CN105929068A - Method for diagnosing plant gray mold by analyzing metabolome of infected plant - Google Patents
Method for diagnosing plant gray mold by analyzing metabolome of infected plant Download PDFInfo
- Publication number
- CN105929068A CN105929068A CN201610260197.1A CN201610260197A CN105929068A CN 105929068 A CN105929068 A CN 105929068A CN 201610260197 A CN201610260197 A CN 201610260197A CN 105929068 A CN105929068 A CN 105929068A
- Authority
- CN
- China
- Prior art keywords
- sample
- plant
- metabolism group
- detection
- derivatization
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/04—Preparation or injection of sample to be analysed
- G01N30/06—Preparation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N2030/022—Column chromatography characterised by the kind of separation mechanism
- G01N2030/025—Gas chromatography
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
The invention provides a method for diagnosing plant gray mold by analyzing metabolome of an infected plant. The method disclosed in the invention diagnoses plant gray mold based on gas chromatographic-mass spectrometric (GC-MS) analysis and partial least squares discriminant analysis (PLS-DA) of the metabolome of the infected plant. The method comprises the following steps: collection of a sample; inactivation with liquid nitrogen; low temperature preservation; extraction of the metabolome; drying; silylation derivatization; GC-MS detection; establishment and detection of a PLS-DA model; etc. With the method provided by the invention, good-reproductivity results of the metabolome of plants infected by pathogens can be obtained; the established PLS-DA model can accurately identify grey mold infected samples without explicit symptoms and precisely identify samples infected by Botrytis cinerea in samples infected by other pathogens and healthy samples. The method is sensitive and accurate, provides an effective method for early diagnosis of gray mold of transplanted seedlings and colonized plants and facilitates early prevention and treatment of field gray mold.
Description
Technical field
The invention provides a kind of method analyzing disease plant metabolism group diagnosis of plant gray mold, relate to metabolism group, botany, microbiology and instrument analysis technology field.
Background technology
Gray mold is one of important disease during vegetable or flower produces, and it often results in a large amount of decayed fruits in postharvest fruit and vegetable and storage and transport process, causes serious financial consequences.Its pathogen the pathogen of Botrytis cinerea host range is wide, can infect and include that Solanaceae, Cucurbitaceae, Rosaceae, pulse family, Vitaceae etc. more than 200 plant plant.After ash arrhizus bacteria infects the plants such as Fructus Fragariae Ananssae, it will usually entering the incubation period of a period of time, on blade, symptom is inconspicuous, and can propagate with shoot transplanting equipment, this brings puzzlement to field diseases diagnosis, produces to field and brings heavy losses.
Metabolism group investigative technique is to disclose plant metabolism group and the specific variations that produced by environmental stimuli provides effective means comprehensively in recent years, plays an important role in host's interaction research in cause of disease.Plant has more than the metabolite of 200,000 kinds, has plenty of primary metabolite necessary to maintenance plant vital movement and growth promoter, have plenty of the secondary metabolites in close relations with plant stress-resistance utilizing primary metabolite to generate.Metabolite is the end product of cell regulate and control process, and its kind and changes of contents are considered biosystem to gene or the final response of environmental change.Study the Volatile Metabolites such as mannitol using HPLC-MS to detect the release of susceptible rye grass, use GC-MS research discovery potato tubers to be infected by Rhizoma Solani tuber osi black shin subspecies (Erwinia carotovora subsp.atroseptica) and specifically produce vinyl acetate, infected by fusarium sambucinum (Fusarium sambucinum) and bicycloheptadiene and styrene can be produced.The escaping gas component analysis of sense ash arrhizus bacteria Fructus Fragariae Ananssae finds, it is closely related that different valeric aldehyde, cis-4-decenal, 2-methyl-1-butene alcohol, isobutanol, 1-octene-3-ketone and 1-OCOL and ash arrhizus bacteria infect strawberry.
After plant is by pathogen infection, there is notable change in the metabolite in plant, cell signaling pathway changes at first, the accumulation of the material such as salicylic acid and ethylene can occur after several hours at pathogen infection, and oxynitride, methyl jasmonic acid, cresotic acid etc. are considered as the crucial intermediary of systemic acquired resistance.Including that saccharide, organic acid, aminoacid and lipid content change then to disease-resistant relevant nascent metabolite in plant, their change makes the organ structure such as plant cell wall and root, stem and leaf adjust, thus stops the invasion of pathogen.Meanwhile, the secondary metabolites such as terpenoid closely-related with disease resistance, Polyphenols, glucosinolate also adjusts in plant, and these materials are generally closely related with toxin and signal conduction.
