spectrum spectrogram data, the spectrum preprocessing result, the black tea main component data, the black tea evaluation model and the real-time data of the black tea evaluation result through the display.
Further, in the black tea sample preparation module, the uniformly mixed solid or powder sample is placed into a rotary sample cup or a sample bottle, and is lightly pressed to be flat, wherein the thickness of the sample is more than or equal to 10mm, and the thickness of the sample which is not crushed is more than or equal to 20 mm.
Furthermore, in the spectrum information acquisition module, the spectrum analyzer adopts an Antaris II Fourier near infrared spectrum analyzer with the wavelength range of 12000-3800 cm-1(ii) a Resolution 4cm-1Precision of wavelength + -0.4 cm-1。
Further, in the spectrum preprocessing module, the preprocessing of the acquired black tea near infrared spectrum spectrogram data by a spectrum preprocessing program comprises:
(1) acquiring a plurality of to-be-processed black tea near infrared spectrogram data; wherein the near infrared spectrogram of the black tea to be processed comprises line numbers reflecting the size of the spectrogram;
(2) correcting the black tea near infrared spectrum spectrogram to be processed by taking the hyperspectral spectrogram to be processed with the minimum row number in the hyperspectral spectrogram to be processed as a reference spectrogram to obtain a corrected infrared spectrum spectrogram;
(3) acquiring the brightness and the adjustment coefficient of the corrected infrared spectrum spectrogram, and adjusting the brightness of the corrected infrared spectrum spectrogram according to the adjustment coefficient to obtain an adjusted infrared spectrum spectrogram;
(4) for each adjustment version infrared spectrum spectrogram, performing spectrum calibration processing on the adjustment version infrared spectrum spectrogram by adopting the calibration formula to obtain an infrared spectrum calibration spectrogram;
(5) and obtaining the spectral reflectivity of the spectral calibration spectrogram aiming at each infrared spectrum calibration spectrogram, and smoothing the spectral calibration spectrogram according to the spectral reflectivity to obtain a smooth spectral spectrogram.
Further, the acquiring brightness and the adjusting coefficient of the corrected infrared spectrum spectrogram, and adjusting the brightness of the corrected infrared spectrum spectrogram according to the adjusting coefficient to obtain the adjusted infrared spectrum spectrogram, includes:
ak(i,j)＝bk(i,j)×t(i,j)；
wherein i is the column number of the infrared spectrum spectrogram of the correction version, and the value range of i is 1 to the set value of the column number; j is the line number of the infrared spectrum spectrogram of the correction edition, and the value range of j is from 1 to the set value of the line number; k is the number of wave bands, and the value range of k is from 1 to the set value of the number of wave bands; a isk(i,j)The pixel value is adjusted; bk(i,j)The pixel value is the pixel value of which the brightness is not adjusted; t is t(i,j)To adjust the coefficient, t(i,j)And calculating by the average value.
Further, the step of performing spectrum calibration processing on the adjustment version infrared spectrum spectrogram by using the calibration formula aiming at each adjustment version infrared spectrum spectrogram to obtain an infrared spectrum calibration spectrogram comprises the following steps:
where σ denotes the wave number, L denotes the target radiance, SreFor adjusting the real part of the infrared spectrum S, SimFor adjusting the real part, G, of the infrared spectrum SreIn response to the real part of the gain G, GimIn response to the imaginary part of the gain G, O is the background radiance self-emitted by the instrument.
Further, in the main component data acquisition module, the main component data acquisition program is used for reducing the dimension of the preprocessed near infrared spectrum spectrogram data by a main component analysis method to acquire the main component data of the black tea, and the main component data acquisition module comprises:
(1) respectively carrying out normalization processing on the preprocessed near infrared spectrum spectrogram to be matched and the spectrum spectrogram in the spectrum library;
(2) respectively acquiring a near infrared spectrum spectrogram to be matched after normalization processing and a sampling histogram of all spectrum spectrograms in a spectrum library;
(3) calculating a sampling histogram of the near infrared spectrum spectrogram to be matched and Euclidean distances of the sampling histograms of all the spectrum spectrograms in the spectrum library;
(4) and selecting a spectrum with the minimum Euclidean distance from the spectrum sampling histogram to be matched in the spectrum library as a matching object, realizing the dimension reduction processing of the near infrared spectrum, and acquiring the main component data of the black tea.
