62 results about "Geographical indication" patented technology

The invention relates to a Wuyi rock tea production place identification method through combination of four detection technologies, and belongs to the technical field of geographical indication product authenticity recognition. In the prior art, the single detection data cannot represent all production place traceability key information, the data matching problem exists when different types of the detection data are subjected to combined use in the metrology method, and other problems exist. A purpose of the present invention is to solve the problems in the prior art. According to the present invention, based on the partial least square discrimination model, the near infrared characteristic spectrum data, the stable isotope data, the trace element data and the amino acid data of the rock teas (produced inside and outside the geographical indication production place) from different production places are integrally fused, the analysis model is established, the sample is extracted, and the rock tea production place is objectively and accurately determined by using the model, wherein the recognition rate is high, achieves 100.0%, and is higher than the PLSDA determining result of the single data, and the recognition rate of the blind sample achieves 100%; and the method has the good application prospect, and can be used as the Wuyi rock tea production place traceability recognition technical method.

The invention provides a system and a method for searching social relations via a geographical indication with time property based on an internet electronic map or a map. The system comprises an electronic map, a user mark storage cell, a business server and user terminal equipment. Mark data submitted by a user or a mobile terminal with a location system is used to upload the geographical indication with time range information; the system is used for automatically judging whether two marks are matched with each other via geographical range and time range, and transmitting information to the user who is matched successfully to recommend relation. The user could set geographical range and time range via the electronic map to select the marks to obtain interested marks so as to reestablish relation according to the contact information of the user to which the marks belong.

The invention belongs to near infrared spectrum analysis and in particular discloses a method for authenticating Xiangshui rice by near-infrared spectroscopy. The method comprises the following steps of: building a clustering discrimination and eligibility discrimination model by respectively selecting a proper spectra preprocessing way, smooth points, a spectral interval, factor number and the like; and scanning a near infrared spectrogram of an unknown sample under the same condition, pre-processing the near infrared spectrogram, and authenticating the unknown sample according to the built clustering discrimination and eligibility discrimination model by selecting the same smooth points, spectral interval, factor number and the like. The method solves the problem of unavailable protection and authentication for the Xiangshui rice, the geographical indication product in the prior art, and has the advantages of well authenticating the Xiangshui rice, along with high identification rate.

The invention relates to an identification method for the producing area of a plant based on multiple detection technologies. The method provided by the invention identifies the producing area of Wuyi rock tea by using a combination of near-infrared spectroscopic data, stable isotope mass spectrometric data and trace element data and belongs to the technical field of identification of the authenticity of products of geographical indication. The objective of the invention is to overcome the problems that single detection data cannot represent all the key information in tracing of a producing area and that data matching is hard to realize for combined usage of detection data of different types in metrological method and other problems in the prior art. According to the invention, near-infrared spectroscopic data, stable isotope mass spectrometric data and trace element data are fused together for modeling analysis on the basis of a least squares support vector machine (LS-SVM) model, and a highest identification rate is obtained, as high as 100.0% and much higher than the determination results of LS-SVM established on the basis of single data; and the identification method has a blind sample identification rate of 100%, so the method has good application prospects. The identification method is also applicable to identification of the producing areas of other plant samples like Chinese torreya and lotus root starch; and the method achieves a producing area identification rate of 99.8% or above in identification of plants except tea.

The invention relates to a Wuyi rock tea production place identification method through combination of isotope detection and trace element detection, and belongs to the technical field of geographical indication product authenticity recognition. In the prior art, the single detection data cannot represent all production place traceability key information, the data matching problem exists when different types of the detection data are subjected to combined use and analysis in the metrology method, and other problems exist. A purpose of the present invention is to solve the problems in the prior art. According to the present invention, based on the partial least square discrimination model, the isotope data and the trace element data of the rock teas (produced inside and outside the geographical indication production place) from different production places are integrally fused, the analysis model is established, the sample is extracted, and the rock tea production place is objectively and accurately determined by using the model, wherein the recognition rate achieves 100.0% and is far higher than the PLSDA result of the single data, and the recognition rate of the blind sample achieves 100%; and the method has the good application prospect, and can be used as the Wuyi rock tea production place traceability recognition technical method.