Use the monitoring plant this change under susceptible state of metabolism group means, the early diagnosis of plant disease is had highly important using value.In the plant interaction research with microorganism, by the detection of metabolic group under susceptible and health status, comparative analysis health plant, the similarities and differences of diseased plant two class biomaterial metabolism group, can disclose the microorganism impact on plant metabolism group, the early diagnosis for plant disease provides technical support comprehensively.At present, about metabonomic technology application in gray mold diagnoses, there is not been reported, and the metabolism group detection method of Infected with Pathogenic Fungi plant and Distinguishing diagnosis method all await determining.The invention provides a kind of method analyzing disease plant metabolism group diagnosis of plant gray mold, can be the detection of rice shoot gray mold and field gray mold early diagnosis offer effective ways, be advantageously implemented the early prevention and treatment of gray mold.
Summary of the invention
It is an object of the present invention to provide a kind of method analyzing disease plant metabolism group diagnosis of plant gray mold.
In order to solve above-mentioned technical problem, the present invention provides the collection of a kind of plant sample, inactivates, preserves, the extraction of metabolism group, be dried, derivatization and the method for GC-MS detection.
Described biological sample can derive from leaf, flower, really, stem, root, fruit etc..
Described collection method is: clip plant tissue 2-15g (preferably 10g) after alcohol disinfecting shears, is contained in the valve bag finishing writing labelling；
Described inactivation treatment is: the valve bag that will be equipped with sample is immediately placed in quick-freezing 3-5min in liquid nitrogen (preferably 5min)；
Described store method is: the plant sample inoculated as stated above, collect, inactivate is placed in ultra cold storage freezer and preserves (preferably-80 DEG C).
The present invention provides the most simultaneously and the plant sample by pathogen infection obtained by said method is carried out metabolism group extraction, the dry and method of derivatization.
Described extracting method comprises the following steps:
1) freeze grinding crushes: the plant sample after inactivation grinds under the conditions of liquid nitrogen, or uses ball milling instrument to grind break process, obtains sample powder；
2) metabolism group is extracted: accurately weigh the plant sample powder of 100.0 ± 0.5mg, accurately adds 1.8mL Extraction solvent, after using vortex oscillation 1-3min (preferably 1min), continues supersound extraction 10-30min (preferably 15min)；
3) centrifugal treating: by 2) extract obtain metabolism group solution under 4000-15000rpm (preferably 12000rpm), be centrifuged 5-15min (preferably 15min), abandon precipitation, obtain metabolism group extracting solution；
Described drying means is evacuation centrifugal drying, and feature is accurately to pipette 0.6mL supernatant in 0.6-2mL (preferably 0.6mL) centrifuge tube, 30-45 DEG C of (preferably 45 DEG C) evacuation centrifugal drying 4-8h, until constant mass；
Described derivatization method includes oximate and trimethyl silicone hydride two step derivative reaction, and step is as follows:
1) draw 100 μ L derivatization reagents 1 and add in the sample cell that centrifugal drying is good, sealing, ultrasonic 10-30min (preferably 20min), vortex 1-3min (preferably 1min) dissolve, oximate derivative reaction 2h under the conditions of being somewhat centrifuged latter 30 DEG C；
2) draw in derivatization reagent 2 to the sample cell of 100 μ L, sealing, ultrasonic 10-30min (preferably 20min), the most centrifugal, Silylation reaction 4-10h (preferably 6h) under the conditions of 37 DEG C；
3) sample that derivatization obtains centrifugal 15min under rotating speed 10000-15000r/min (preferably 12000r/min), in Aspirate supernatant to GC mother glass pipe, it is thus achieved that for the metabolism group sample of GC-MS detection.
Described extracting method step 2) described Extraction solvent is: methanol and water mixed solution, methanol and water mixed volume are than for 9.5:0.5-5:5 (preferably 8:2)；
Described derivatization method step 1) described derivatization reagent 1 is: methoxy amine hydrochlorate is dissolved in the solution that pyridine obtains, and concentration is 10-40mg/mL (preferably 20mg/mL)；
Described derivatization method step 2) described derivatization reagent 2 is: trim,ethylchlorosilane, N, O-double trimethylsilyl acetamide, tri-methylimidazolium, N, any one in O-double trimethylsilyl trifluoroacetamide, N-methyl-N-trimethylsilyl trifluoroacetamide, HMDS, N-methyl-N-trimethylsilyl acetamide.
Additionally, a kind of method that the present invention provides health plant obtaining above-mentioned pre-treating method and diseased plant tissue metabolism group detects the most simultaneously, it is characterized in that:
Select HP-5MS capillary column (30m × 0.25mm × 0.25 μm)；Sampling volume 1 μ L；Flow velocity 1mL/min；Temperature programming；Ion source and transmission line temperature are respectively 230 DEG C and 280 DEG C；Helium is carrier gas, constant voltage mode；Mass spectrum EI ionization source electron energy 70eV, full scan sweep limits 20-650m/z, frequency 0.2s/scan；Solvent delay time 5.5min.