Further, the normalization processing formula is as follows:
ρn＝(ρ-ρmin)/(ρmax-ρmin)
where ρ isnIs the normalized spectral radiance value, rho is the radiance value of the original spectrum, rhomaxIs the maximum value of the radiation value in the original spectrum, pminIs the minimum of the radiance value in the original spectrum.
Further, the calculating of the sampling histogram of the near infrared spectrum spectrogram to be matched and the euclidean distances of the sampling histograms of all the spectrum spectrograms in the spectrum library includes:
wherein, A ═ α'11,α′12,…α′1M,…α′s1,…α′sMIs a sampling histogram of the spectrum to be measured, alpha'ijThe number of times of intersection of the jth narrow band in the ith corresponding wave band of the spectrum to be detected and the spectrum curve is A ″ { alpha ″)11,α″12,…α″1M,…α″s1,…α″sMIs a sampling histogram of any spectrum in the spectrum library, alpha ″ijThe number of times of intersection of the jth narrow band in the ith corresponding band of any spectrum in the spectrum library with the spectrum curve is determined.
Further, in the evaluation model building module, the building of the black tea evaluation model according to the obtained black tea main component data by the model building program comprises the following steps:
(1) aiming at the treated black tea near infrared spectrum spectrogram, matching sensory evaluation data given by a same sample tea sensory evaluation expert;
(2) selecting an optimal spectrum interval, and performing Partial Least Squares (PLS) regression on the optimal spectrum interval of the correction set sample and the classification variables corresponding to the sample;
(3) and establishing a black tea evaluation model of sensory evaluation five-factor project evaluation and spectral characteristics of the correction set sample.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for applying said system for assessing black tea based on near infrared spectroscopy technology when executed on an electronic device.
It is another object of the present invention to provide a computer readable storage medium storing instructions which, when executed on a computer, cause the computer to apply said system for assessing black tea based on near infrared spectroscopy.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the system for evaluating the black tea based on the near infrared spectrum technology, the obtained data of the near infrared spectrum spectrogram of the black tea is preprocessed through the spectrum preprocessing module, the brightness of the spectrogram can be adjusted according to the adjustment coefficient, the overall brightness of each graph is guaranteed to be consistent, the distorted part of the spectrum curve can be corrected, and then distortion and radiation distortion are reduced; the main component data acquisition module is used for reducing the dimension of the preprocessed near infrared spectrogram data to acquire the main component data of the black tea, so that the calculation amount in subsequent matching can be obviously reduced, meanwhile, the relative position information in the spectrogram is reserved by using a segmented extraction method in sampling, and the matching precision is improved; the evaluation model building module builds the black tea evaluation model by utilizing principal component analysis, partial least square and other linear transformation methods, and scientific, accurate, rapid and simple judgment on the fermentation degree of the black tea can be realized.
Meanwhile, at least one sample can be measured in one minute, and the conventional method generally has about 60 evaluation amounts of three examiners in one day; the invention relates to a model established by depending on the evaluation data of at least six tea sensory evaluation experts or mechanisms on the same tea sample, namely the data measured by the method is accurate, reliable and objective, and the subjective errors possibly caused by multiple reasons such as the number of evaluation and personal preference of manual evaluation are avoided. Meanwhile, the practical problems of shortage of the number of professional tea leaf evaluation talents, high evaluation cost and the like at the present stage also make the invention have positive practical significance in the field.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of a system for evaluating black tea based on near infrared spectroscopy according to an embodiment of the present invention;
in the figure: 1. a black tea sample preparation module; 2. a sample dividing module; 3. a spectrum information acquisition module; 4. a central control module; 5. a spectrum preprocessing module; 6. a principal component data acquisition module; 7. an evaluation model construction module; 8. a black tea evaluation module; 9. a data storage module; 10. and updating the display module.
Fig. 2 is a flow chart of a method for evaluating black tea based on near infrared spectrum technology provided by the embodiment of the invention.
Fig. 3 is a flowchart of a method for preprocessing acquired data of a near infrared spectrogram of black tea by a spectrum preprocessing module using a spectrum preprocessing program according to an embodiment of the present invention.
Fig. 4 is a flowchart of a method for obtaining black tea principal component data by performing dimensionality reduction on preprocessed near infrared spectrogram data of a near infrared spectrum by a principal component analysis method through a principal component data obtaining module and a principal component data obtaining program according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for constructing a black tea evaluation model according to the obtained main component data of black tea by using a model construction program through an evaluation model construction module according to an embodiment of the present invention.
