Wuyi rock tea production place identification method through combination of four detection technologies
A technology of origin and rock tea, applied in measuring devices, material analysis through optical means, instruments, etc., can solve problems such as inability to represent origin traceability
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Embodiment 1
[0083] A. Collect rock tea samples from different origins
[0084]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, Jian...
Embodiment 2
[0150] Using the same modeling data as in Example 1, the data segmentation uses the Duplex segmentation program, and uses K-fold interactive verification to establish PLSDA, neural network ELM and least squares support vector machine LS-SVM models respectively, and the near-infrared data is constant. Stable isotopes, trace elements, amino acids according to hydrogen, oxygen, nitrogen, carbon, strontium, Cs, Cu, Ca, Rb, Sr, Ba, asparagine, proline, tryptophan, phosphoethanolamine, urea, valine After splicing the near-infrared data with acid, the model recognition rates were 91.7%, 85.8%, and 82.1%, respectively.
Embodiment 3
[0152] Using the same modeling data as in Example 1, the data segmentation uses the Duplex segmentation program, and uses K-fold interactive verification to establish PLSDA, neural network ELM and least squares support vector machine LS-SVM models respectively, and the near-infrared data is constant. Stable isotopes, trace elements, and amino acids are spliced in the near-infrared data according to hydrogen, oxygen, nitrogen, carbon, strontium, Cs, Cu, Ca, Rb, Sr, Ba, asparagine, proline, tryptophan, and phosphoethanolamine After that, the recognition rates of the models were 95.9%, 86.3%, and 90.1%, respectively.
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