The invention relates to a Wuyi rock tea production place identification method through combination of three detection methods such as near-infrared spectrum detection, stable isotope mass spectrum detection and catechin detection so as to establish a Wuyi rock tea production place identification method, and belongs to the technical field of geographical indication product authenticity recognition. In the prior art, the single detection data cannot represent all production place traceability key information, the data matching problem exists when different types of the detection data are subjected to combined use in the metrology method, and other problems exist. A purpose of the present invention is to solve the problems in the prior art. According to the present invention, based on the least square support vector machine model, the near infrared characteristic spectrum data, the stable isotope data and the catechin data of the rock teas from different production places are integrally fused, the LS-SVM analysis model is established, the recognition rate is highest, achieves 100.0%, and is higher than the LS-SVM result of the single data, and the recognition rate of the blind sample achieves 100%; and the method has the good application prospect, and can be used as the Wuyi rock tea production place traceability recognition technical method.

The invention relates to a Wuyi rock tea production place identification method based on deep learning, and belongs to the technical field of authenticity identification of geographical indication products. The method aims at solving the problems that a single kind of detection data can not represent complete key information about production place tracing, and different kinds of detection data are not matched when used in combination in a metrological method. According to the method, based on a neural network ELM model with a deep learning function, an ELM analysis model is established for stable isotope data, microelement data, electronic tongue data and fused data of the three kinds of data of rock tea from different production places with the same method; after sample extraction, the production places of the rock tea are subjectively and accurately judged with the model. The model established with the fused data of the three kinds of data has the highest identification rate which reaches 100.0% and is far higher than that of the discrimination result of a neural network model established with a single kind of data; besides, the identification rate on blind samples reaches 100%. The method has good application prospects and can serve as a technical method for tracing identification of Wuyi rock tea production places.

The invention provides a rapid aroma fingerprint identification method for a geographical indication protection product of vinegar. The method comprises the following steps of: A) enriching and detecting aroma components in the vinegar; B) constructing a shared model aroma fingerprint; C) screening principal aroma components through principal component analysis (PCA); D) establishing an aroma fingerprint model of the geographical indication protection product of the vinegar; and E) rapidly identifying an unknown vinegar sample. The rapid aroma fingerprint identification method for the geographical indication protection product of the vinegar can be widely applied to screening of doubtable fake geographical indication protection products of the vinegar, has short analysis time, is high in sensitivity, accuracy and practicality and has significance of identifying and protecting the geographical indication protection products of the vinegar, and the problem that authenticity identification of the geographical indication protection product of the vinegar in the market is difficult and consumes long time is solved.

The invention discloses a radio frequency interference detection method based on satellite passive microwave remote sensing data. The method comprises the steps of data screening 1, geological positioning 2, mean processing 3, geographical indication 4 and comprehensive analysis 5, wherein in data screening 1, only land data in the satellite passive microwave remote sensing data is extracted for analysis; in the geological positioning 2, each group of data in which radio frequency interference is detected is subjected to (0.001 degree)* (0.001 degree) grid point cubic polynomial interpolation, and a position coordinate corresponding to a maximum brightness temperature value after extraction and interpolation is taken as a position of radio frequency interference; in the geographical indication 4, the geographical position distribution characteristic, brightness temperature distribution characteristic and occurrence rate of radio frequency interference can be obtained through analysis; and in the comprehensive analysis 5, the change of radio frequency interference along with time and directions can be obtained through analysis. Compared with statistics based on frequency domains and signal characteristics, the radio frequency interference detection method is well applicable to radio frequency interference detection of the satellite passive microwave remote sensing data.

The invention relates to an identification method for the producing area of Wuyi rock tea and with a deep learning function, belonging to the technical field of identification of the authenticity of products of geographical indication. The objective of the invention is to overcome the problems that single detection data cannot represent all the key information in tracing of the producing area and that data matching is hard to realize for combined usage of detection data of different types in metrological method and other problems in the prior art. According to the invention, near-infrared characteristic spectroscopic data, stable isotope mass spectrometric data, trace element data and electronic tongue data of rock tea from different producing areas (including rock tea from and not from a geographically indicated producing area) are fused together for modeling analysis on the basis of an ELM neural network discrimination model, and the model is used for objectively and accurately determining the producing area of an extracted sample; the identification method has the highest identification rate, as high as 100.0% and higher than the ELM determination results of single data; and the identification method has a blind sample identification rate of 100%, so the method has good application prospects and is applicable as a technical identification method for tracing the producing area of the Wuyi rock tea.

