Research On Identification For Origin Of Longjing Tea Based On Multi-source Information Fusion

With the research object of Longjing tea, this dissertation will apply the nearinfrared spectrum technology and two-dimensional bar code mode methods to studythe true and false identification, quality and interior ingredients for Xihu Longjing‘tea.The following are main results:1. Firstly, this dissertation compares effects of two NIR technologies (Fouriertransform and Fabry interference) on true and false identification for Xihu Longjing‘tea. On this basis, the CARS algorithm is used for different spectrometers to optimizethe spectrum identification module, and select key variables (15and7) for the two NIRspectrometers to identify true and false Longjing tea, which indicates the infraredspectroscopic analysis technology can be used to identify true and false Longjing teafast.2. In order to develop portable NIRS to identify true and false Longjing tea fast,this thesis selects the NIR on10526cm-1-6060cm-1band in Fourier transformspectrograph and applies PLS-DA to establish module and analyze, the result indicatesthe above band can distinguish Xihu Longjing‘tea and Zhejiang Longjing tea betterand be the band to identify true and false Xihu Longjing‘tea.3. On the basis of the above band selection, this dissertation designs anddevelops an identification device to identify true and false Xihu Longjing‘tea, whichcombines advantages of NIR technology and two-dimensional bar code and appliesthe concept of consistent object and code (object refers to Longjing tea and code refersto two-dimensional bar code) to identify true and false Xihu Longjing‘tea. Thisdesign development firstly starts with data storage demands of commodity label,selection of NIR module and man-machine interaction demands. Through comparisonand demonstration, due to low cost, fast reading and good man-machine interaction,the two-dimensional bar code technology can be used to store basic information ofcommodities and encryption information to identify Xihu Longjing‘tea, therefore,this dissertation selects such technology to be the commodity label of Xihu Longjing‘tea and QR coding as the format of two-dimensional bar code. However, according toresults of pre-evaluation for spectral range necessary to identify true and false XihuLongjing‘tea, the super-miniature near infrared spectrometer designed based on linearand tunable optical filter is selected to acquire module which is powered only withUSB data and do not exceed60g on single weight. Finally, in order to achieve better man-machine interaction and higher development efficiency, C#language under NETframework of Microsoft Corporation is used to develop system, design and develop aset of two-dimensional bar code storage plan written in spectral information of XihuLongjing‘tea, which can prevent the lawbreaker to steal the embedded modulealgorithm in identification device to fast identify true and false Xihu Longjing‘teathrough converse cracking. The instrument this dissertation researched and developedhas strengthened the identification technology and can provide basis anddemonstration for sources of quality safety of other agricultural products.4. In order to achieve lossless packing, and check the authenticity of XihuLongjing‘tea, an acquisition method of Longjing tea spectrum via single ziplock bagthin film is proposed and a packing bag is specially designed.5. In order further to reveal the mechanism, conducts wet chemical measurementon the main indicators of Longjing tea’s quality and applies Fourier transformspectrometer with high precision to predict the ingredient content of Longjing teasample under pre-handling conditions of no smash and grind. Firstly, the spectralpretreatment of scattering adjustment is implemented for achieved Longjing tea, andeffects of partial least squares regression model for original spectrum, first derivativespectrum and second derivative spectrum are compared on smooth treatmentconditions of different counts (3,5,7,9). On this basis, the CARS algorithm is appliedfor spectrum with optimal retreatment plan to respectively find out key modelingvariables related with each ingredient of Longjing tea in order to further improve theprecision of module. The last is to find out key variables for near infrared analysismodeling of Tea Polyphenols, caffeine, amino acid, and EGCG The number ofmodeling variables sharply reduces from4401to74,101,101and87and themodeling calculation speed is greatly improved, which can satisfy requirement ofonline and fast test for quality of Longjing tea.