CN105803070A - Method for measuring relative content of puccinia striiformis DNA (deoxyribose nucleic acid) in wheat leaves - Google Patents
Method for measuring relative content of puccinia striiformis DNA (deoxyribose nucleic acid) in wheat leaves Download PDFInfo
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Abstract
The invention belongs to the technical field of plant protection and provides a method for measuring the relative content of puccinia striiformis DNA (deoxyribose nucleic acid) in wheat leaves. The method comprises steps as follows: acquiring near-infrared spectrum information of to-be-tested leaves in the incubation period of wheat stripe rust; applying a measurement model to determine the relative content of puccinia striiformis DNA corresponding to the near-infrared spectrum information of the to-be-tested leaves in the incubation period of wheat stripe rust, wherein the measurement model indicates the corresponding relation between the near-infrared spectrum information and the relative content of puccinia striiformis DNA. The method for measuring the relative content of puccinia striiformis DNA in the wheat leaves can be used for measuring the relative content of puccinia striiformis DNA in the incubation period of wheat stripe rust quickly, accurately and quantitatively.
Description
Technical field
The present invention relates to technical field of plant protection, be specifically related to Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade.
Background technology
Stripe rust of wheat is to be caused by bar shaped handle rest fungus Semen Tritici aestivi specialized form (Pucciniastriiformisf.sp.tritici, Pst), is one of Major Diseases on Semen Tritici aestivi in world wide.This disease can cause serious wheat yield to lose, once outburst at least results in wheat yield 10%～30%, even causes total crop failure, is the significant threat of China's Semen Tritici aestivi safety in production.Since the 1950's, stripe rust of wheat was repeatedly very popular in China, has had a strong impact on Wheat Production, made China's wheat yield 60,30,26 and 1,400,000,000 kg respectively in 1950,1964,1990 and 2002.One infection processs of wheat stripe rust generally comprises contact phase, stage of invasion, incubation period and 4 periods of period of disease.The land puccinia striiformis in wheat leaf blade surface relies on uredospores germination to produce germ tube and invades Semen Tritici aestivi, initial stage of infecting produces substantial amounts of mycelia in wheat leaf blade, but it is difficult to observe by Disease symptoms at blade surface, causes many difficulties and inconvenience to the early monitoring of disease and prediction.
Puccinia striiformis infect and extension in pin main body is the process of a dynamic quantitative change, once produce Stripe Rust uredium on blade, this disease can be propagated by air-flow.If the early stage detection that puccinia striiformis infects can be accomplished, particularly infecting the detection by quantitative of bacterium amount, the formulation pinpointing preventing and treating, prediction and control strategy early for this disease has great importance.Especially, if Yue Xia district can be realized, district's stripe rust of wheat of surviving the winter infects the early stage detection by quantitative of bacterium amount, the macroscopical prevention and control for stripe rust of wheat are particularly important.At present, usually by the investigation of field incidence, stripe rust of wheat is monitored.More existing new technology and method are used to plant disease monitoring, and especially high spectrum resolution remote sensing technique, molecular Biological Detection technology, thermal infrared imaging technology and near-infrared spectrum technique etc. be detect in early days of plant disease to provide more fast and convenient means.By detecting the existence of puccinia striiformis, utilize Protocols in Molecular Biology accurately qualitative detection can be subject to infecting of Stripe Rust to wheat leaf blade in the stripe rust of wheat incubation period.High spectrum resolution remote sensing technique is utilized to may identify which healthy Semen Tritici aestivi and be subject to puccinia striiformis and infect but the Semen Tritici aestivi that not yet shows symptom.Studies have reported that the utilization outer infrared imagery technique of heat and near-infrared spectrum technique can detect infecting of puccinia striiformis before Disease symptoms occurs.But the research of stripe rust of wheat incubation period pathogen quantitatively early stage context of detection is relatively fewer.Studies have reported that the detection by quantitative realizing incubation period puccinia striiformis DNA mainly by real-timePCR method.
But, utilize and waste time and energy during field incidence investigation method monitoring stripe rust of wheat, and be only capable of field of falling ill is carried out investigation statistics, it is impossible to incubation period stripe rust blade is carried out accurate, quickly identify；High spectrum resolution remote sensing technique instrument is costly；Instrument imaging resolution and temperature resolution are required higher by the outer red imaging technique of heat；Protocols in Molecular Biology detection process is complicated, and technology and instrument requirements is higher, and sample is subject to environmental pollution.Although at present existing can the instrument of quantitative analysis in the wild, but still need to user and grasp corresponding molecular biology technical ability, and need to obtain a large amount of detected sample, utilize merely Protocols in Molecular Biology cannot quickly obtain large-area molecular data and provide foundation for disease early warning.And, based on detection method more difficult large-scale promotion application on producing of the pathogen latent infection of high spectrum resolution remote sensing technique, thermal infrared imaging technology and Protocols in Molecular Biology.Therefore, it is badly in need of seeking a kind of simple and convenient, stripe rust of wheat early stage detection method accurately and rapidly.
Near-infrared spectrum technique (nearinfraredreflectancespectroscopy, NIRS) it is a kind of accurate, lossless, stable analytical technology, this technical Analysis process is simple, quick, is that one is easy to on-line analysis, lower-cost Fast Detection Technique.At present, near-infrared spectrum technique is widely used to the industries such as agricultural, food, oil, chemical industry, medicine.Utilize near-infrared spectrum technique can carry out puccinia striiformis and the uredinial qualitative recognition of leaf rust bacterium and quantitative assay.But, prior art is only utilize near-infrared spectrum technique that stripe rust of wheat and leaf rust blade can carry out early stage qualitative recognition, realize the assessment of stripe rust of wheat Severity gradation, and qualitative recognition is subject to puccinia striiformis and infects not yet aobvious disease, is in the Semen Tritici aestivi in incubation period.But there is no the research report utilizing near-infrared spectrum technique to carry out stripe rust of wheat incubation period bacterium amount detection by quantitative at present.
