Combined detection method used for identification of producing area of Wuyi rock tea

A technology of joint detection and origin, applied in measuring devices, material analysis through optical means, instruments, etc., can solve the problem that the detection data cannot represent the traceability of the origin, and achieve the effect of avoiding insensitive loss functions and reducing computational complexity

CN106560699AInactive Publication Date: 2017-04-12CHINA JILIANG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
Publication Date
2017-04-12
Estimated Expiration
Not applicable · inactive patent

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Abstract

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.
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Description

[0001] (1) Technical field

[0002] The invention relates to a combined detection method for identifying the origin of Wuyi rock tea. The combined detection methods involved in the invention include three types of detection methods: near-infrared spectroscopy, stable isotope and electronic tongue. Combining near-infrared spectroscopy, stable isotope and electronic tongue detection data, and using least squares support vector machine to establish a method for identifying the origin of Wuyi rock tea belongs to the technical field of authenticity identification of geographical indication products.

[0003] (2) Background technology

[0004] According to the definition of GB / T 17924-2008, a geographical indication product refers to the use of raw materials produced in a specific region and produced in a specific region according to traditional techniques. The quality, characteristics or reputation are essentially determined by the geographical characteristics of the region of origin...

Examples

Embodiment 1

[0081] A. Collect rock tea samples from different origins

[0082] The national standard (GB / T 18745-2006) stipulates the scope of geographical protection of Wuyi rock tea, that is, within the administrative division of Wuyishan City, Fujian Province, the present invention is located in Wuyi Street, Chong'an Street, Shangmei, and Xingxia in the Wuyi Rock Tea Geographical Indication Protection Area. Samples were collected in 11 administrative areas including Village, Wufu, Langu, Xinfeng Street, Yangzhuang, Xingtian, Xiamei, and Wutun, and 3 sampling points were randomly selected in each administrative area (respectively A, B, C to be marked), a total of 33 sampling points, the sampling range basically covers the main production areas, and each sampling point takes 15 samples (respectively marked with A-1, A-2...A-15), and obtained 495 samples of Wuyi rock tea in geographical indication protected areas, and other counties and cities in Fujian Province except Wuyishan City (Jian...

Embodiment 2

[0133] Data segmentation adopts Kenston program, K-fold interactive verification, and PLSDA model. According to the above modeling method, the near-infrared spectrum, isotope, electronic tongue and the fusion data of the three are modeled and analyzed. The results are shown in Table 6.

[0134] Table 6: Summary of PLSDA model discrimination results

[0135]

[0136] Using the PLSDA discriminant model, the feature indicators are also complementary. The recognition rate of the three fusion data is higher than that of the single-data PLSDA discriminant model, with a recognition rate of 95.2%, but the PLSDA recognition rate is lower than that of the 100.0% recognition rate of LS- SVM discriminant model.

Embodiment 3

[0138] Data segmentation adopts Kenston program, K-fold interactive verification, and neural network ELM model. According to the above modeling method, the near-infrared spectrum, isotope, electronic tongue and the fusion data of the three are modeled and analyzed. The results are shown in Table 7.

[0139] Table 7: Summary of ELM model discrimination results

[0140]

[0141] The ELM discriminant model is used, and the feature indicators are also complementary. The recognition rate of the three fusion data is higher than that of the single data ELM discriminant model, with a recognition rate of 94.5%, but the recognition rate of ELM is lower than that of LS- SVM discriminant model.