In addition, the present invention provides a kind of healthy plant obtaining said method the most simultaneously and disease plant metabolism group data thank the group derivation of qualitative, quantitative data, the foundation of discriminant analysis model and detection, thus carry out plant sense gray mold and sentence method for distinguishing, it is characterized in that:
The deriving method of metabolism group qualitative, quantitative data is: use GC-MS to analyze software and testing result carries out metabolism group is qualitative and the derivation of quantitative data, in the total ions chromatogram (TIC) of typical sample, retrieval NIST composes storehouse, obtain the qualitative of chromatographic peak, belong to according to the metabolite of Silanization reaction law-analysing chromatographic peak.Each chromatographic peak is chosen 1 object ion, 2 reference ions, creates quantitative data storehouse, integral parameter is set, from sample detection data, derives each characteristic ion peak area, metabolism group composition is carried out relative quantification；
Discriminant analysis model is set up and is detected as: model is set up and used SAS, TheThe PLS-DA instrument of the softwares such as X or SPSS, the susceptible sample of gray mold and healthy sample or feel him and plant in disease sample, randomly select part data as training set, metabolism group data and classified variable are carried out PLS analysis, sets up the PLS regression model of classified variable and metabolism group data.Model inspection chooses the sample data having neither part nor lot in modeling as detection collection unknown sample, calculating classified variable predictive value, the accuracy rate of analysis sense gray mold sample detection.
Being established as of discriminant analysis model:
1) randomly selecting the metabolism group data of 2/3 sample as training set, set up the classified variable of training set, 1 represents the susceptible sample of grey mold, and 0 represents the susceptible sample of non-grey mold；
2) classified variable is analyzed with the PLS of metabolism group data, sets up the PLS regression model of classified variable and metabolism group data, and modelling verification uses leave one cross validation；
Being detected as of described discriminant analysis model:
1) the metabolism group data of 1/3 sample having neither part nor lot in modeling are chosen as detection collection；
2) the PLS model between the classified variable set up according to training set and metabolism group data, calculates the predictive value (Y of the classified variable of detection collection unknown samplepred), concrete method of discrimination is:
The Y of samplepred> 0.5 and deviation less than 0.5, then judge that sample is as the susceptible sample of grey mold；
The Y of samplepred< 0.5 and deviation less than 0.5, then judge that sample is as the susceptible sample of non-grey mold；
The deviation of sample is more than 0.5, then differentiate instability.
The invention have the advantage that
1, GC-MS is sensitive, stable to the detection of metabolism group, favorable reproducibility, analysis throughput are big.Sample handling procedure is simple, and easy to operate, processing speed is fast, it is adaptable to the process of extensive sample and detection.
2, to unknown sample, the PLS-DA method of discrimination set up differentiates that accuracy rate is high, can realize the differentiation differentiation not showing disease grey mold disease plant and healthy plant, and discriminating grey mold diseased plant disease plant and healthy plant can be planted from infecting him, accurately and reliably, the detection of transplanted seedling grey mold diseased plant and field early prevention and treatment provide reliable method to method.
Accompanying drawing explanation
In conjunction with accompanying drawing, the detailed description of the invention of the present invention is described in further detail.
Fig. 1 Botrytis cinerea infects strawberry and healthy strawberry metabolism group PLS shot chart
Fig. 2 infects PLS actual value and the predictive value regression figure of the PLS-DA calibration model sample classification variable of plant and healthy plant metabolism group based on Botrytis cinerea
Fig. 3 detects PLS-DA Model checking result (1) concentrating unknown sample
Fig. 4 the pathogen of Botrytis cinerea, Fructus Fragariae Ananssae anthrax infect the PLS shot chart of plant and healthy plant metabolism group
Fig. 5 infects PLS actual value and the predictive value regression figure of the PLS-DA calibration model sample classification variable infecting plant and healthy plant metabolism group with Fructus Fragariae Ananssae anthrax based on ash arrhizus bacteria
Fig. 6 detects PLS-DA Model checking result (2) concentrating unknown sample
Fig. 7 does not connects bacterium matched group Strawberry Leaves sample metabolism group total ion current figure
Fig. 8 inoculates the pathogen of Botrytis cinerea Strawberry Leaves sample metabolism group total ion current figure
Detailed description of the invention
Embodiment 1 analyzes the strawberry metabolism group gray mold diagnostic analysis to not showing disease sample based on GC-MS
One, the pre-treatment of strawberry metabolism group sample is analyzed based on GC-MS
1) inoculation of the pathogen of Botrytis cinerea
Inoculate front clear water and wash away the dust of blade surface, with 75% ethanol to blade surface disinfection.Using the vaccination ways without wound spraying, by 25ml spore suspension, (concentration is 105Individual/about ml) uniformly it is sprayed to the position, ground of strawberry.After inoculation, flowerpot is put in water tray, seal with plastic foil.By 20 DEG C of dark processing 12h of strawberry of inoculation the pathogen of Botrytis cinerea, it is positioned under normal lighting conditions cultivation afterwards.Control treatment sprays clear water, and other process are identical；
2) collection method is: respectively after inoculation 2d, 5d, 7d, and clip plant tissue after alcohol disinfecting shears is contained in the valve bag finishing writing labelling；
3) inactivation treatment is: the valve bag that will be equipped with blade is placed in quick-freezing 3-5min in liquid nitrogen；
4) store method is: the plant leaf blade sample inoculated as stated above, collect, inactivate is placed in-80 DEG C of ultra cold storage freezers and preserves.