Summary of the invention
For the defect that prior art exists, the present invention proposes Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade, to solve the problem that stripe rust of wheat can not carry out early stage detection by quantitative simple and convenient, accurately and rapidly that prior art exists.
For this purpose it is proposed, the present invention provides Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade, the method includes:
Obtain the near infrared light spectrum information of stripe rust of wheat incubation period blade to be measured；
Near infrared light spectrum information according to described stripe rust of wheat incubation period blade to be measured, application rating model determines the Stripe Rust DNA relative amount corresponding with the near infrared light spectrum information of described stripe rust of wheat incubation period blade to be measured；Described rating model is the model representing the corresponding relation between near infrared light spectrum information and Stripe Rust DNA relative amount.
Wherein, before the near infrared light spectrum information of described acquisition stripe rust of wheat incubation period to be measured blade, described method also includes:
Build described rating model, specifically include:
To the stripe rust of wheat incubation period, the near infrared spectrum of leaf sample is acquired, and obtains the near infrared spectrum of sample；
Calculate the Stripe Rust DNA relative amount in described stripe rust of wheat incubation period leaf sample；
Relative amount according to the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and the near infrared spectrum of described sample, build Stripe Rust DNA relative amount rating model.
Wherein, the described near infrared spectrum to stripe rust of wheat incubation period leaf sample is acquired, and obtains the near infrared spectrum of sample, including:
Adopt integrating sphere diffuse-reflectance method to gather the near infrared spectrum of stripe rust of wheat incubation period leaf sample, obtain the near infrared spectrum of stripe rust of wheat incubation period leaf sample.
Wherein, the Stripe Rust DNA relative amount in leaf sample of described calculating described stripe rust of wheat incubation period, including:
Extract healthy wheat leaf blade DNA, Stripe Rust uredospore DNA and described stripe rust of wheat incubation period leaf sample DNA respectively, obtain the content of described healthy wheat leaf blade DNA content, the content of described Stripe Rust uredospore DNA and described stripe rust of wheat incubation period leaf sample DNA；
According to described healthy wheat leaf blade DNA content, described Stripe Rust uredospore DNA content, adopt multiple fluorescence quantitative PCR technology, set up the standard curve of the described healthy standard curve of wheat leaf blade DNA, described Stripe Rust uredospore DNA；
Content according to described stripe rust of wheat incubation period leaf sample DNA, utilize the standard curve of the described healthy standard curve of wheat leaf blade DNA, described Stripe Rust uredospore DNA, calculate the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and wheat leaf blade DNA；
According to the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and wheat leaf blade DNA, calculate the relative amount of Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample.
Wherein, the near infrared spectrum of the described relative amount according to the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and described sample, build Stripe Rust DNA relative amount rating model, including:
The relative amount of the Stripe Rust DNA near infrared spectrum according to described sample and described stripe rust of wheat incubation period leaf sample, combination adopts quantitative partial least square method QPLS and support vector regression SVR, builds kQPLS-SVR rating model.
Wherein, the relative amount of the Stripe Rust DNA in the described near infrared spectrum according to described sample and described stripe rust of wheat incubation period leaf sample, combination adopts quantitative partial least square method QPLS and support vector regression SVR, builds kQPLS-SVR rating model, including:
Randomly selecting m feature from the wavelength points spectral signature of the near infrared spectrum of described stripe rust of wheat incubation period leaf sample, and number of principal components is set to n, wherein, m, n are preset constant；
According to described m feature and the described number of principal components being set to n, building k QPLS rating model successively, wherein, k is preset constant；
Using the predictive value of described k QPLS rating model as variable, build SVR rating model, thus obtaining kQPLS-SVR rating model.
Wherein, described method also includes:
According to preset ratio, by the near infrared spectrum of described stripe rust of wheat incubation period leaf sample, it is divided into training set and test set；
Relative amount according to the Stripe Rust DNA in described training set and described stripe rust of wheat incubation period leaf sample, combination adopts quantitative partial least square method QPLS and support vector regression SVR, builds kQPLS-SVR rating model；
Coefficient of determination R according to described training set, described test set2, calibration standard difference SEC, prediction standard deviation SEP, average relative error AARD and relative prediction deviation RPD, described kQPLS-SVR rating model is evaluated, obtains evaluation result；
According to described evaluation result, select optimum kQPLS-SVR rating model.
Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade provided by the invention, by utilizing near-infrared spectrum technique to gather the near infrared spectrum of stripe rust of wheat incubation period leaf sample, and utilize multiple fluorescence quantitative PCR technology, obtain the relative amount of stripe rust of wheat incubation period leaf sample Stripe Rust DNA, and pass through the near infrared spectrum of stripe rust of wheat incubation period leaf sample and the relative amount of Stripe Rust DNA, set up the causes of the near infrared spectrum of wheat leaf blade and the relative amount of Stripe Rust DNA, and utilize this causes to carry out quantitatively to the Stripe Rust amount in stripe rust of wheat incubation period blade to be detected, quickly, lossless, detect accurately, and the early stage detection for other plant disease provides reference.
