Study On Pathogenetic Process Monitoring And Rapid Detection Methods Of Pear Black Spot Disease Based On Spectroscopic And Spectral Imaging Technologies

Korla pear fruit is fresh,juicy,sweet and delicious.It is favored by consumers and exported to many countries and regions,and sold throughout the year;however,it is highly susceptible to multiple diseases during storage and sales.Among them,black spot disease is one of the most serious storage diseases,which is caused by Alternaria alternata?A.alternata?.The occurrence of black spot disease reduces the quality and commercial value of pear fruit,affecting its sales,and ultimately causing serious economic losses.Thus,this work is focused on the research of dynamic monitoring and rapid detection of postharvest diseases of pear fruit,which are of great significance for the prevention and control of black spot diseases and for to improve the quality of commercially available fruit.Herein,research was conducted on Korla pear fruit from the following aspects.Firstly,hyperspectral imaging?HSI?technology was implemented to monitor the pathogenetic process of black spot disease in pear fruit and detect the early onset of the disease.Secondly,subtle change in chemical composition and structure of fruit cell wall during the pathogenetic process of disease was studied by confocal Raman microspectroscopy?CRM?and Raman imaging techniques.Thirdly,surface-enhanced Raman spectroscopy?SERS?was used to precisely detect alternariol produced by A.alternata infection and the change of polyphenol oxidase?PPO?activity in infected fruit during the pathogenetic process of the disease.Finally,A.alternata content in pear fruit was detected based on the SERS technique.The main research objectives and results are listed as follows.?1?Pathogenetic process monitoring and early detection of pear black spot disease caused by A.alternata using HSI technique-The hyperspectral images of fresh and infected fruits were obtained by HSI system.Then spectral angle mapper?SAM?were creatively performed to segment the infected area from sound tissue,and to monitor the pathogenetic process of the black spot disease.Finally,principal component analysis?PCA?was conducted to the feasibility of identifying fruit at different stages of disease based on HSI technique.Moreover,partial least squares discriminant analysis?PLSDA?,k-nearest neighbor?KNN?,and support vector machine?SVM?models were developed to detect the onset of black spot disease.The results indicated that SAM can be successfully applied to the identification of the infected areas and to monitor the pathogenetic process of the disease on the surface of pear fruit.The PLSDA,KNN,and SVM models can be used to categorize the fruit in different infection periods;however,their classification accuracy varies greatly.Among these three models,SVM performed with the highest accuracy of 97.50%and 96.56%by using the spectra for the entire wavelength range and the optimal wavelengths,respectively,indicating the proposed method was suitable for disease early detection.?2?Microscopic determination of cell wall chemical composition and structure changes of pear fruit during pathogenetic process of black spot disease by Raman chemical imaging-Firstly,Raman spectra of the cell wall of both fresh and infected fruits were collected using CRM,and then Raman spectra of standard and the related literature reports were used to determine the assignment of Raman peak of pear fruit cell wall,and the changes in the Raman intensity of cellulose and pectin in the pathogenetic process were calculated.Secondly,PCA was used to classify the cell wall Raman spectra of infected fruit at different stages of disease.Finally,the chemical images of the main components of cell wall including polysaccharide,cellulose and pectin were obtained by Raman chemical imaging,which were used as a visual aid to observe the subtle changes of the main components and structure of cell wall during the pathogenetic process.The results demonstrated significant changes in the signal intensity of the main components of cell wall in the pathogenetic process.After 2 and 8 days of infection,the intensities of cellulose were decreased by 19.11%and 58.50%,and pectin were decreased by19.20%and 58.67%,respectively.In addition,the images of fresh and infected fruits were compared,indicating that the disease caused the alterations in morphological structure and chemical composition of the cell wall in a time-dependent manner.?3?Another objective is to detect the alternariol produced by A.alternata in pear fruit by SERS with pyridine-modified silver nanoparticles?AgNPs?.Firstly,the AgNPs substrate was prepared and modified by pyridine to circumvent weak affinity of the alternariol molecules to the silver surface and to improve the sensitivity of detection.Secondly,the quantitative relationship between the SERS intensity and concentration of the alternariol standard solution was established.The feasibility of this method for the detection of alternariol