The present invention discloses a rice producing area identification method based on mineral matter analysis technology and application, and belongs to the technical field of quality and safety of agricultural products. The method is as follows: after pretreatment of raw rices of different producing areas, mineral element content of the rice can be measured by high-resolution inductively coupled plasma mass spectrometer, the characteristics of mineral element content of the rice of different producing areas can be analyzed, a discrimination model can be built and validated, and the producing area of a to-be-tested rice can be measured by the discrimination model. The method has the characteristics of high discriminating accuracy, the accuracy rate can reach 97.8%, and the method has great significance to agricultural product quality inspection and protection of geographical indications.

The invention discloses a fluorescence spectrum identification method of Fushunliao schisandra chinensis. The fluorescence spectrum identification method comprises the following steps of: firstly, obtaining a three-dimensional fluorescence spectrum of the Fushunliao schisandra chinensis and deriving the three-dimensional fluorescence spectrum in a data file ASCII (American Standard Code for Information Interchange) format to obtain original data of the three-dimensional fluorescence spectrum; extracting constant wavelength synchronous fluorescence signal data of emission wavelength and excitation wavelength with different wavelength intervals; obtaining a synchronous dynamic spectrum disturbed by different wavelength intervals between the related emission wavelength and excitation wavelength according to the data, so as to establish a two-dimensional related synchronous fluorescence spectrum of the Fushunliao schisandra chinensis; establishing a two-dimensional related synchronous fluorescence spectrum of unknown schisandra chinensis of the source area according to the same method; and comparing the two-dimensional related synchronous fluorescence spectrum with the two-dimensional related synchronous fluorescence spectrum of the Fushunliao schisandra chinensis to judge whether the sample is the Fushunliao schisandra chinensis. According to the method disclosed by the invention, the Fushunliao schisandra chinensis which is used as a geographical indication product and other non-Fushunliao schisandra chinensis can be directly and visually identified to enhance the protection on the Fushunliao schisandra chinensis.

The invention relates to an intelligent identification method for the producing area of Wuyi rock tea based on multiple inspection techniques, belonging to the technical field of identification of the authenticity of products of geographical indication. The objective of the invention is to overcome the problems that single detection data cannot represent all the key information in tracing of the producing area and that data matching is hard to realize for combined usage of detection data of different types in metrological method and other problems in the prior art. According to the invention, near-infrared characteristic spectroscopic data, stable isotope mass spectrometric data, trace element data, amino acid data, catechin data and electronic tongue data of rock tea from different producing areas (including rock tea from and not from a geographically indicated producing area) are fused together for modeling analysis on the basis of a partial least squares discrimination model, and the model is used for objectively and accurately determining the producing area of an extracted sample; the intelligent identification method has the highest identification rate, as high as 100.0% and higher than the PLSDA determination results of single data; and the intelligent identification method has a blind sample identification rate of 100%, so the method has good application prospects and is applicable as a technical identification method for tracing the producing area of the Wuyi rock tea.

The invention relates to a Wuyi rock tea production place identification method based on partial least square discrimination, and belongs to the technical field of geographical indication product authenticity recognition. In the prior art, the single detection data cannot represent all production place traceability key information, the data matching problem exists when different types of the detection data are subjected to combined use in the metrology method, and other problems exist. A purpose of the present invention is to solve the problems in the prior art. According to the present invention, based on the partial least square discrimination model, the near infrared characteristic spectrum data, the stable isotope data, the trace element data and the catechin data of the rock teas (produced inside and outside the geographical indication production place) from different production places are integrally fused, the analysis model is established, the sample is extracted, and the rock tea production place is objectively and accurately determined by using the model, wherein the recognition rate is highest, achieves 100.0%, and is higher than the PLSDA determining result of the single data, and the recognition rate of the blind sample achieves 100%; and the method has the good application prospect, and can be used as the Wuyi rock tea production place traceability recognition technical method.

The present invention relates to systems and methods for improving a sort plan. According to one embodiment, several groups are formed where each group contains articles having an identifier of a hierarchical structure. In certain embodiments, the identifier may include a geographical indication, such as a postal or ZIP code. Further aspects relate to systems and methods for conducting sort plan optimization where at least some prior data is known or otherwise obtainable. In one embodiment, data relating to the quantity of groups within the sort plan, the quantity of articles associated with each identifier, and / or the quantity of articles within each group may be estimated or known. In certain embodiments, such data may be utilized to assign articles to specific bins, including any available bin, and then optimize the sort plan by selecting at least one bin for improvement.