Accompanying drawing explanation
In order to be illustrated more clearly that disclosure embodiment or technical scheme of the prior art, the accompanying drawing used required in embodiment or description of the prior art will be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the disclosure, for those of ordinary skill in the art, under the premise not paying creative work, it is also possible to obtain other accompanying drawing according to these figure.
The flow chart of Stripe Rust DNA relative amount measuring method in the wheat leaf blade that Fig. 1 provides for one embodiment of the invention；
Fig. 2 is the flow chart of the fine division step of the step S0 in one embodiment of the invention；
Fig. 3 is the near infrared light spectrogram of the stripe rust of wheat incubation period leaf sample obtained in one embodiment of the invention；
Fig. 4 is the canonical plotting of the Stripe Rust uredospore DNA in one embodiment of the invention；
Fig. 5 is the canonical plotting of the healthy wheat leaf blade DNA in one embodiment of the invention；
Fig. 6 is the Day-to-day variability figure of the Stripe Rust DNA relative amount in the stripe rust of wheat incubation period leaf sample in one embodiment of the invention；
Fig. 7 is the Day-to-day variability figure of the Stripe Rust DNA relative amount logarithm value in the stripe rust of wheat incubation period leaf sample in one embodiment of the invention；
Fig. 8 is the modeling procedure figure of the kQPLS-SVR rating model in one embodiment of the invention.
Detailed description of the invention
Below in conjunction with the accompanying drawing in disclosure embodiment, the technical scheme in disclosure embodiment is clearly and completely described, it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the disclosure, the every other embodiment that those of ordinary skill in the art obtain under not making creative work premise, broadly fall into the scope of disclosure protection.
As it is shown in figure 1, the disclosure one embodiment provides Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade, the method comprises the steps S0 to S2:
S0, structure rating model；
S1, obtain the near infrared light spectrum information of stripe rust of wheat incubation period blade to be measured；
S2, near infrared light spectrum information according to described stripe rust of wheat incubation period blade to be measured, apply described rating model and determine the Stripe Rust DNA relative amount corresponding with the near infrared light spectrum information of described stripe rust of wheat incubation period blade to be measured；Described rating model is the model representing the corresponding relation between near infrared light spectrum information and Stripe Rust DNA relative amount.
Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade that the present embodiment provides, by utilizing near-infrared spectrum technique to gather the near infrared spectrum of stripe rust of wheat incubation period blade to be measured, and the near infrared spectrum according to the stripe rust of wheat incubation period blade to be measured gathered, application rating model, Stripe Rust DNA relative amount in measurement stripe rust of wheat incubation period to be measured blade that can be quick, accurate, quantitative.
Specifically, as in figure 2 it is shown, the step S0 in above-described embodiment, following fine division step S01 to S03 is specifically included:
S01, near infrared spectrum to stripe rust of wheat incubation period leaf sample are acquired, and obtain the near infrared spectrum of sample；
S02, the Stripe Rust DNA relative amount calculated in described stripe rust of wheat incubation period leaf sample；
Specifically, the calculation of the relative amount (PstDNA) of the Stripe Rust DNA in stripe rust of wheat incubation period leaf sample is:
S03, near infrared spectrum according to the relative amount of the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and described sample, build Stripe Rust DNA relative amount rating model.
It should be noted that, the present embodiment is build Stripe Rust DNA relative amount rating model by the aecidium DNA relative amount in the collection near infrared spectrum of stripe rust of wheat incubation period leaf sample, stripe rust of wheat incubation period leaf sample, but the present embodiment does not limit concrete vegetation type, the thought of the available the present embodiment of those skilled in the art, detects the disease of the other plant such as corn and soybean, Brassica campestris L.
Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade that the present embodiment provides, by utilizing near-infrared spectrum technique to gather the near infrared spectrum of stripe rust of wheat incubation period leaf sample, and utilize multiple fluorescence quantitative PCR technology, obtain the relative amount of stripe rust of wheat incubation period leaf sample Stripe Rust DNA, and pass through the near infrared spectrum of stripe rust of wheat incubation period leaf sample and the relative amount of Stripe Rust DNA, set up the causes of the near infrared spectrum of wheat leaf blade and the relative amount of Stripe Rust DNA, and utilize this causes to carry out quantitatively to the Stripe Rust amount in stripe rust of wheat incubation period blade to be detected, quickly, lossless, detect accurately, and the early stage detection for other plant disease provides reference.
It should be noted that the obtaining step of stripe rust of wheat incubation period leaf sample is:
(1) expanding propagation puccinia striiformis: will engrave virtuous 169 seeds moisturizing accelerating germination 24h under room temperature, select full and germinate the uniform program request of good seed in the seedling-growing container that diameter is 10cm, every basin program request 25 (plumule upwards and towards flowerpot center), then proceeds to the artificial climate indoor cultivation that ambient parameter is 14/10h alternation of light and darkness, intensity of illumination 10000lux, temperature 11～13 DEG C, relative humidity 60%～70%.When wheat seedling first lobus cardiacus is fully deployed, carry out the spray inoculation of puccinia striiformis.Take out No. 33 (CYR33) uredospores in the puccinia striiformis biological strain bar preserved in liquid nitrogen container, 40～45 DEG C of warm water activates 5min, then 4 DEG C of low temperature hydrated 12h.The tween of appropriate uredospore Yu 0.2% is configured to spore suspension.First gently smooth out with the fingers blade to remove top layer waxiness with finger-dipping clear water before inoculation, then utilize the spore suspension prepared to carry out spray inoculation, inoculate moisturizing 24h under the dark condition being placed on 10 DEG C.The artificial climate indoor being finally placed under above-mentioned condition are cultivated, rear 15d to be seeded (my god) the big volume production spore of Caulis et Folium Tritici aestivi of falling ill, collect Fresh spores.
