Wuyi rock tea origin identification method combining near infrared test and stable isotope test
A stable isotope, near-infrared technology, applied in the field of authenticity identification of geographical indication products, can solve the problem of unable to represent the origin of traceability and other problems
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Embodiment 1
[0076] A. Collect rock tea samples from different origins
[0077] 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 of Village, Wufu, Langu, Xinfeng Street, Yangzhuang, Xingtian, Xiamei, and Wutun, and 3 sampling points were randomly selected in each administrative area (in the order of A, B, C marked), a total of 33 sampling points, the sampling range basically covers the main production areas, each sampling point took 15 samples (marked with A-1, A-2...A-15), and obtained 495 geographical Wuyi rock tea samples in the protected area of the logo, and other counties and cities in Fujian Province (Jianyang, Jianou, Zhangzhou, Quanzhou, Songxi, Zhe...
Embodiment 2
[0135] Blind sample detection: The blind sample supervision team purchases rock tea samples from Wuyi rock tea farmers, monitors the steps of drying, greening, and finishing to ensure the origin of the rock tea samples. The above samples are used as geographical indications in the blind samples. Samples in the region; rock tea was purchased from Jianyang, Jianou, Wuyuan and other places as samples outside the geographical indication production area in the blind sample. The above blind sample and the modeling rock tea sample came from different manufacturers. Analyzing and testing personnel failed to know the origin attribute of the blind sample to be tested in advance, randomly selected several copies, tested, and then judged the origin attribute of the blind sample according to the method of the present invention, and checked with the blind sample supervision team to determine the recognition rate of the blind sample .
[0136] 20, 60, and 100 blind samples were respectively ...
Embodiment 3
[0138] Adopt the modeling method identical with embodiment 1, data segmentation uses Kenstone segmentation procedure, with Monte Carlo interactive verification, set up partial least squares (PLSDA), neural network ELM and least squares support vector machine (LS-SVM) respectively For the model, the near-infrared data remains unchanged, and the stable isotopes are spliced into the near-infrared data according to hydrogen, oxygen, nitrogen, carbon, and strontium. The model recognition rates are 97.3%, 90.7%, and 82.3%, respectively.
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