The invention provides a parking timing method which is used in a parking place. The parking timing method adopts an information hierarchical structure which comprises an environmental perception layer, a geographical indication layer, an object layer, a feature layer, a semantic layer, and a decision layer. The parking timing method comprises the following steps: acquiring monitoring images and the shooting time corresponding to each frame of monitoring image, and storing the monitoring images and the shooting time corresponding to each frame of monitoring image in the environmental perception layer; using a deep convolutional neural network calculation unit arranged in field monitoring equipment to process the monitoring images so as to identify the license plate number of each incoming vehicle and the license plate number of each outgoing vehicle, and storing the license plate number of each incoming vehicle and the license plate number of each outgoing vehicle in the feature layer; comparing the license plate number of each outgoing vehicle with the license plate number of each incoming vehicle; and calculating the duration of stay of a corresponding vehicle according to the shooting time of the monitoring images corresponding to the license plate number of an incoming vehicle and the license plate number of an outgoing vehicle which are consistent, and storing the duration of stay in the semantic layer. The whole parking and timing process can be managed intelligently, and manual operation can be reduced. The invention further discloses a parking timing device.

The invention discloses a road monitoring method which is realized by adopting an information hierarchical structure; and the information hierarchical structure comprises an environment perception layer, a geographical indication layer, an object layer and a semantic layer. The road monitoring method comprises the following steps of acquiring monitoring images and photographing locations, and storing the monitoring images and the photographing locations at the environment perception layer; extracting lane images from the monitoring images, and storing the lane images at the geographical indication layer; judging whether the foreign matter throwing condition exists or not according to the monitoring images; if exist, extracting foreign matter region images from the monitoring images, and storing the foreign matter region images at the object layer; comprehensively treating the foreign matter region images and the lane images to acquire the condition that foreign matters cover a pavement, and storing the condition at the semantic layer; and generating prompt information. According to the road monitoring method, by processing and recognizing the monitoring images, whether the foreign matter throwing condition occurs or not can be analyzed, and early warning or advice information is generated, so that related personnel is liable to know the foreign matter throwing condition as soon as possible and treats the condition as soon as possible. The invention also discloses a road monitoring device.

The invention discloses a method for distinguishing geographical indications of rice. On the basis of an ICP-MS (inductively coupled plasma mass spectrometry) process for simultaneously determining 24 mineral elements, stoichiometry is combined by using the mineral element contents as the indexes to establish a model for distinguishing the producing area of rice, thereby achieving the goal of distinguishing the producing area. The method is simple to operate, and has the advantages of stable mineral element fingerprint characteristics and multiple indexes for tracing detection, thereby enhancing the distinguishing precision.

The invention belongs to the technical fields of safety and quality detection of agricultural products, and relates to a method for identifying place of origin of honeysuckle flower based on a mineral element fingerprint technique. The method comprises the following steps of pretreating a honeysuckle flower sample which is randomly selected from a main production area of the honeysuckle flower, measuring the content of mineral element in the pretreated honeysuckle flower sample, analyzing the mineral elements with obvious judging function on the main production area of the honeysuckle flower, and establishing a judging model; according to the judging mobile, determining a geographical indication of the honeysuckle flower, wherein at the significance level of 0.05, the mineral elements with obvious judging function on the main production area of the honeysuckle flower comprise Cd, Cr, Hg, Se, Co, Ni, Sr, Fe and Cu. The method has the advantages that a honeysuckle flower place of origin tracing model is established according to the nine types of mineral elements, the place of origin of the honeysuckle flower can be quickly traced, and the technical support is provided for the protection of geological indication products and characteristic products.