(2) acquisition of stripe rust of wheat incubation period leaf sample: the spore suspension even spraying that the tween of CYR33 uredospore fresh for 3mg Yu 0.2% is made into 0.15mg/mL is inoculated in wheat seedling, inoculates 50 basins and supplies used by test.Gathering, every 24h, the wheat leaf blade that 60 size growing ways are consistent after inoculation, every two panels is a sample gathering spectrum, and every day is totally 30 samples.
Step S01 in above-described embodiment: " near infrared spectrum of leaf sample is acquired to the stripe rust of wheat incubation period, obtains the near infrared spectrum of sample ", is specially step S01`:
S01`, employing integrating sphere diffuse-reflectance method gather the near infrared spectrum of stripe rust of wheat incubation period leaf sample, obtain the near infrared spectrum of sample.
Specifically, the process of the near infrared spectrum gathering stripe rust of wheat incubation period leaf sample is:
It is cut into unqualified shape by often organizing stripe rust of wheat incubation period leaf sample, pours in the specimen cup that internal diameter is 20mm, at room temperature utilize MPA Fourier transform near infrared instrument to carry out near infrared spectra collection.Gathering spectroscopy mode is integrating sphere diffuse-reflectance, gathers 30 spectrum every time.Spectra collection ranges for 4000-12000cm-1, spectral resolution is 8cm-1(every spectrum comprises 2100 wavelength points altogether), scanning times 32 times.Whole gatherer process until uredospore break through blade epidermis (after inoculation 10d), now the incubation period terminates, altogether obtain 300 near infrared spectrums, it is thus achieved that near infrared light spectral curve as shown in Figure 3.
It should be noted that the often group stripe rust of wheat incubation period leaf sample having gathered spectrum loads in the grinding pipe of 2mL, put into-80 DEG C of preservations after numbering at once, for the extraction of follow-up stripe rust of wheat incubation period leaf sample DNA.
Step S02 in above-described embodiment: " calculating the Stripe Rust DNA relative amount in described stripe rust of wheat incubation period leaf sample ", specifically includes not shown following fine division step S021 to S024:
S021, extract healthy wheat leaf blade DNA, Stripe Rust uredospore DNA and described stripe rust of wheat incubation period leaf sample DNA respectively, obtain the content of described healthy wheat leaf blade DNA content, the content of described Stripe Rust uredospore DNA and described stripe rust of wheat incubation period leaf sample DNA；
S022, according to described healthy wheat leaf blade DNA content, described Stripe Rust uredospore DNA content, adopt multiple fluorescence quantitative PCR technology, set up the standard curve of the described healthy standard curve of wheat leaf blade DNA, described Stripe Rust uredospore DNA；
S023, content according to described stripe rust of wheat incubation period leaf sample DNA, utilize the standard curve of the described healthy standard curve of wheat leaf blade DNA, described Stripe Rust uredospore DNA, calculate the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and wheat leaf blade DNA；
S024, according to the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and wheat leaf blade DNA, calculate the relative amount of Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample.
Specifically, in the step S021 in above-described embodiment, for the process extracting healthy wheat leaf blade DNA, the extraction process of healthy wheat leaf blade DNA, Stripe Rust uredospore DNA and stripe rust of wheat incubation period leaf sample DNA is described:
(1) each addition 0.4g quartz sand, grinding bead, a 600 μ L buffer containing 2% cetyl trimethylammonium bromide (HexadecyltrimethylammoniumBromide, CTAB) in pipe are ground to the 2mL equipped with wheat leaf blade.
nullWherein，The manufacturing process of the 600 μ L buffer containing 2%CTAB is: 2gCTAB and 1g polyvinylpyrrolidone (polyvinylpyrrolidone，PVP)，It is separately added into three (methylol) aminomethane (Tris (hydroxymethyl) aminomethane of 10 μ L1M and pH=8.0，Tris-HCl)、2 μ L0.5M and pH=8.0 disodiumedetate (Ethylenediaminetetraaceticaciddisodiumsalt，EDTA)、28mL5M sodium chloride (Sodiumchloride，NaCl)，Then 100mL it is settled to，Carry out autoclave sterilization again，100 μ L beta-mercaptoethanols are added after cooling.
(2) put into and FastPrep-24 beveller grinds 40s with the grinding rate of 6.0m/s, grind twice, ice bath 5min during grinding, be then placed in water-bath 1h in 65 DEG C of water-baths, mix every 15min jog.
(3) take out grinding pipe, add chloroform/isoamyl alcohol that 600 μ L volume ratios are 24:1, shake into emulsus, with the centrifugal 10min of the centrifugal speed of 12000r/min.
(4) take supernatant in the sterile centrifugation tube that specification is 1.5mL, add the isopropanol of 0.6 times of volume-20 DEG C, shake up gently and put into-20 DEG C of standing 1h, with the centrifugal 10min of the centrifugal speed of 12000r/min, remove supernatant fraction；
(5) add the washing with alcohol of 500 μ L70%, rock gently, with the centrifugal 10min of the centrifugal speed of 12000r/min, remove supernatant fraction, dry.
