The Effect Of Graphene Based Materials Onthe Electrochemical Fingerprint Of Plants

The identification and discernment of flora serve as theoretical guidance in the fields of botanical and medicinal plant resources,exhibiting immense practical utility in drug verification,food safety,and economic production regulation.Throughout tens of thousands of years of evolution,a plethora of plant species have developed distinct characteristics,thereby enabling species classification via observational traits.However,within closely related species,these traits often exhibit minimal divergence,rendering conventional taxonomical methodologies,reliant on these differences,inadequate for swift identification and classification.Phytochemical taxonomy,predicated on the analysis of chemical constituents within plant tissues,is employed to ascertain the phylogenetic relationships between plant populations.In this context,electrochemical fingerprinting of plants,a technique predicated on the detection of electrochemically active substances within plant tissues,aids in the recognition and classification of plants.However,its low sensitivity presents a significant bottleneck,necessitating the selection of modified electrodes to enhance its detection performance.In this paper,based on the influence of graphene material modified electrode on electrode performance and the application of electroanalytical chemistry to the recognition of Labiatae plants,two major aspects were discussed.The main research content is as follows:(1)Electrochemical sensing of plants based on graphene modified electrode was studied.Under different conditions,the electrochemical fingerprints of plants measured by the electrodes modified with five kinds of materials including graphene oxide,aminofossil graphene and graphene with different sheet diameters and thickness were compared and analyzed,including whether there was a catalytic reaction and the impact on the original characteristic peak.Observe the modified electrode performance and detection performance,and select the graphene material with the best comprehensive performance.(2)The effect of graphene modified electrode on the electrochemical fingerprints of labiatae plants was analyzed.Using glassy carbon electrode modified with or without graphene material to measure 36 species of Labiatae plants.The electrochemical fingerprint was used for detection.The volt-ampere diagram,scatter diagram,density diagram and thermal diagram are drawn according to the obtained data.Comparing the two,the results showed that the fingerprint characteristics detected by the modified electrode were more obvious,and according to the clustering and PCA analysis,it was found that it was more accurate to show the affinity between 36 species of Labiatae plants.(3)To establish a method for intelligent identification of electrochemical fingerprints of plants.The traditional convolution neural network method is used to intelligently recognize the electrochemical fingerprints of 36 species of Labiatae plants.When the number of training is 60,the recognition accuracy is 82.222%.The results show that the construction of convolution neural network has a very important application prospect for the electrochemical fingerprint of plants.