Early Detection Of Korla Fragrant Pear Tree Canker Disease Based On SERS

During the growth of Korla fragrant pear tree,due to the problems of freezing injury,insect bite,mechanical damage and differences in individual resistance,the tree is very vulnerable to various pathogens,and tree rot is one of them.If the disease is mild,it will affect the growth of the tree,and if it is severe,it will lead to the death of the tree.Rot disease is highly infectious,and it is easy to infect between trees,resulting in the destruction of pear orchards.Therefore,the study of a detection technology for the disease degree of tree rot disease has certain practical significance.It can control the disease before the early symptoms of rot disease,reduce the losses of fruit farmers and promote the export of fragrant pear.Compared with hyperspectral imaging detection,mid infrared spectroscopy detection and chlorophyll fluorescence imaging detection,surface enhanced Raman spectroscopy（SERS）has the characteristics of less sample pretreatment,high sensitivity,short detection time and small amount of data.Therefore,SERS is widely used in plant scientific research,agricultural products detection and other fields.In this paper,the spectrum law of early disease of infected rotten tree segments based on SERS technology is studied.The main research contents are as follows:（1）Preparation,optimization and characterization of gold nanoparticle sol and silver nanoparticle sol.Gold and silver nanoparticle sol was prepared by chemical reduction method with chloroauric acid and silver nitrate as raw materials and trisodium citrate as redox agent.Through the orthogonal test of four factors and three levels,the preparation conditions of gold and silver nanoparticle sol were optimized,characterized by UV-Vis spectrophotometer and transmission electron microscope,and the optimal preparation conditions of gold and silver nanoparticle sol were obtained.The optimal preparation scheme of gold nanoparticle sol:2ml trisodium citrate was added to chloroauric acid solution,the stirring speed was 400R/min,the heating temperature was 100℃,and the reaction time was 30min;The optimal preparation scheme of silver nanoparticle sol:add 4ml trisodium citrate into silver nitrate solution,the stirring speed is 800r/min,the heating temperature is 250℃,and the reaction time is 30min.（2）Raman spectroscopy of spore suspensions.Common Raman（Raman spectroscopy,RS）and SERS spectroscopy data were collected by DXR Smart Raman spectrometer,and the enhancement effect of ordinary Raman and gold nanoparticle solvent was not obvious and no Raman peak with silver nanoparticle solvent as the surface at245cm^-1,325cm^-1,954cm^-1,1325cm^-1.（3）Raman Spectroscopic Study on the pathogen of rot disease in Korla Fragrant Pear Tree section.The bacterial cake containing the pathogen of rot disease was inoculated on the Korla Fragrant Pear Tree section with bark removed,and the growth of the pathogen was observed.The Raman spectrum data of Korla Fragrant Pear Tree section and spore suspension with surface enhanced substrate at different infection time were collected by DXR smart Raman spectrometer.The enhancement effect of spore suspension was not obvious by ordinary Raman and gold nanoparticle sol,and there was no obvious Raman peak;The silver nanoparticle sol was used as the surface enhanced substrate to detect the diseased area of the infected tree segment.The Raman peaks were 243cm^-1,340cm^-1and 478cm^-1.The corresponding substances were glucose,etc.,730cm^-1,ribonucleotide and chlorophyll,1125cm^-1,cellulose,1179cm^-1,aromatic amino acids in protein and 1220cm^-1,respectively,The corresponding substances of 1550cm^-1are ribonucleotides such as cytosine and phenylalanine;The silver nanoparticle sol was used as the surface enhanced substrate to detect the area around the diseased tree segment.The Raman peaks were 635cm^-1,the corresponding substance was ribose,805cm^-1was lysine,1021cm^-1was carbohydrates and 1124cm^-1was cellulose.（4）Establishment of disease degree discrimination model of infected rotten tree section based on SERS.The disease degree is divided into health,pre infection,mid infection and post infection.After savitzky Golay convolution smoothing and first derivative preprocessing for the spectral data of Korla Fragrant Pear Tree section infected with rot disease,the support vector machine（SVM）discrimination model is established for the ordinary Raman spectral data,the spectral data with gold nanoparticle solution and the spectral data with silver nanoparticle sol,the results show that he optimal discrimination model of ordinary Raman,gold nanoparticle sol enhancement and silver nanoparticle sol is the discrimination model of silver nanoparticle sol enhancement,and the accuracy of silver nanoparticle sol spectrum discrimination model is100%in the early stage,100%in the middle stage and 100%in the later stage.