(6) aseptic double-distilled water adding 50 μ L makes DNA dissolve, and then leaves under-20 DEG C of environment standby.
nullWhen multiple fluorescence quantitative PCR measures wheat leaf blade DNA，Upstream and downstream primer TAG2315F and TAG2473R adopts the (SandbergM such as Sandberg,LundbergL,FermM,Yman,IM.RealtimePCRforthedetectionanddiscriminationofcerealcontaminationinglutenfreefoods[J].EuropeanFoodResearchandTechnology,2003,217 (4): 344-349.) primer designed according to Triticum alcohol soluble protein gene (prolamingene) reported，Probe TAG-Pr1 by China Agricultural University plant disease epidemics laboratory Pan Yang etc. according to this sequential design (not yet delivering)；When multiple fluorescence quantitative PCR measures Stripe Rust DNA, upstream and downstream primer Pst-F and Pst-R and probe Pst-P adopts (Li Yong, the paddy medical centers such as Li Yong, Wu Boming, Jin Shelin, Cao Shiqin, Wang Xiaoming, Sun Zhenyu, Luo Yong, Ma Zhanhong. the foundation [J] of puccinia striiformis and the multiple TaqManReal-timePCR method of Powdery Mildew. Plant Pathology, 2015,45 (2): 205-210.) primer based on ITS sequence design reported and probe, as shown in table 1:
Table 1
The Real-timePCR reaction system adopted in multiple fluorescence quantitative PCR technology in above-described embodiment is: comprise Mg in 20 μ L reaction systems2+(25 μMs) 3.20 μ L, dideoxyribonucleotide triphosphate (deoxy-ribonucleosidetriphosphate, dNTP) (2500 μMs) 2.00 μ L, 10 × Buffer2.00 μ L, Taq enzyme (5U/ μ L) 0.60 μ L, the primer Pst-F of 10 μMs (, Pst-R, TAGF and TAGR) each 0.30 μ L, the each 0.25 μ L of probe (Pst-P and the TAG-Pr1 of 10 μMs), template DNA 2.00 μ L, add appropriate ddH2O so that Real-timePCR reaction system reaches 20 μ L.
The Real-timePCR amplified reaction program adopted in multiple fluorescence quantitative PCR technology in above-described embodiment is: carry out denaturation 3min under 95 DEG C of conditions, a circulation；Degeneration 20s is carried out under 94 DEG C of conditions；Anneal 30s when 56 DEG C；Under 72 DEG C of conditions, extend 30s, and detect fluorescence signal under this condition, 40 circulations.
The process of the standard curve setting up DNA in the step S022 in above-described embodiment is:
(1) the Stripe Rust DNA gradient dilution successively by the concentration known extracted in step S021 is 1,10-1、10-2、10-3、10-4ng/μL；The wheat leaf blade DNA gradient dilution successively of concentration known is 10,1,10-1、10-2Ng/ μ L, adopts multiple fluorescence quantitative PCR technology quantitative analysis and records Ct value.
(2) respectively with Stripe Rust uredospore DNA and healthy wheat leaf blade DNA concentration logarithm value for vertical coordinate, Ct value is abscissa, it is thus achieved that respective standard curve and equation of linear regression, as shown in Figure 4 and Figure 5.Wherein, the standard curve equation of Stripe Rust uredospore DNA is y=-0.3019x+7.4752 (R2=0.9926), wherein, y is Stripe Rust DNA concentration common logarithm (log10) value, and x is Ct value；The standard curve equation of healthy wheat leaf blade DNA is y=-0.3008x+9.2660 (R2=0.9989), wherein, y is wheat leaf blade DNA concentration common logarithm (log10) value, and x is Ct value.
The amplification efficiency of Stripe Rust uredospore DNA in the present embodiment and healthy wheat leaf blade DNA respectively 99.7% and 100.1%, amplification efficiency is all good.
The Stripe Rust DNA in calculating stripe rust of wheat incubation period leaf sample and the process of wheat leaf blade DNA in step S023 in above-described embodiment be:
Real-timePCR reaction system in above-described embodiment is utilized to carry out detection by quantitative to extracting, from least one set stripe rust of wheat incubation period leaf sample, the DNA obtained, and record Ct value, utilize the standard curve of the standard curve of wheat leaf blade DNA of foundation, Stripe Rust uredospore DNA in above-described embodiment, calculate the content of Stripe Rust DNA and wheat leaf blade DNA in sample.
The PstDNA in step S024 in above-described embodiment utilizes the computing formula of the PstDNA in above-described embodiment to be calculated obtaining.The PstDNA Day-to-day variability figure obtained is as shown in Figure 6, it can be seen that PstDNA increases over time, is exponentially increased.
The fit equation setting up PstDNA Day-to-day variability is y=0.0096e0 . 9287x, wherein, y is puccinia striiformis DNA relative amount in blade, and x is days post inoculation, and the coefficient of determination is R2=0.8784.Partial least square method is utilized to set up a multiple linear regression model, but owing to actual measurement Stripe Rust DNA relative amount ranges for 0.00385%～90.09%, first 6 days all in 0.2% scope, for making data as far as possible in normal distribution, Stripe Rust DNA relative amount value in wheat leaf blade is carried out Logarithm conversion process.Obtain the Stripe Rust relative amount logarithm value Day-to-day variability figure in stripe rust of wheat incubation period leaf sample as shown in Figure 7, it can be seen that the Stripe Rust relative amount value in sample sets up the coefficient of determination R of linear equation before and after Logarithm conversion processes with natural law (d)2Respectively 0.8784 and 0.8750, there is not large change, therefore, set up at model and process adopts equation below set up detection by quantitative model as chemical score and near infrared spectrum data after the Stripe Rust relative amount value in sample is changed:
It should be noted that before puccinia striiformis DNA relative amount is carried out Logarithm conversion process, it is necessary to it is multiplied by 105To ensure that chemical score is for just.