5) weigh the plant sample powder of 100.0 ± 0.5mg in centrifuge tube, add 1.8mL said extracted solvent, after vortex oscillation 1min, continue supersound extraction 20min.
6) centrifugal drying: be centrifuged 10min under 12000rpm by extracting the metabolism group solution obtained,
Accurately pipetting 0.6mL supernatant in centrifuge tube, 45 DEG C of evacuation centrifugal drying 4h are to constant mass.
7) derivatization
Including the double trimethylsilyl trifluoroacetamide of N, O-and methoxy amine hydrochlorate two step derivative reaction:
Drawing 100 μ L derivatization reagent methoxy amine hydrochlorate solution (being dissolved in pyridine, concentration 20mg/mL) and add in the sample cell that centrifugal drying is good, sealing, ultrasonic 15min, vortex 1min dissolve, are somewhat centrifuged rear 30 DEG C of derivative reaction 2h；
Add the double trimethylsilyl trifluoroacetamide of derivatization reagent N, O-of 100 μ L in sample cell, sealing, ultrasonic 20min, the most centrifugal, 37 DEG C of derivative reaction 6h carry out following step 3)；
The derivatization sample obtained is centrifugal 15min under centrifugal rotational speed 12000r/min, draws in 160 μ L to GC mother glass pipes, it is thus achieved that for the strawberry metabolism group sample of GC-MS detection.
Two, the detection of strawberry sample metabolism group sample is analyzed based on GC-MS
Carrying out GC-MS detection, INSTRUMENT MODEL is: gas phase is 7890A, and mass spectrum is 5975C.The testing conditions of concrete employing is: HP-5MS capillary column (30m × 0.25mm × 0.25 μm)；Sampling volume 1 μ L；Flow velocity 1mL/min；Ion source and transmission line temperature are respectively 230 DEG C and 280 DEG C；Helium is carrier gas, constant voltage mode；Mass spectrum EI ionization source 70eV, full scan sweep limits m/z 20-650, frequency 0.2s/scan；Solvent delay time 5.5min.
Heating schedule parameter is shown in Table 1:
Table 1 chromatographic column gradient increased temperature program parameter
| Programming rate (DEG C/min) | Temperature (DEG C) | Retention time (min) |
| 65 | 2 | |
| 5 | 185 | 0 |
| 1 | 200 | 0 |
| 15 | 280 | 25 |
After testing, bacterium matched group Strawberry Leaves sample metabolism group total ion current figure is not connect as shown in Figure 7.189 peaks detected altogether, compose storehouse comparison with NIST, and after removing repetition material, find that the Strawberry Leaves metabolism group matching degree metabolite more than 80% has 31, wherein organic acid have 12 kinds, saccharide have 13 kinds, other classification have 6 kinds.
Three, analyze strawberry metabolism group based on GC-MS and the gray mold not showing disease sample is diagnosed discriminant analysis
PLS-DA method is the regression model between the sample classification variable and GC-MS data set up based on PLS method.Therefore, first the sample to training set carries out assignment: the susceptible sample of Botrytis cinerea of three sampling time acquisitions is entered as 1, and healthy sample is entered as 0.Test have collected 36 samples, and the ratio that training set and detection integrate, as 2:1, uses 24 samples to do training set, and 12 are made detection collection.
1) foundation of PLS-DA discrimination model and checking
Utilize PLS method that the GC-MS data of calibration set sample and the classified variable of sample are carried out regression analysis, set up Botrytis cinerea diseased plant discriminant analysis PLS model.As it is shown in figure 1, susceptible for Botrytis cinerea group and healthy group can clearly be separated by model, the X variable of 35% can explain the Y variable of 8%, and the reliability of the adjustment model is high, may be used for discriminant analysis.
The discrimination model of the Fructus Fragariae Ananssae incidence set up by PLS regression analysis as shown in Figure 2 is preferable.In figure, two straight lines are respectively model correction result and the regression line of the result, and two regression line essentially coincide.The corrected value of indicator variable and the validation value correlation coefficient of model are all higher than 0.946；Correction straight-line pass initial point, checking straight line is close to initial point；The correction of model and the mean square deviation root (RMSE) of the result are respectively 0.0434,0.1210 all close to 0, skew (Offset) respectively 0.0038,0.0499 is close to 0, and slope (Slop) is respectively 0.9925,0.8853 close to 1.Illustrate that the matching of model is good.
