Identification method for producing area of plant based on multiple detection technologies
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A detection technology and technology of origin, applied in the field of authenticity identification of geographical indication products, which can solve the problem that detection data cannot represent the key information of origin traceability.
Inactive Publication Date: 2017-04-12
CHINA JILIANG UNIV
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[0011] The purpose of the present invention is to solve the problems that a single detection data cannot represent all the key information of origin traceability and the defects of traditional metrology methods, and provide a plant origin identification method based on multiple detection technologies, that is, combining near-infrared spectral data, stable Wuyi rock tea origin identification model technology method based on isotope and trace element data. This method is based on the least squares support vector machine discriminant model. The stable isotope data and trace element data are fused together to establish an analysis model, and the model is used to objectively and accurately determine the origin of rock tea after extracting samples
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Embodiment 1
[0072] A. Collect rock tea samples from different origins
[0073] 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, Xingcun, Xingtian, Xinfeng, Wuyi Rock Tea Geographical Indication Protection Area Samples were collected in 11 administrative areas including Street Street, Chongan Street, Shangmei, Wufu, Langu, Yangzhuang, 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 (Jianyang, Jianou,...
Embodiment 2
[0138] Adopt the modeling method identical with embodiment 1, data segmentation uses Kenstone segmentation program, uses Monte Carlo interactive verification, establishes LS-SVM, neural network ELM and partial least squares (PLSDA) discriminant model respectively, near-infrared spectrum data is not Stable isotopes and trace elements are spliced in near-infrared data according to hydrogen, oxygen, nitrogen, carbon, strontium, Cs, Cu, Ca, Rb, Sr, Ba, Mg, Mn, Ti, Cr, Co, Ni, Zn, and Cd After that, the model recognition rates were 91.3%, 83.7% and 81.2% respectively.
Embodiment 3
[0140] Adopt near-infrared identical with embodiment 1 and through the stable isotope of SVM-RFE process, trace element data, set up LS-SVM, neural network ELM and partial least squares (PLSDA) discriminant model respectively, near-infrared spectrum data is constant, Stable isotopes and trace elements are spliced into near-infrared data according to hydrogen, oxygen, nitrogen, carbon, strontium, Cs, Cu, Ca, and Rb, and the model recognition rates are 97.8%, 87.5%, and 89.3%, respectively.
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Abstract
The invention relates to an identification method for the producing area of a plant based on multiple detection technologies. The method provided by the invention identifies the producing area of Wuyi rock tea by using a combination of near-infrared spectroscopic data, stable isotope mass spectrometric data and trace element data and belongs 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 spectroscopic data, stable isotope mass spectrometric data and trace element data are fused together for modeling analysis on the basis of a least squares support vector machine (LS-SVM) model, and a highest identification rate is obtained, as high as 100.0% and much higher than the determination results of LS-SVM established on the basis of single data; and the identification method has a blind sample identification rate of 100%, so the method has good application prospects. The identification method is also applicable to identification of the producing areas of other plant samples like Chinese torreya and lotus root starch; and the method achieves a producing area identification rate of 99.8% or above in identification of plants except tea.
Description
[0001] (1) Technical field [0002] The present invention relates to a method for identifying the origin of plants based on various detection technologies, that is, a method for identifying the origin of plants by combining near-infrared spectroscopy, stable isotopes and trace elements. The technical field of authenticity identification of geographical indication products. [0003] (2) Background technology [0004] Geographical indication products refer to products that are produced in a specific region using raw materials from a specific region according to traditional techniques, and are named after the name of the region of origin after examination and approval in accordance with legal procedures. Geographical features of the region of origin. The quality and taste of tea are closely related to the geographical conditions, climatic factors, environmental factors and other factors of the place of origin. It has obvious regional characteristics and quality characteristics, a...
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