Step S03 in above-described embodiment: " near infrared spectrum according to the relative amount of the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and described sample builds Stripe Rust DNA relative amount rating model " specifically includes step S03`:
S03`, relative amount according to the Stripe Rust DNA in the near infrared spectrum of described sample and described stripe rust of wheat incubation period leaf sample, combination adopts quantitative partial least square method QPLS and support vector regression SVR, builds kQPLS-SVR rating model.
Specifically, the step S03` in the present embodiment specifically includes not shown following fine division step S03`1 to S03`3:
S03`1, randomly selecting m feature from the wavelength points spectral signature of the near infrared spectrum of described sample, and number of principal components is set to n, wherein, m, n are preset constant；
S03`2, according to described m feature and the described number of principal components being set to n, successively build k QPLS rating model；
S03`3, using the predictive value of described k QPLS rating model as variable, build SVR rating model, thus obtaining kQPLS-SVR rating model.
Specifically, the present embodiment also includes the effect of Stripe Rust DNA relative amount kQPLS-SVR rating model is evaluated, the step A1 to A4 including not shown:
A1, according to preset ratio, by the near infrared spectrum of described stripe rust of wheat incubation period leaf sample, be divided into training set and test set；
A2, relative amount according to the Stripe Rust DNA in described training set and described stripe rust of wheat incubation period leaf sample, combination adopts quantitative partial least square method QPLS and support vector regression SVR, builds kQPLS-SVR rating model；
A3, coefficient of determination R according to described training set, described test set2, calibration standard difference SEC, prediction standard deviation SEP, average relative error AARD and relative prediction deviation SEP, described kQPLS-SVR rating model is evaluated, obtains evaluation result；
A4, according to described evaluation result, select optimum kQPLS-SVR rating model.
As shown in Figure 8, the algorithm flow that puccinia striiformis DNA relative amount kQPLS-SVR rating model is set up is: first, randomly choose m feature, number of principal components is set to n from 2100 wavelength points spectral signatures, build a QPLS model, build k QPLS model according to the method altogether；Secondly, using above-mentioned k constructed QPLS model predication value as variable, it is used for building SVR model, thus obtaining kQPLS-SVR rating model.When building SVR model, set up SVR model with RBF (radialbasisfunction, RBF) as kernel function, utilize grid-search algorithms (gridsearchalgorithm), 2-8～28Punishing parameter C and kernel functional parameter g with 0.8 for step search optimization in scope, the parameter search result when mean square error (meansquarederror, MSE) of preference pattern is minimum is as model optimized parameter.The wavelength points characteristic number m randomly choosed is respectively set to 700 and 1400, and number of principal components n when building QPLS model is respectively set to 4,8 and 12, and constructed QPLS pattern number k is respectively set to 5,10 and 15.The process that more than calculates all carries out in software MATLAB7.8.0 (R2009a).
It should be noted that the coefficient of determination R of the modeling effect utilization training set of built puccinia striiformis DNA relative amount kQPLS-SVR rating model and test set2, calibration standard difference SEC, prediction standard deviation SEP, average relative error AARD be evaluated with relative prediction deviation RPD.Wherein, R2> 0.5 show build rating model can be used for actual screening, R2Degree of accuracy closer to 1 rating model showing structure is more high；The degree of accuracy of rating model built is also relevant to RPD, and its value is 2.0～3.0 is the minimum requirements that can be used for actual screening, and 3.0～5.0 show that model has predictability, RPD > 5.0 show that rating model is more excellent；SEC, SEP and AARD are more little, it was shown that rating model accuracy is more high.SEC, SECV, SEP, AARD value is more little, illustrates that the accuracy of rating model and predictability are more good.Optimum kQPLS-SVR rating model is selected according to These parameters.
Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade that the present embodiment provides, adopts QPLS and SVR by combining, and builds the kQPLS-SVR rating model of Stripe Rust DNA relative amount.And, by utilizing near infrared spectrum training set and test set coefficient of determination R2, the effect of the Stripe Rust DNA relative amount kQPLS-SVR rating model of structure is evaluated by calibration standard difference SEC, prediction standard deviation SEP, average relative error AARD and relative prediction deviation RPD, and select best Stripe Rust DNA relative amount kQPLS-SVR rating model according to evaluation result, further increasing the accuracy of Stripe Rust DNA relative amount kQPLS-SVR rating model.
It should be noted that, according to the ratio of 3:1 in the present embodiment, the near infrared spectrum of sample is divided into training set and test set, but the present embodiment does not limit concrete division proportion, those skilled in the art according to practical situation, can set the division proportion of the near infrared spectrum of sample.
It should be noted that, it the present embodiment is the relative amount of the original near infrared spectrum according to the stripe rust of wheat incubation period leaf sample gathered and Stripe Rust DNA, building Stripe Rust DNA relative amount rating model, the measurement effect of constructed rating model is better than the rating model built according to the near infrared spectrum after processing.