2) the PLS-DA model differentiation to detection collection sample
12 unknown samples are differentiated by the model of employing foundation, Fig. 3 and Biao 2 is susceptible group of Botrytis cinerea and predicting the outcome that health is organized in detection collection sample.The prediction deviation of all samples is the most relatively low as shown in Table 2, close to 0.1.The Y of 1～No. 6 samplepredBoth greater than 0.5, close to 1, it determines for the susceptible sample of Botrytis cinerea.The Y of 7～No. 12 samplespredIt is respectively less than 0.5, close to 0, is identified as healthy sample.All 12 sample standard deviations obtain correct differentiation, show PLS-DA model can well by the susceptible sample of Botrytis cinerea and healthy sample differentiate out, the recognition accuracy of sample has reached 100%.
The differentiation result of the PLS-DA model of unknown sample is concentrated in table 2 detection
Embodiment 2 is analyzed Botrytis cinerea based on GC-MS and is infected strawberry metabolism group to gray mold diagnostic analysis
One, the pre-treatment of strawberry metabolism group sample is infected based on GC-MS analysis ash arrhizus bacteria and Strawberry anthracnose bacterium
1) the pathogen of Botrytis cinerea and the inoculation of Fructus Fragariae Ananssae anthrax
Inoculate front clear water and wash away the dust of blade surface, with 75% ethanol to blade surface disinfection.Using the vaccination ways without wound spraying, by 25ml spore suspension, (concentration is 105Individual/about ml) uniformly it is sprayed to the position, ground of strawberry.After inoculation, flowerpot is put in water tray, seal with plastic foil.By 20 DEG C of dark processing 12h of strawberry of inoculation botrytis cinerea, it is positioned under normal lighting conditions cultivation afterwards.By 26 DEG C of dark processing 48h of strawberry of inoculation Fructus Fragariae Ananssae anthrax, it is positioned under normal lighting conditions cultivation afterwards.Control treatment sprays clear water, and other process are identical；
2) collection method is: for inoculating the plant of the pathogen of Botrytis cinerea, after inoculation, 2d, 5d, 7d collect strawberry sense gray mold sample according to embodiment 1 method；For inoculating the plant of Strawberry anthracnose bacterium, after inoculation, 3d, 7d, 14d collect strawberry sense anthrax sample according to embodiment 1 method；Inoculate the collection of corresponding time respectively at two kinds of pathogenic bacterias and do not connect bacterium strawberry sample as healthy plant sample.
The inactivation treatment of sample, preserve, extract, centrifugal drying, derivatization method be with embodiment 1.
Two, the detection of strawberry metabolism group sample is infected based on GC-MS analysis ash arrhizus bacteria and Strawberry anthracnose bacterium
The detection method of sample is with embodiment 1.After testing, inoculation the pathogen of Botrytis cinerea Strawberry Leaves sample metabolism group total ion current figure is as shown in Figure 8.189 peaks detected altogether, compose storehouse comparison with NIST, and after removing repetition material, find that the Strawberry Leaves metabolism group matching degree metabolite more than 80% has 31, wherein organic acid have 12 kinds, saccharide have 13 kinds, other classification have 6 kinds.
Three, analyze strawberry metabolism group based on GC-MS and gray mold is diagnosed discriminant analysis
Data analysing method is in the same manner as in Example 1.
First the sample to training set carries out assignment: the sample of two strain the pathogen of Botrytis cinereas 52,59 inoculations of three time collections is entered as 1, and the sample not connecing bacterium sample and the inoculation of Fructus Fragariae Ananssae anthrax spores is then entered as 0.We have collected 89 samples, and the ratio that training set and detection integrate, as 2:1, uses 60 samples to do training set, and 29 samples are used as detection collection.
1) foundation of PLS-DA discrimination model and checking
As shown in Figure 4, Botrytis cinerea disease plant can clearly be distinguished by model with healthy plant or Fructus Fragariae Ananssae anthrax disease plant, the X variable of 48% can explain the Y variable of 3%, the reliability of the adjustment model is high, may be used for differentiating the analysis of Botrytis cinerea disease plant from healthy strawberry or Fructus Fragariae Ananssae anthrax disease plant.
The Fructus Fragariae Ananssae incidence set up by PLS regression analysis as shown in Figure 5 and the good relationship of indicator variable.In figure, two straight lines are respectively model correction result and the regression line of checking, and two regression line essentially coincide.The corrected value of indicator variable and the validation value correlation coefficient of model are all higher than 0.962；Correction straight-line pass initial point, checking straight line is close to initial point；The correction of model and the mean square deviation root (RMSE) of the result are respectively 0.0551,0.0975 all close to 0, skew (Offset) is respectively 0.0051,0.0229 close to 0, slope (Slop) respectively 0.9873,0.9396, close to 1, illustrates fitting preferably of model.
