Wuyi rock tea production place identification method through combination of electronic tongue and chromatographic separation technology
A chromatographic separation and electronic tongue technology, which is applied in the field of identification of the origin of Wuyi rock tea, can solve the problems of being unable to represent the origin of the origin.
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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 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, 15 samples were taken from each sampling point (marked with A-1, A-2...A-15 respectively), and 495 samples were obtained Wuyi rock tea samples in the geographical indication protected area, and other counties and cities in Fujian Province except Wuyishan C...
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 . Select 20, 60, and 100 blind samples respectively, and su...
Embodiment 3
[0137] Adopt the modeling method identical with embodiment 1, data segmentation uses Kenstone segmentation program, with Monte Carlo interactive verification, establishes least squares support vector machine (LS-SVM), neural network ELM, partial least squares (PLSDA) respectively Model, electronic tongue data unchanged (ZZ, BA, BB, CA, GA, HA, JB), amino acid and catechin data according to aspartyl, proline, tryptophan, phosphoethanolamine, urea, After splicing amino acid, EGC, C, EGCG, GA, EC, ECG, and caffeine into the electronic tongue data, the model recognition rates were 91.3%, 80.9%, and 77.5%, respectively.
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