Fig. 6 is a modeling diagram provided by an embodiment of the invention.
FIG. 7 is a graphical representation of modeling data provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a method and a system for evaluating black tea based on a near infrared spectrum technology, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a system for evaluating black tea based on near infrared spectrum technology provided by an embodiment of the present invention includes: the system comprises a black tea sample preparation module 1, a sample division module 2, a spectrum information acquisition module 3, a central control module 4, a spectrum preprocessing module 5, a principal component data acquisition module 6, an evaluation model construction module 7, a black tea evaluation module 8, a data storage module 9 and an update display module 10.
The black tea sample preparation module 1 is connected with the central control module 4 and used for selecting black tea fermented leaves under different time sequences in a black tea primary tea or product sample preparation process through sample preparation equipment to serve as black tea evaluation samples;
the sample dividing module 2 is connected with the central control module 4 and used for randomly dividing black tea evaluation sample data into a training set and a prediction set through a sample dividing program;
the spectrum information acquisition module 3 is connected with the central control module 4 and is used for scanning the diffuse reflection spectrum of the raw black tea or the product by using the spectrum analyzer through an information acquisition program to obtain the data of the near infrared spectrum spectrogram of the black tea;
the central control module 4 is connected with the black tea sample preparation module 1, the sample division module 2, the spectrum information acquisition module 3, the spectrum preprocessing module 5, the main component data acquisition module 6, the evaluation model construction module 7, the black tea evaluation module 8, the data storage module 9 and the update display module 10, and is used for coordinating and controlling the normal operation of each module of the system for evaluating the black tea based on the near infrared spectrum technology through a central processing unit;
the spectrum preprocessing module 5 is connected with the central control module 4 and used for preprocessing the acquired data of the near infrared spectrum spectrogram of the black tea through a spectrum preprocessing program;
the main component data acquisition module 6 is connected with the central control module 4 and used for performing dimensionality reduction processing on the preprocessed near infrared spectrogram data by a main component analysis method through a main component data acquisition program to acquire main component data of the black tea;
the evaluation model building module 7 is connected with the central control module 4 and used for building a black tea evaluation model according to the obtained black tea main component data through a model building program and training the black tea evaluation model by utilizing a training set and a prediction set;
the black tea evaluation module 8 is connected with the central control module 4 and used for evaluating a black tea sample through a black tea evaluation model obtained through training;
the data storage module 9 is connected with the central control module 4 and used for storing the obtained black tea evaluation sample data, sample division results, black tea near infrared spectrum spectrogram data, spectrum preprocessing results, black tea main component data, a black tea evaluation model and black tea evaluation results through a memory;
and the updating display module 10 is connected with the central control module 4 and is used for updating and displaying the acquired black tea evaluation sample data, the sample division result, the black tea near infrared spectrum spectrogram data, the spectrum preprocessing result, the black tea main component data, the black tea evaluation model and the real-time data of the black tea evaluation result through a display.
As shown in fig. 2, the method for evaluating black tea based on near infrared spectrum technology provided by the embodiment of the present invention comprises the following steps:
s101, selecting representative black tea in different time sequences in the raw black tea or the product according to standards by a black tea sample preparation module through sample preparation equipment, and taking the representative black tea as a black tea evaluation sample;
s102, randomly dividing black tea evaluation sample data into a training set and a prediction set by a sample dividing module through a sample dividing program;
s103, performing diffuse reflection spectrum scanning on the crude black tea or the product by using the spectrum analyzer through the spectrum information acquisition module by using an information acquisition program to obtain the data of the near infrared spectrum spectrogram of the black tea;
s104, the central control module utilizes a central processing unit to coordinate and control the normal operation of each module of the system for evaluating the black tea based on the near infrared spectrum technology;
s105, preprocessing the acquired black tea near infrared spectrum spectrogram data by using a spectrum preprocessing program through a spectrum preprocessing module;
s106, performing dimensionality reduction on the preprocessed near infrared spectrogram data by using a principal component analysis method through a principal component data acquisition module by using a principal component data acquisition program to acquire the principal component data of the black tea;
s107, constructing a black tea evaluation model according to the obtained black tea main component data by using an evaluation model construction module through a model construction program, and training the black tea evaluation model by using a training set and a prediction set;
s108, conducting black tea sample evaluation through a black tea evaluation module by using the black tea evaluation model obtained through training;
s109, storing the obtained black tea evaluation sample data, sample division results, black tea near infrared spectrum spectrogram data, spectrum preprocessing results, black tea main component data, a black tea evaluation model and black tea evaluation results by using a memory through a data storage module;
and S110, updating and displaying the obtained black tea evaluation sample data, the sample division result, the black tea near infrared spectrum spectrogram data, the spectrum preprocessing result, the black tea main component data, the black tea evaluation model and the real-time data of the black tea evaluation result by using the display through the updating and displaying module.