2) the PLS-DA model differentiation to detection collection sample
Using the model set up that 29 unknown samples carry out discriminant analysis, what Fig. 6 and Biao 3 was susceptible group of Botrytis cinerea in detection collection sample and health group or susceptible group of Fructus Fragariae Ananssae anthrax predicts the outcome.The prediction deviation of the most all samples is the most relatively low, close to 0.1.The Y of 1～No. 12 samplepredBoth greater than 0.5, close to 1, it determines for the susceptible sample of grey mold.The Y of 13～No. 29 samplespredIt is respectively less than 0.5, close to 0, is identified as healthy group or susceptible group of sample of Fructus Fragariae Ananssae anthrax.All 29 sample standard deviations obtain correct differentiation, show that susceptible for Botrytis cinerea sample can be differentiated out from healthy group or susceptible group of sample of Fructus Fragariae Ananssae anthrax by PLS-DA model well, and the recognition accuracy of sample has reached 100%.
The differentiation result of the PLS-DA model of unknown sample is concentrated in table 3 detection
。
Claims (6)
1. the method analyzing disease plant metabolism group diagnosis of plant gray mold, comprises the following steps and carries out successively: the collection of plant sample, inactivates, preserve, the extraction of metabolism group, be dried, derivatization and GC-MS detection；
The acquisition method of described plant sample is: clip plant tissue 2-15g after alcohol disinfecting shears, is contained in the valve bag finishing writing labelling；
Described ablation method is: the valve bag that will be equipped with sample is immediately placed in quick-freezing 3-5min in liquid nitrogen；
Described store method is: the plant sample inoculated as stated above, collect, inactivate is placed in ultra cold storage freezer and preserves；
Described metabolism group extracting method comprises the following steps:
1) freeze grinding crushes: the plant sample after inactivation grinds under the conditions of liquid nitrogen, or uses ball milling instrument to grind break process, obtains sample powder；
2) metabolism group is extracted: weigh the plant sample powder of 100.0 ± 0.5mg, accurately adds 1.8mL Extraction solvent, after using vortex oscillation 1-3min, continues supersound extraction 10-30min；
3) centrifugal treating: by 2) extract obtain metabolism group solution under 4000-15000rpm, be centrifuged 5-15min, discard precipitation, obtain metabolism group extracting solution；
Described drying means is: accurately pipette 0.6mL supernatant in 0.6-2mL centrifuge tube, 30 DEG C-45 DEG C evacuation centrifugal drying 4-8h, until constant mass；
Described derivatization method includes oximate and trimethyl silicone hydride two step derivative reaction, and step is as follows:
1) draw 100 μ L derivatization reagents 1 and add in the sample cell that centrifugal drying is good, sealing, ultrasonic 10-30min, vortex 1-3min dissolving, oximate derivative reaction 2h under the conditions of being somewhat centrifuged latter 30 DEG C；
2) add in derivatization reagent 2 to the sample cell of 100 μ L, sealing, ultrasonic 10-30min, the most centrifugal, Silylation reaction 4-10h under the conditions of 37 DEG C；
3) sample that derivatization obtains centrifugal 15min under rotating speed 10000-15000r/min, in Aspirate supernatant to GC mother glass pipe, it is thus achieved that for the metabolism group sample of GC-MS detection；
Described Extraction solvent is: methanol and water mixed solution, and methanol and water mixed volume are than for 9.5:0.5-5:5；
Described derivatization reagent 1 is: methoxy amine hydrochlorate is dissolved in the solution that pyridine obtains, and concentration is 10-40mg/mL；
Described derivatization reagent 2 is: trim,ethylchlorosilane, N, O-double trimethylsilyl acetamide, tri-methylimidazolium, N, any one in O-double trimethylsilyl trifluoroacetamide, N-methyl-N-trimethylsilyl trifluoroacetamide, HMDS, N-methyl-N-trimethylsilyl acetamide；
Described GC-MS detection method is: select HP-5MS capillary column, temperature programming, and ion source and transmission line temperature are respectively 230 DEG C and 280 DEG C, use EI ionization source, full scan scope m/z 20～650.
2. the method analyzing as claimed in claim 1 disease plant metabolism group diagnosis of plant gray mold, it is characterised in that: the wherein collection of plant sample, inactivation, the condition of store method be:
The acquisition method of described plant sample is: clip plant tissue 10g after alcohol disinfecting shears, is contained in the valve bag finishing writing labelling；
Described ablation method is: the valve bag that will be equipped with sample is immediately placed in quick-freezing 5min in liquid nitrogen；
Described store method is: the plant sample inoculated as stated above, collect, inactivate is placed in-80 DEG C of Refrigerator stores.