The invention discloses a method for identifying the specificity of Biluochun tea from Tungting Mountains, Soochow. The method disclosed by the invention comprises the following steps: using tea which is prepared from native populations in a protective range meeting the national standard GB / T 18957-2008F geographical indication tea provision as a standard substance sample and extracting the fingerprint of the tea as a comparison reference group; respectively extracting a specificity liquid chromatogram fingerprint and a specificity gas chromatogram fingerprint of a tea sample to be identified and comparing by utilizing fingerprint computing software; based on the identification reference that the similarity between the liquid chromatogram fingerprint and the standard substance sample fingerprint and the similarity between the gas chromatogram fingerprint and the standard substance sample fingerprint are both higher than 80%, qualitatively and quantitatively identifying the genuineness and quality of the tea sample. By the implementation of the method, the practical restriction that the fake Biluochun tea from Tungting Mountains are hardly identified by the traditional identification method based on perception indexes, rationalization indexes, safety indexes and the like can be broken through, and the genuineness of the Biluochun tea from Tungting Mountains can be effectively and accurately identified, therefore the invention provides a solid guarantee for protecting geographical indication tea.

The invention relates to a combined detection method used for identification of the producing area of Wuyi rock tea, i.e., a method for identifying the producing area of Wuyi rock tea through a combination of near infrared spectroscopy, stable isotope mass spectrometry and electronic tongue detection, belonging to the technical field of identification of the authenticity of products of geographical indication. The objective of the invention is to overcome the problems that single detection data cannot represent all the key information in tracing of a producing area and that data matching is hard to realize for combined usage of detection data of different types in metrological method and other problems in the prior art. According to the invention, near-infrared characteristic spectroscopic data, stable isotope mass spectrometric data and electronic tongue data of rock tea from different producing areas are fused together for establishment of a least squares support vector machine (LS-SVM) analysis model on the basis of a LS-SVM model; the method has the highest identification rate, as high as 100.0% and much higher than LS-SVM results composed of single data; and the method has a blind sample identification rate of 100.0%, so the method has good application prospects and is applicable as a technical identification method for tracing the producing area of the Wuyi rock tea.

The invention relates to a visualization method suitable for personal geographical indication data, and belongs to the technical field of data visualization processing. When the personal geographical indication data is processed, a background map is removed, points in a dense region are stretched and points in a sparse region are compressed so as to obtain an indication topological graph of which all geographical positions are displayed on one graph on a premise that orientation orthogonality is kept constant. Through the above process, the personal geographical indication data can be simply displayed, deformed geographical points still keep original relative position relationship, and finally, all position points can be displayed in the same graph. When the invention is compared with a text list and a common map, the search efficiency of the invention is superior to the search efficiency of the common map and is superior to the search efficiency of the text list when the amount of the personal geographical indication data is large.

The invention relates to a method for identifying specific geographical indications of a Wuyi rock tea and belongs to the technical field of authenticity recognition of geographical indication products. The method solves the problem that single detection data cannot represent all the key information of places of origin and different types of detection data have poor matching ability to data used in the metrological method. The method comprises fusing stable isotope data and trace element and catechin data of rock teas in different places of origin based on a neural network ELM model, buildingan analysis model, extracting a sample, and objectively and accurately determining places of origin of rock teas through the model, wherein the model built by three fused data has the highest recognition rate of 100.0% much higher than the ELM results of single data and the blind sample recognition rate of 100%. The method has a good application prospect and can be used as the Wuyi rock tea originidentifying technology.

The present invention discloses a construction method and applications of a Shanxi mature vinegar liquid-phase fingerprint, and relates to the technical field of fingerprint construction. The construction method comprises: (1) taking 1 mL of Shanxi mature vinegar, and filtering by using a 0.22 [mu]m micro-pore filtration membrane for spare; and (2) sucking the filtered Shanxi mature vinegar, and determining through a high-pressure liquid chromatograph to obtain the chemical fingerprint. According to the present invention, the sample pre-treatment is simple and easy, the chemical components and the quality characteristics of the Shanxi mature vinegar can be completely reflected, the Shanxi mature vinegar liquid-phase fingerprint can be used for the quality control of the Shanxi mature vinegar and can further provide technical support of the protection of the Shanxi mature vinegar having the origin production region and the geographical indication.

The invention discloses a road monitoring method. The road monitoring method is achieved by adopting an information hierarchy structure, and the information hierarchy structure comprises an environmental perception layer, a geographical indication layer, an object layer, a feature layer, a semantic layer and a decision making layer. The road monitoring method comprises the steps that a monitored image and a shooting site are acquired and stored in the environmental perception layer; whether a flood situation exists in the monitored image or not is judged; if yes, a flooding area image and a vehicle area image are extracted from the monitored image and stored in the object layer; the flooding area image and the vehicle area image are comprehensively processed to acquire flood situation parameters and vehicle information, and the flood situation parameters and the vehicle information are stored in the feature layer; a conclusion on the semantic level is generated according to site information, the flood situation parameters and the vehicle information; suggestion information is generated according to the conclusion. According to the method, whether the flood situation is generated on a road or not can be analyzed by processing and recognizing the monitored image, the image is processed and analyzed to obtain the flood situation parameters, and then the suggestion information is generated to be reported to people concerned. The invention further discloses a road monitoring device.

The invention provides a navigation indication product navigation method, an information acquisition method and a navigation system. According to the geographical indication product navigation method,the location information of a user and the origin location information of a geographical indication product in a preset range of the location information are obtained; multimedia information of the geographical indication product is obtained from a geographical indication product database of a server according to a distance between the location information and the original location of the geographical indication product; and the multimedia information of the geographical indication product is played. According to the geographical indication product navigation method and the information acquisition method, a function of carrying out displaying, querying and voice introduction on geographical indication product information is provided for users on electronic maps, so that the users can conveniently and rapidly know the geographical indication product information in time, thereby increasing the trip joy of the users and improving the satisfaction of the users.

The invention relates to a Wuyi rock tea production place identification method through combination of electronic tongue and a chromatographic separation technology, and belongs to the technical field of geographical indication product authenticity recognition. In the prior art, the single detection data cannot represent all production place traceability key information, the data matching problem exists when different types of the detection data are subjected to combined use in the metrology method, and other problems exist. A purpose of the present invention is to solve the problems in the prior art. According to the present invention, based on the least square support vector machine discrimination model, the electronic tongue data and the chromatographic separation data (including amino acids, catechin and the like) of the rock teas (produced inside and outside the geographical indication production place) from different production places are integrally fused, the LS-SVM analysis model is established, the sample is extracted, and the rock tea production place is objectively and accurately determined by using the model, wherein the recognition rate of the model formed through the data fusion is highest, achieves 100.0%, and is higher than the LS-SVM result of the single data, and the recognition rate of the blind sample achieves 100%; and the method has the good application prospect, and can be used as the Wuyi rock tea production place traceability recognition technical method.

The invention discloses a geographical origin tracing identification method for geographical indication mandarin fishes. The method comprises the following steps: firstly preparing to-be-detected mandarin fish muscle solution, determining contents of seven mineral elements, namely Ca, Mg, Ti, V, Fe, Se and Rb, in the to-be-detected mandarin fish solution by utilizing an inductively coupled plasmaemission spectrometer and an inductively coupled plasma source mass spectrometer, substituting a determination result into a mandarin fish Fisher function discrimination model, and determining a geographical origin of to-be-detected mandarin fishes by comparing the size of the mandarin fish Fisher function discrimination model. The method disclosed by the invention firstly builds the mandarin fishFisher function discrimination model for three geographical origins, namely Lianhuanhu in Heilongjiang, Qiupu in Anhui and Echeng in Hubei, accuracy is 100% when the discrimintation model is utilizedfor identifying the geographical origin of the mandarin fishes, discrimination accuracy is high, stability is good, repeatability is high, system error is small, and rapid geographical origin tracingidentification on the geographical indication mandarin fishes from different geographical origins is realized, so that the method disclosed by the invention has better practical guiding significanceand extensive popularization and application values.

The invention relates to a Wuyi rock tea production place deep studying system based on five-hiding layer, and belongs to the technical field of geographical indication product authenticity recognition. In the prior art, the single detection data cannot represent all production place traceability key information, the data matching problem exists when different types of the detection data are subjected to combined use in the metrology method, and other problems exist. A purpose of the present invention is to solve the problems in the prior art. According to the present invention, based on the neural network ELM model, the near infrared characteristic spectrum data, the stable isotope data, the trace element data, the catechin data and the electronic tongue data of the rock teas (produced inside and outside the geographical indication production place) from different production places are integrally fused, the analysis model is established, the sample is extracted, and the rock tea production place is objectively and accurately determined by using the model, wherein the recognition rate is highest, achieves 100.0%, and is higher than the ELM result of the single data, and the recognition rate of the blind sample achieves 100%; and the method has the good application prospect, and can be used as the Wuyi rock tea production place traceability recognition technical method.