In the step S101 provided by the embodiment of the invention, the total fermentation time of the black tea is 6-8 h, the uniformly mixed solid or powder sample is placed into a rotary sample cup or a sample bottle, the sample is lightly pressed and leveled, the thickness of the sample is more than or equal to 10mm, and the thickness of the sample which is not crushed is more than or equal to 20 mm. .
In step S103 provided by the embodiment of the present invention, the spectrum analyzer uses an Antaris ii fourier near infrared spectrum analyzer, and the wavelength range is 12000-3800 cm-1(ii) a Resolution 4cm-1Precision of wavelength + -0.4 cm-1。。
As shown in fig. 3, in step S105, the preprocessing the acquired black tea near-infrared spectrogram data by the spectrum preprocessing module using the spectrum preprocessing program according to the embodiment of the present invention includes:
s201, acquiring a plurality of to-be-processed black tea near infrared spectrogram data; wherein the near infrared spectrogram of the black tea to be processed comprises line numbers reflecting the size of the spectrogram;
s202, correcting the black tea near infrared spectrum spectrogram to be processed by taking the hyperspectral spectrogram to be processed with the minimum row number in the hyperspectral spectrogram to be processed as a reference spectrogram to obtain a corrected infrared spectrum spectrogram;
s203, obtaining the brightness and the adjustment coefficient of the corrected infrared spectrum spectrogram, and adjusting the brightness of the corrected infrared spectrum spectrogram according to the adjustment coefficient to obtain an adjusted infrared spectrum spectrogram;
s204, aiming at each adjustment version infrared spectrum spectrogram, performing spectrum calibration processing on the adjustment version infrared spectrum spectrogram by adopting the calibration formula to obtain an infrared spectrum calibration spectrogram;
s205, aiming at each infrared spectrum calibration spectrogram, obtaining the spectral reflectivity of the spectrum calibration spectrogram, and smoothing the spectrum calibration spectrogram according to the spectral reflectivity to obtain a smooth spectrum spectrogram.
In step S203 provided in the embodiment of the present invention, the obtaining of the brightness and the adjustment coefficient of the corrected infrared spectrum spectrogram, and adjusting the brightness of the corrected infrared spectrum spectrogram according to the adjustment coefficient to obtain the adjusted infrared spectrum spectrogram includes:
ak(i,j)＝bk(i,j)×t(i,j)；
wherein i is the column number of the infrared spectrum spectrogram of the correction version, and the value range of i is 1 to the set value of the column number; j is the line number of the infrared spectrum spectrogram of the correction edition, and the value range of j is from 1 to the set value of the line number; k is the number of wave bands, and the value range of k is from 1 to the set value of the number of wave bands; a isk(i,j)The pixel value is adjusted; bk(i,j)The pixel value is the pixel value of which the brightness is not adjusted; t is t(i,j)To adjust the coefficient, t(i,j)And calculating by the average value.
In step S204 provided in the embodiment of the present invention, the performing, by using the calibration formula, a spectrum calibration process on each adjustment version of the infrared spectrum spectrogram to obtain an infrared spectrum calibration spectrogram includes:
where σ denotes the wave number, L denotes the target radiance, SreFor adjusting the real part of the infrared spectrum S, SimFor adjusting the real part, G, of the infrared spectrum SreIn response to the real part of the gain G, GimIn response to the imaginary part of the gain G, O is the background radiance self-emitted by the instrument.