3. the method analyzing as claimed in claim 1 disease plant metabolism group diagnosis of plant gray mold, it is characterised in that: the extraction of wherein metabolism group, it is dried and the condition of derivatization method is:
Described metabolism group extracting method comprises the following steps:
1) freeze grinding crushes: the plant sample after inactivation grinds under the conditions of liquid nitrogen, or uses ball milling instrument to grind break process 1min, obtains sample powder；
2) metabolism group is extracted: weigh the plant sample powder of 100.0 ± 0.5mg, accurately adds 1.8mL Extraction solvent, after using vortex oscillation 1min, continues supersound extraction 15min；
3) centrifugal treating: by 2) extract obtain metabolism group solution under 12000rpm, be centrifuged 15min, discard precipitation, obtain metabolism group extracting solution；
Described drying means is: accurately pipette 0.6mL supernatant in 0.6mL centrifuge tube, 45 DEG C of evacuation centrifugal drying 4-8h, until constant mass；
Described derivatization method includes oximate and trimethyl silicone hydride two step derivative reaction, and step is as follows:
1) draw 100 μ L derivatization reagents 1 and add in the sample cell that centrifugal drying is good, sealing, ultrasonic 20min, vortex 1min dissolving, oximate derivative reaction 2h under the conditions of being somewhat centrifuged latter 30 DEG C；
2) add in derivatization reagent 2 to the sample cell of 100 μ L, sealing, ultrasonic 20min, the most centrifugal, Silylation reaction 4-10h under the conditions of 37 DEG C；
3) sample that derivatization obtains centrifugal 15min under rotating speed 12000r/min, in Aspirate supernatant to GC mother glass pipe, it is thus achieved that for the metabolism group sample of GC-MS detection.
4. the as claimed in claim 3 method analyzing disease plant metabolism group diagnosis of plant gray mold, it is characterised in that: the Extraction solvent used by the extraction of wherein metabolism group and derivatization and the agent combination used by derivative reaction be:
Described Extraction solvent is: methanol and water mixed solution, and methanol and water mixed volume are than for 8:2；
Described derivatization reagent 1 is: methoxy amine hydrochlorate is dissolved in the solution that pyridine obtains, and concentration is 20mg/mL；
Described derivatization reagent 2 is: trim,ethylchlorosilane, N, O-double trimethylsilyl acetamide, tri-methylimidazolium, N, any one in O-double trimethylsilyl trifluoroacetamide, N-methyl-N-trimethylsilyl trifluoroacetamide, HMDS, N-methyl-N-trimethylsilyl acetamide.
5. the plant sense gray mold discriminant analysis method that the GC-MS testing result utilizing method as described in any one of claim 1-4 to obtain is carried out, comprises the following steps and carries out successively: derivation, the foundation of discriminant analysis model and the detection of metabolism group qualitative, quantitative data；
The deriving method of described metabolism group qualitative, quantitative data is: use GC-MS to analyze software and testing result carries out metabolism group is qualitative and the derivation of quantitative data, in the total ions chromatogram (TIC) of typical sample, retrieval NIST composes storehouse, obtain the qualitative of chromatographic peak, belong to according to the metabolite of Silanization reaction law-analysing chromatographic peak.Each chromatographic peak is chosen 1 object ion, 2 reference ions, creates quantitative data storehouse, integral parameter is set, from sample detection data, derives each characteristic ion peak area, metabolism group composition is carried out relative quantification；
Described discriminant analysis model is set up and is detected as: model is set up and used SAS, TheThe PLS-DA instrument of the softwares such as X or SPASS, the susceptible sample of gray mold and healthy sample or feel him and plant in disease sample, randomly select part data as training set, metabolism group data and classified variable are carried out PLS analysis, sets up the PLS regression model of classified variable and metabolism group data.Model inspection chooses the sample data having neither part nor lot in modeling as detection collection unknown sample, calculating classified variable predictive value, the accuracy rate of analysis sense gray mold sample detection.
6. the plant sense gray mold discriminant analysis method that the GC-MS testing result utilizing method as described in any one of claim 1-4 to obtain as claimed in claim 5 is carried out, it is characterised in that: wherein foundation and the detection method of discriminant analysis model is:
Being established as of described discriminant analysis model:
1) randomly selecting the metabolism group data of 2/3 sample as training set, set up the classified variable of training set, 1 represents the susceptible sample of grey mold, and 0 represents the susceptible sample of non-grey mold；
2) classified variable is analyzed with the PLS of metabolism group data, sets up the PLS regression model of classified variable and metabolism group data, and modelling verification uses leave one cross validation；
Being detected as of described discriminant analysis model:
1) the metabolism group data of 1/3 sample having neither part nor lot in modeling are chosen as detection collection；
2) the PLS model between the classified variable set up according to training set and metabolism group data, calculates the predictive value (Y of the classified variable of detection collection unknown samplepred), concrete method of discrimination is:
The Y of samplepred> 0.5 and deviation less than 0.5, then judge that sample is as the susceptible sample of grey mold；