in pear fruit was verified by the spiked recovery experiment.Thirdly,the SERS method was used to detect the alternariol content in three different kinds of pear fruit samples including fresh fruit,artificially infected fruit and naturally occurring fruit.The reliability of SERS method for real sample detection was verified by HPLC analysis.The results indicated that the AgNPs modified by pyridine solved the problem of weak adsorption capacity of alternariol on the surface of AgNPs,which can improve the sensitivity of detection and reduce the limit of detection?LOD?.SERS can be used for the detection of alternariol standard solution.The relationship between the SERS intensity and the concentration of the alternariol solution was I=1453.7 log c-553.4,within a coefficient of determination of 0.9926,a linear range of 3.16-316.0?g/L,and a LOD of 1.30?g/L?below the LOD of HPLC?.In addition,the SERS method was successfully applied for the detection of alternariol in pear fruit,and the reliability of the results was verified by the traditional HPLC method.The results of these two methods were consistent,and the relative standard deviation was less than 10%.?4?Detection of PPO activity changes in pear fruit during the pathogenetic process of black spot disease by SERS technique-Firstly,a AgNPs substrate was synthesized and used to determine the optimal catechol concentration range for PPO activity determination.Secondly,the SERS signal of the reaction medium at different reaction stages was collected,and the relationship between the reduction in SERS intensity??I?and PPO activity?E_c?was established.Thirdly,the PPO activity in pear fruit samples at different disease stages was determined based on the established linear equation and the results were compared with those obtained by the colorimetric method.Finally,the change rule of PPO activity in pear fruit during the pathogenetic process of black spot disease was determined.The results showed that the optimal catechol concentration range for PPO activity determination was 1.0-9.0 mM.When a purified PPO solution was analyzed,the reduction in SERS intensity??I?was linear to PPO activity?E_c?with a wide range of 500-50000 U/L,and a linear regression equation of log?I/?t=0.6223 log E_c+0.8072,with a coefficient of determination of 0.9689 and a LOD of 224.65 U/L,was obtained.In addition,SERS can be used to determine the PPO activity of pear fruit and the stability of the test results is better than those obtained by the colorimetric method,and the PPO activity changes can be sensitively determined throughout the pathogenetic process of black spot disease.The PPO activity of the infected pear fruit can reach the maximum value on the2^nd day after inoculation;oxalic acid treatment can enhance the PPO activity of the infected fruit and prolong the time for PPO activity to reach the maximum value.?5?Detection of A.alternata in pear fruit using SERS based silver nanodots array-Firstly,a silver nanodots array substrate was prepared and the particle size and thickness of the substrate were optimized to achieve the desired SERS enhancement and reproducibility.Secondly,the SERS signals of different concentrations of A.alternata in water and pear fruit juice were determined based on SERS method,and the relationship between SERS signal intensity and A.alternata concentration was established to detect A.alternata in pear fruit.Thirdly,different concentrations of A.alternata was visually achieved by Raman imaging.The results indicated that the SERS method can be used for the rapid detection of A.alternata suspension,and it can be described by the fitting curve equation?y=-18.84 x²+665.38 x-1813.12?with the coefficient of determination of 0.9511,detection range of 1.0×10³-1.0×10⁷ cfu/mL,and the LOD of 1.0×10³ cfu/mL.The lowest concentration of A.alternata suspension detected by Raman imaging was 1.0×10⁴ cfu/mL within the suitable detection range of 1.0×10⁴-1.0×10⁷cfu/mL.The method was good with the detection of artificially polluted pear fruit juice.The fitting curve equation between the SERS intensity and A.alternata concentration in juice was y=-29.27 x²+511.47 x-1435.18,the coefficient of determination was 0.9852,and the LOD was 10⁴ cfu/mL.To conclude,this work has monitored the pathogenetic process and rapid detection methods of pear black spot disease based on spectroscopic and spectral imaging technologies,which could realize the dynamic monitoring of postharvest diseases of pear fruit and the rapid detection of physiological and biochemical indexes during the pathogenetic process.The results of this thesis provide a theoretical basis for detection of pathogenic infection and fruit pathogenesis research.It has practical significance and aims to function as a guide for the prevention and control of postharvest diseases pertaining to pear fruit and consequently improving the quality of commercially available fruit.At the same time,it plays an important role in promoting industrial development of the Korla pear fruit.