The kQPLS-SVR the rating model below original near infrared spectrum according to stripe rust of wheat incubation period blade built and the effect according to the kQPLS-SVR rating model of the near infrared spectrum structure after processing compare as shown in table 2, table 3, table 4, table 5:
Wherein, the effect data of the table 2 kQPLS-SVR rating model constructed by the original spectrum according to stripe rust of wheat incubation period blade:
Table 2
Table 3 is the effect data adopting additional dispersion bearing calibration (multiplicationscattercorrection, MSC) that original near infrared spectrum carries out the kQPLS-SVR rating model constructed by pretreatment:
Table 3
Table 4 is the effect data adopting standard normal variable alternative approach (standardnormalizedvariate, SNV) that original near infrared spectrum carries out the kQPLS-SVR rating model constructed by pretreatment:
Table 4
Table 5 is the effect data adopting vector method for normalizing (vectornormalization, VN) that original near infrared spectrum carries out the kQPLS-SVR rating model constructed by pretreatment:
Table 5
By the data in above-mentioned table 2, table 3, table 4 and table 5, it can be seen that adopt original near infrared spectrum and MSC and SNV pretreatment near infrared spectrum built kQPLS-SVR rating model result all better.Adopt the coefficient of determination R of the built kQPLS-SVR rating model training set of VN pretreatment near infrared spectrum and test set2Less, and RPD value is also less.Adopting the built kQPLS-SVR rating model of SNV pretreatment near infrared spectrum to choose number of principal components is 4, little compared with additive method, it is understood that there may be the situation of insufficient matching (Underfit), makes model prediction accuracy.Adopt the test set R of the built kQPLS-SVR rating model of MSC pretreatment near infrared spectrum2It is 0.8730, less than adopting original near infrared spectrum institute established model.Therefore, using built for original for employing near infrared spectrum kQPLS-SVR rating model (selected characteristic number be 700, number of principal components be 8, set up 5 QPLS models) as optimum kQPLS-SVR rating model.
Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade that the present embodiment provides, QPLS and SVR is adopted by combining, build the optimum kQPLS-SVR rating model of the Stripe Rust DNA relative amount obtained, the measurement effect of Stripe Rust DNA relative amount in wheat leaf blade is better than the measurement effect of other rating model.Owing to selected optimum kQPLS-SVR rating model uses original near infrared spectrum data, therefore, based on original near infrared spectrum data, being utilized respectively QPLS and SVR method and set up puccinia striiformis DNA relative amount rating model, model result is listed in table 6.
Table 6
It should be noted that be utilized respectively QPLS and SVR to set up puccinia striiformis DNA relative amount rating model, and compare with the optimum kQPLS-SVR rating model of the foundation utilizing kQPLS-SVR method, specifically, utilize coefficient of determination R2, the effect of three kinds of rating models such as optimum kQPLS-SVR rating model, QPLS rating model and SVR rating model is evaluated by calibration standard difference SEC, prediction standard deviation SEP, average relative error AARD and relative prediction deviation RPD.Be can be seen that by the data in table 6, the optimum kQPLS-SVR rating model that builds in the present embodiment (adopt original near infrared spectrum, selected characteristic number be 700, number of principal components be 8, set up 5 QPLS models), is better than QPLS rating model and the measurement effect of SVR rating model to the measurement effect of the relative amount of Stripe Rust DNA in stripe rust of wheat incubation period blade.Therefore, select kQPLS-SVR rating model as Stripe Rust DNA relative amount rating model in stripe rust of wheat incubation period blade.
It should be noted that, when utilizing QPLS and SVR method to set up puccinia striiformis DNA relative amount rating model, used number of principal components is to be determined by calculating predictive residual error sum of squares PRESS (predictionresidualerrorsumofsquare, Press).Usually, when PRESS value is minimum, it is possible to corresponding number of principal components is best, but is also possible to cause overfitting.Therefore adopt F statistic law to determine best number of principal components, F statistic law following (f* is the number of principal components that minimum PRESS value is corresponding): F (f)=PRESS (f)/PRESS (f*), best f is less than f*, little as far as possible and meet F (f) < F α, m, m (α=0.25, m is degree of freedom) condition (Lu Wanzhen, Yuan Hongfu, Xu Guangtong, Qiang Dongmei. NIR spectra analysis [M]. Beijing: Sinopec publishing house .2000).
Stripe Rust DNA relative amount measuring method in a kind of wheat leaf blade that the present embodiment provides, the relative amount of original near infrared light spectrum information and Stripe Rust DNA by adopting stripe rust of wheat incubation period leaf sample, build Stripe Rust DNA relative amount kQPLS-SVR rating model, the effect of this model is better, further, the accuracy measuring the result obtained is higher.
nullPresent invention achieves according to the near infrared spectrum gathering the stripe rust of wheat incubation period blade obtained，Utilize Stripe Rust DNA relative amount rating model in the stripe rust of wheat incubation period blade set up，Can carry out the stripe rust of wheat incubation period infects the quantitative fast automatic detecting of bacterium amount，It is achieved thereby that stripe rust of wheat is quantitative、Lossless、Quickly、Automatically early stage detection，It is possible with the present invention to set up incubation period of other diseases and infect bacterium amount rating model，Provide a kind of quantitative、Lossless、Quick disease technique for detection，The quantitatively quick early stage realizing disease infestation bacterium amount and disease measures，A situation arises and bacterium amount to be easy to grasp field diseases as early as possible，For suppressing the accumulation of bacterium amount、Reduce transmission of pathogen body quantity、The preventing and treating of fixed point early of disease、The formulation of prediction and warning and macroscopic view prevention and control strategy provides foundation，Can for disease management subtracts medicine potentiation offer brute force support.The present invention also provides foundation for research and development portable plant disease detection by quantitative near infrared spectrometer and plant disease detection by quantitative sensor.
One of ordinary skill in the art will appreciate that: various embodiments above only in order to technical scheme to be described, is not intended to limit；Although the present invention being described in detail with reference to foregoing embodiments, it will be understood by those within the art that: the technical scheme described in foregoing embodiments still can be modified by it, or wherein some or all of technical characteristic is carried out equivalent replacement；And these amendments or replacement, do not make the essence of appropriate technical solution depart from the scope of the claims in the present invention.
Claims (7)
1. Stripe Rust DNA relative amount measuring method in a wheat leaf blade, it is characterised in that described method includes:
Obtain the near infrared light spectrum information of stripe rust of wheat incubation period blade to be measured；
Near infrared light spectrum information according to described stripe rust of wheat incubation period blade to be measured, application rating model determines the Stripe Rust DNA relative amount corresponding with the near infrared light spectrum information of described stripe rust of wheat incubation period blade to be measured；Described rating model is the model representing the corresponding relation between near infrared light spectrum information and Stripe Rust DNA relative amount.
2. method according to claim 1, it is characterised in that before the near infrared light spectrum information of described acquisition stripe rust of wheat incubation period to be measured blade, described method also includes:
Build described rating model, specifically include:
To the stripe rust of wheat incubation period, the near infrared spectrum of leaf sample is acquired, and obtains the near infrared spectrum of sample；
Calculate the Stripe Rust DNA relative amount in described stripe rust of wheat incubation period leaf sample；
Relative amount according to the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and the near infrared spectrum of described sample, build Stripe Rust DNA relative amount rating model.
3. method according to claim 2, it is characterised in that the described near infrared spectrum to stripe rust of wheat incubation period leaf sample is acquired, and obtains the near infrared spectrum of sample, including:
Adopt integrating sphere diffuse-reflectance method to gather the near infrared spectrum of stripe rust of wheat incubation period leaf sample, obtain the near infrared spectrum of stripe rust of wheat incubation period leaf sample.
4. method according to claim 2, it is characterised in that the Stripe Rust DNA relative amount in leaf sample of described calculating described stripe rust of wheat incubation period, including:
Extract healthy wheat leaf blade DNA, Stripe Rust uredospore DNA and described stripe rust of wheat incubation period leaf sample DNA respectively, obtain the content of described healthy wheat leaf blade DNA content, the content of described Stripe Rust uredospore DNA and described stripe rust of wheat incubation period leaf sample DNA；
According to described healthy wheat leaf blade DNA content, described Stripe Rust uredospore DNA content, adopt multiple fluorescence quantitative PCR technology, set up the standard curve of the described healthy standard curve of wheat leaf blade DNA, described Stripe Rust uredospore DNA；
Content according to described stripe rust of wheat incubation period leaf sample DNA, utilize the standard curve of the described healthy standard curve of wheat leaf blade DNA, described Stripe Rust uredospore DNA, calculate the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and wheat leaf blade DNA；
According to the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and wheat leaf blade DNA, calculate the relative amount of Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample.
5. method according to claim 2, it is characterised in that the near infrared spectrum of the described relative amount according to the Stripe Rust DNA in described stripe rust of wheat incubation period leaf sample and described sample, builds Stripe Rust DNA relative amount rating model, including:
The relative amount of the Stripe Rust DNA near infrared spectrum according to described sample and described stripe rust of wheat incubation period leaf sample, combination adopts quantitative partial least square method QPLS and support vector regression SVR, builds kQPLS-SVR rating model.
6. method according to claim 5, it is characterized in that, the relative amount of the Stripe Rust DNA in the described near infrared spectrum according to described sample and described stripe rust of wheat incubation period leaf sample, combination adopts quantitative partial least square method QPLS and support vector regression SVR, build kQPLS-SVR rating model, including:
Randomly selecting m feature from the wavelength points spectral signature of the near infrared spectrum of described stripe rust of wheat incubation period leaf sample, and number of principal components is set to n, wherein, m, n are preset constant；
According to described m feature and the described number of principal components being set to n, building k QPLS rating model successively, wherein, k is preset constant；
Using the predictive value of described k QPLS rating model as variable, build SVR rating model, thus obtaining kQPLS-SVR rating model.
7. method according to claim 5, it is characterised in that described method also includes:
According to preset ratio, by the near infrared spectrum of described stripe rust of wheat incubation period leaf sample, it is divided into training set and test set；
Relative amount according to the Stripe Rust DNA in described training set and described stripe rust of wheat incubation period leaf sample, combination adopts quantitative partial least square method QPLS and support vector regression SVR, builds kQPLS-SVR rating model；
Coefficient of determination R according to described training set, described test set2, calibration standard difference SEC, prediction standard deviation SEP, average relative error AARD and relative prediction deviation RPD, described kQPLS-SVR rating model is evaluated, obtains evaluation result；
According to described evaluation result, select optimum kQPLS-SVR rating model.
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| CN113155747B (en) * | 2021-01-15 | 2022-12-06 | 西安科技大学 | Method for constructing fractional order differential spectral index and monitoring wheat stripe rust thereof |
| CN113567392A (en) * | 2021-07-20 | 2021-10-29 | 西北农林科技大学 | Wheat airborne pathogenic bacterium spore rapid nondestructive identification method based on near infrared spectrum |
| CN117420095A (en) * | 2023-12-15 | 2024-01-19 | 乐比(广州)健康产业有限公司 | Nasal spray ingredient detection method |
| CN117420095B (en) * | 2023-12-15 | 2024-03-01 | 乐比(广州)健康产业有限公司 | Nasal spray ingredient detection method |
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