The Y of samplepred< 0.5 and deviation less than 0.5, then judge that sample is as the susceptible sample of non-grey mold；
The deviation of sample is more than 0.5, then differentiate instability.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610260197.1A CN105929068B (en) | 2016-04-25 | 2016-04-25 | A method of analysis disease plant metabolism group diagnosis of plant gray mold |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610260197.1A CN105929068B (en) | 2016-04-25 | 2016-04-25 | A method of analysis disease plant metabolism group diagnosis of plant gray mold |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105929068A true CN105929068A (en) | 2016-09-07 |
| CN105929068B CN105929068B (en) | 2018-09-28 |
Family
ID=56837121
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610260197.1A Active CN105929068B (en) | 2016-04-25 | 2016-04-25 | A method of analysis disease plant metabolism group diagnosis of plant gray mold |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105929068B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107796884A (en) * | 2017-09-06 | 2018-03-13 | 中国农业大学 | A kind of bactericide study on mechanism method based on metabolism group |
| CN109828019A (en) * | 2019-02-21 | 2019-05-31 | 南昌大学 | The method that electron spray extraction ionization mass spectrometry quickly detects Citrus Huanglongbing pathogen |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104391060A (en) * | 2014-10-15 | 2015-03-04 | 中国农业大学 | Sample pretreatment and detection methods in researches of Botrytis cinerea metabolome based on GC-MS |
-
2016
- 2016-04-25 CN CN201610260197.1A patent/CN105929068B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104391060A (en) * | 2014-10-15 | 2015-03-04 | 中国农业大学 | Sample pretreatment and detection methods in researches of Botrytis cinerea metabolome based on GC-MS |
Non-Patent Citations (2)
| Title |
|---|
| D. D. ARCHBOLD等: "Identifying Natural Volatile Compounds That Control Gray Mold (Botrytis cinerea) during Postharvest Storage of Strawberry,Blackberry, and Grape", 《J. AGRIC. FOOD CHEM. 》 * |
| 王衬: "基于衍生化GC-MS的水稻-真菌互相代谢普研究", 《万方学位论文数据库》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107796884A (en) * | 2017-09-06 | 2018-03-13 | 中国农业大学 | A kind of bactericide study on mechanism method based on metabolism group |
| CN109828019A (en) * | 2019-02-21 | 2019-05-31 | 南昌大学 | The method that electron spray extraction ionization mass spectrometry quickly detects Citrus Huanglongbing pathogen |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105929068B (en) | 2018-09-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Fredes et al. | Quantification of prominent volatile compounds responsible for muskmelon and watermelon aroma by purge and trap extraction followed by gas chromatography–mass spectrometry determination | |
| Cellini et al. | Early detection of bacterial diseases in apple plants by analysis of volatile organic compounds profiles and use of electronic nose | |
| Sharma et al. | Rapid in situ analysis of plant emission for disease diagnosis using a portable gas chromatography device | |
| Sinha et al. | Rapid and non–destructive detection of Pectobacterium carotovorum causing soft rot in stored potatoes through volatile biomarkers sensing | |
| CN102565233B (en) | Method for determining volatile and semi-volatile secondary metabolite in fresh tobacco leaves | |
| CN104391060B (en) | The sample pre-treatments of GC-MS research the pathogen of Botrytis cinerea metabolism group and detection method | |
| Blasioli et al. | Electronic nose as an innovative tool for the diagnosis of grapevine crown gall | |
| Qiu et al. | High-temperature induced changes of extracellular metabolites in Pleurotus ostreatus and their positive effects on the growth of Trichoderma asperellum | |
| Bianchi et al. | Characterisation of the volatile profile of orange juice contaminated with Alicyclobacillus acidoterrestris | |
| CN105929068A (en) | Method for diagnosing plant gray mold by analyzing metabolome of infected plant | |
| Cagnasso et al. | Rapid screening of alicyclobacillus acidoterrestris spoilage of fruit juices by electronic nose: a confirmation study | |
| Wang et al. | Emission of volatile organic compounds from healthy and diseased onions | |
| Zhang et al. | Aroma in freshly squeezed strawberry juice during cold storage detected by E-nose, HS–SPME–GC–MS and GC-IMS | |
| CN106093237B (en) | Plant anthracnose diagnostic method based on the analysis of disease plant metabolic components | |
| Neri et al. | Interplay of apple volatile organic compounds with Neofabraea vagabunda and other post‐harvest pathogens | |
| CN107796884A (en) | A kind of bactericide study on mechanism method based on metabolism group | |
| Girotti et al. | Early detection of toxigenic Fusarium graminearum in wheat | |
| Stein et al. | Fusarium head blight severity and deoxynivalenol concentration in wheat in response to Gibberella zeae inoculum concentration | |
| US20230304984A1 (en) | A method for the early detection of potato bacterial diseases based on characterizing volatile signatures | |
| CN107271490B (en) | The method that Antrodia camphorata liquid fermentation process quickly characterizes triterpenoid changes of contents | |
| CN207067075U (en) | Rice mould on-line monitoring system | |
| Tunali et al. | Endophytic fungi and ergot alkaloids in native Turkish grasses | |
| CN104215759B (en) | A kind of with DASELISA immunoadsorption method detection by quantitative Morchella esculenta (L.) Pers. Mycelium | |
| Kim et al. | Development of on-line sorting system for detection of infected seed potatoes using visible near-infrared transmittance spectral technique | |
| CN111122658B (en) | Method and device for detecting infection degree of fruit botrytis cinerea |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |