Wuyi rock tea production place identification method based on partial least square discrimination
A technology of partial least squares and place of origin, which is applied in the field of authenticity identification of geographical indication products, and can solve problems such as being unable to represent the place of origin.
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Embodiment 1
[0082] A. Collect rock tea samples from different origins
[0083] 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 marked), a total of 33 sampling points, the sampling range basically covers the main production areas, each sampling point sampling 15 copies (respectively marked with A-1, A-2...A-15), obtained 495 Wuyi rock tea samples from the Geographical Indication Protection Area, and other counties and cities in Fujian Province except Wuyishan City (Jianyang, Jia...
Embodiment 2
[0152] Adopt the modeling method identical with embodiment 1, data segmentation uses Duplex segmentation program, with Monte Carlo interactive verification, respectively establishes PLSDA, neural network ELM and least squares support vector machine LS-SVM model, near-infrared data is constant, Stable isotopes, trace elements and catechins were spliced in the near-infrared The model recognition rates were 92.3%, 80.5%, and 88.9% respectively.
Embodiment 3
[0154] Adopt the modeling method identical with embodiment 1, data segmentation uses Duplex segmentation program, with Monte Carlo interactive verification, respectively establishes PLSDA, neural network ELM and least squares support vector machine LS-SVM model, near-infrared data is constant, Stable isotopes, trace elements, and catechins were spliced in the near-infrared data according to hydrogen, oxygen, nitrogen, carbon, strontium, Cs, Cu, Ca, Rb, Sr, Ba, EGC, C, EGCG, GA, and EC, respectively. The model recognition rates were 94.5%, 83.2%, and 89.7%, respectively.
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