As shown in fig. 4, in step S106 provided in the embodiment of the present invention, the performing, by the principal component data obtaining module, dimensionality reduction on the preprocessed near infrared spectrogram data by using a principal component analysis method by using a principal component data obtaining program to obtain black tea principal component data includes:
s301, respectively carrying out normalization processing on the preprocessed near infrared spectrum spectrogram to be matched and the spectrum spectrogram in the spectrum library;
s302, respectively obtaining a near infrared spectrum spectrogram to be matched after normalization processing and a sampling histogram of all spectrum spectrograms in a spectrum library;
s303, calculating sampling histograms of the near infrared spectrum spectrograms to be matched and Euclidean distances of the sampling histograms of all the spectral spectrograms in the spectral library;
s304, selecting a spectrum with the minimum Euclidean distance from the spectrum sampling histogram to be matched from the spectrum library as a matching object, realizing the dimension reduction processing of the near infrared spectrum, and acquiring the main component data of the black tea.
In step S301 provided in the embodiment of the present invention, the normalization processing formula is as follows:
ρn＝(ρ-ρmin)/(ρmax-ρmin)
where ρ isnIs the normalized spectral radiance value, rho is the radiance value of the original spectrum, rhomaxIs the maximum value of the radiation value in the original spectrum, pminIs the minimum of the radiance value in the original spectrum.
In step S303 provided in the embodiment of the present invention, the calculating a sampling histogram of the near infrared spectrum spectrogram to be matched and euclidean distances between sampling histograms of all spectrum spectrograms in the spectrum library includes:
wherein, A ═ α'11,α′12,…α′1M,…α′s1,…α′sMIs a sampling histogram of the spectrum to be measured, alpha'ijThe number of times of intersection of the jth narrow band in the ith corresponding wave band of the spectrum to be detected and the spectrum curve is A ″ { alpha ″)11,α″12,…α″1M,…α″s1,…α″sMIs a sampling histogram of any spectrum in the spectrum library, alpha ″ijThe number of times of intersection of the jth narrow band in the ith corresponding band of any spectrum in the spectrum library with the spectrum curve is determined.
As shown in fig. 5, in step S107 provided in the embodiment of the present invention, the building of the black tea evaluation model by the evaluation model building module according to the obtained black tea main component data by using the model building program includes:
s401, setting classification variables for the processed near infrared spectrum spectrogram of the black tea;
s402, selecting an optimal spectrum interval, and performing Partial Least Squares (PLS) regression on the optimal spectrum interval of the correction set sample and the classification variable corresponding to the sample;
and S403, establishing a black tea evaluation model of the classification variables and the spectral characteristics of the correction set samples.
The technical solution of the present invention will be further described with reference to the following examples.
The method for rapidly giving the Guizhou black tea total score in the sensory evaluation based on the near infrared spectrum technology provided by the embodiment of the invention comprises the following steps:
preparing a tea sample: collecting 268 samples of tea leaves in 2019-2020 tea activities, packaging in aluminum foil sample bags, sealing and refrigerating;
the experts were examined, and 26 experts in 13 units were examined for tea.
(3) And (3) acquisition of near infrared spectrum: collecting a diffuse reflection spectrogram of a tea sample and a transmission spectrogram of tea soup of the tea sample;
(4) establishing a model: through the TQ Analyst modeling software, the sensory evaluation and correction model analysis and evaluation are similar to the evaluation of the main chemical component quantitative correction model, the near-infrared characteristic spectrogram of the sample is combined with the evaluation given by an evaluation expert to establish a Guizhou black tea near-infrared sensory evaluation and correction model, which is shown in figure 6;
(5) and (3) verification of the model: measuring a new tea sample on a near-infrared instrument according to the same method as the step 2, measuring by using the sensory model established in the step 4, comparing with the result measured by a tea taster according to the national standard method, and obtaining the sensory evaluation result consistent with the results obtained by the two methods, wherein the result is shown in figure 7.
Wherein, the modeling data source is: 1. in 2019, 30 samples are taken in autumn tea fighting games, and 7 evaluation experts are selected; 2. in 2020 spring tea fighting, 38 samples are obtained, and 7 evaluation experts are available; 3. in 2019, the Qian tea cup has 30 samples and 7 evaluation experts; 4. 2020 Qian teacup, 56 samples, 7 assessment experts; 5. in 2020, Riping fighting tea match, 22 samples and 7 appraisal experts; 6. meitan fourth world tea king race, 60 samples, 5 appraisal experts.
In the description of the present invention, "a plurality" means two or more unless otherwise specified; the terms "upper", "lower", "left", "right", "inner", "outer", "front", "rear", "head", "tail", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are only for convenience in describing and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, should not be construed as limiting the invention. Furthermore, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A system for assessing black tea based on near infrared spectroscopy, comprising:
the system comprises a black tea sample preparation module, a sample division module, a spectrum information acquisition module, a central control module, a spectrum preprocessing module, a principal component data acquisition module, an evaluation model construction module, a black tea evaluation module, a data storage module and an updating display module;
the black tea sample preparation module is connected with the central control module and used for selecting black tea fermented leaves under different time sequences in a black tea primary tea or product sample preparation process through sample preparation equipment to serve as black tea evaluation samples;
the sample dividing module is connected with the central control module and used for randomly dividing black tea evaluation sample data into a training set and a prediction set through a sample dividing program;
the spectrum information acquisition module is connected with the central control module and is used for scanning the diffuse reflection spectrum of the raw black tea or the product by the spectrum analyzer through an information acquisition program to obtain the data of the near infrared spectrogram of the black tea;
the central control module is connected with the black tea sample preparation module, the sample division module, the spectrum information acquisition module, the spectrum preprocessing module, the main component data acquisition module, the evaluation model construction module, the black tea evaluation module, the data storage module and the updating display module and is used for coordinating and controlling the normal operation of each module of the system for evaluating the black tea based on the near infrared spectrum technology through the central processing unit;
the spectrum preprocessing module is connected with the central control module and used for preprocessing the acquired black tea near infrared spectrum spectrogram data through a spectrum preprocessing program;
the main component data acquisition module is connected with the central control module and used for carrying out dimensionality reduction on the preprocessed near infrared spectrogram data by using a main component analysis method through a main component data acquisition program to acquire main component data of the black tea;
the evaluation model building module is connected with the central control module and used for building a black tea evaluation model according to the obtained black tea main component data through a model building program and training the black tea evaluation model by utilizing a training set and a prediction set;
the black tea evaluation module is connected with the central control module and used for evaluating a black tea sample through the black tea evaluation model obtained through training;
the data storage module is connected with the central control module and used for storing the obtained black tea evaluation sample data, sample division results, black tea near infrared spectrogram data, spectrum preprocessing results, black tea main component data, a black tea evaluation model and black tea evaluation results through a memory;
and the updating display module is connected with the central control module and is used for updating and displaying the acquired black tea evaluation sample data, the sample division result, the black tea near infrared spectrum spectrogram data, the spectrum preprocessing result, the black tea main component data, the black tea evaluation model and the real-time data of the black tea evaluation result through the display.
2. A system for assessing black tea based on near infrared spectroscopy as claimed in claim 1 wherein the black tea sample preparation module places the blended solid or powder sample into a rotating sample cup or bottle and gently presses it flat with a sample thickness of 10mm or more and an unpulverized sample thickness of 20mm or more.
3. The system for evaluating black tea based on near infrared spectrum technology as claimed in claim 1, wherein in the spectrum information collecting module, the spectrum analyzer is an Antaris II Fourier near infrared spectrum analyzer with a wavelength range of 12000-3800 cm-1(ii) a Resolution 4cm-1Precision of wavelength + -0.4 cm-1。
4. The system for assessing black tea based on near infrared spectroscopy as claimed in claim 1, wherein the preprocessing of the acquired black tea near infrared spectrogram data by the spectrum preprocessing program in the spectrum preprocessing module comprises:
(1) acquiring a plurality of to-be-processed black tea near infrared spectrogram data; wherein the near infrared spectrogram of the black tea to be processed comprises line numbers reflecting the size of the spectrogram;
(2) correcting the black tea near infrared spectrum spectrogram to be processed by taking the hyperspectral spectrogram to be processed with the minimum row number in the hyperspectral spectrogram to be processed as a reference spectrogram to obtain a corrected infrared spectrum spectrogram;
(3) acquiring the brightness and the adjustment coefficient of the corrected infrared spectrum spectrogram, and adjusting the brightness of the corrected infrared spectrum spectrogram according to the adjustment coefficient to obtain an adjusted infrared spectrum spectrogram;
(4) for each adjustment version infrared spectrum spectrogram, performing spectrum calibration processing on the adjustment version infrared spectrum spectrogram by adopting the calibration formula to obtain an infrared spectrum calibration spectrogram;
(5) and obtaining the spectral reflectivity of the spectral calibration spectrogram aiming at each infrared spectrum calibration spectrogram, and smoothing the spectral calibration spectrogram according to the spectral reflectivity to obtain a smooth spectral spectrogram.
5. The system for assessing black tea based on near infrared spectroscopy as claimed in claim 4, wherein the obtaining of the brightness and the adjustment factor of the corrected infrared spectrogram, the adjusting of the brightness of the corrected infrared spectrogram according to the adjustment factor to obtain the adjusted infrared spectrogram comprises:
ak(i,j)＝bk(i,j)×t(i,j)；
wherein i is the column number of the infrared spectrum spectrogram of the correction version, and the value range of i is 1 to the set value of the column number; j is the line number of the infrared spectrum spectrogram of the correction edition, and the value range of j is from 1 to the set value of the line number; k is the number of wave bands, and the value range of k is from 1 to the set value of the number of wave bands; a isk(i,j)The pixel value is adjusted; bk(i,j)The pixel value is the pixel value of which the brightness is not adjusted; t is t(i,j)To adjust the coefficient, t(i,j)And calculating by the average value.
6. The system for assessing black tea based on near infrared spectroscopy as claimed in claim 4, wherein the spectral calibration processing is performed on each adjusted version of the infrared spectrum spectrogram by using the calibration formula to obtain the infrared spectrum calibration spectrogram, comprising:
where σ denotes the wave number, L denotes the target radiance, SreFor adjusting the real part of the infrared spectrum S, SimFor adjusting the real part, G, of the infrared spectrum SreIn response to the real part of the gain G, GimIn response to the imaginary part of the gain G, O is the background radiance self-emitted by the instrument.
7. The system for assessing black tea based on near infrared spectroscopy as claimed in claim 1, wherein the principal component data obtaining module, in which the principal component data obtaining program performs dimensionality reduction on the preprocessed near infrared spectrogram data by a principal component analysis method, obtains black tea principal component data, comprises:
(1) respectively carrying out normalization processing on the preprocessed near infrared spectrum spectrogram to be matched and the spectrum spectrogram in the spectrum library;
(2) respectively acquiring a near infrared spectrum spectrogram to be matched after normalization processing and a sampling histogram of all spectrum spectrograms in a spectrum library;
(3) calculating a sampling histogram of the near infrared spectrum spectrogram to be matched and Euclidean distances of the sampling histograms of all the spectrum spectrograms in the spectrum library;
(4) selecting a spectrum with the minimum Euclidean distance from a spectrum sampling histogram to be matched as a matching object in a spectrum library, realizing the dimension reduction processing of the near infrared spectrum, and acquiring the main component data of the black tea;
the normalization processing formula is as follows:
ρn＝(ρ-ρmin)/(ρmax-ρmin)
where ρ isnIs the normalized spectral radiance value, rho is the radiance value of the original spectrum, rhomaxIs the maximum value of the radiation value in the original spectrum, pminFor the original light of the stripThe minimum of the radiation values in the spectrum;
the calculation of the Euclidean distance of the sampling histogram of the near infrared spectrum spectrogram to be matched and the sampling histograms of all the spectrum spectrograms in the spectrum library comprises the following steps:
wherein, A ═ α'11,α′12,…α′1M,…α′s1,…α′sMIs a sampling histogram of the spectrum to be measured, alpha'ijThe number of times of intersection of the jth narrow band in the ith corresponding wave band of the spectrum to be detected and the spectrum curve is A ″ { alpha ″)11,α″12,…α″1M,…α″s1,…α″sMIs a sampling histogram of any spectrum in the spectrum library, alpha ″ijThe number of times of intersection of the jth narrow band in the ith corresponding band of any spectrum in the spectrum library with the spectrum curve is determined.
8. The system for evaluating black tea based on near infrared spectrum technology as claimed in claim 1, wherein in the evaluation model building module, the building of the black tea evaluation model according to the obtained black tea main component data through a model building program comprises:
(1) setting classification variables for the treated black tea near infrared spectrum spectrogram;
(2) selecting an optimal spectrum interval, and performing Partial Least Squares (PLS) regression on the optimal spectrum interval of the correction set sample and the classification variables corresponding to the sample;
(3) and establishing a black tea evaluation model of classification variables and spectral characteristics of the correction set samples.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for applying a system for assessing black tea based on near infrared spectroscopy as claimed in any one of claims 1 to 8 when executed on an electronic device.
10. A computer readable storage medium storing instructions which, when executed on a computer, cause the computer to apply a system for assessing black tea based on near infrared spectroscopy as claimed in any one of claims 1 to 8.
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