CN105424636B - A kind of quick determination method of control pollution condition and its application - Google Patents
A kind of quick determination method of control pollution condition and its application Download PDFInfo
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- CN105424636B CN105424636B CN201511010212.9A CN201511010212A CN105424636B CN 105424636 B CN105424636 B CN 105424636B CN 201511010212 A CN201511010212 A CN 201511010212A CN 105424636 B CN105424636 B CN 105424636B
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- 238000000034 method Methods 0.000 title claims abstract description 26
- 241000233866 Fungi Species 0.000 claims abstract description 20
- 238000001514 detection method Methods 0.000 claims abstract description 13
- 238000000513 principal component analysis Methods 0.000 claims abstract description 13
- 230000002538 fungal effect Effects 0.000 claims abstract description 12
- 238000012795 verification Methods 0.000 claims abstract description 12
- 238000004458 analytical method Methods 0.000 claims abstract description 10
- 238000004611 spectroscopical analysis Methods 0.000 claims abstract description 10
- 238000004483 ATR-FTIR spectroscopy Methods 0.000 claims abstract description 8
- 238000010239 partial least squares discriminant analysis Methods 0.000 claims abstract description 7
- 241000894007 species Species 0.000 claims abstract description 6
- 239000000284 extract Substances 0.000 claims abstract description 4
- 241000132177 Aspergillus glaucus Species 0.000 claims description 53
- 238000011109 contamination Methods 0.000 claims description 25
- 241000223221 Fusarium oxysporum Species 0.000 claims description 19
- 238000001228 spectrum Methods 0.000 claims description 8
- 241000131314 Aspergillus candidus Species 0.000 claims description 7
- 230000003595 spectral effect Effects 0.000 claims description 7
- 241001123663 Penicillium expansum Species 0.000 claims description 6
- 244000005700 microbiome Species 0.000 abstract description 2
- 241000209094 Oryza Species 0.000 description 47
- 235000007164 Oryza sativa Nutrition 0.000 description 47
- 235000009566 rice Nutrition 0.000 description 47
- 239000000843 powder Substances 0.000 description 22
- 235000013339 cereals Nutrition 0.000 description 17
- 239000000725 suspension Substances 0.000 description 13
- 238000002329 infrared spectrum Methods 0.000 description 11
- 241000894006 Bacteria Species 0.000 description 10
- 230000004069 differentiation Effects 0.000 description 8
- 239000001963 growth medium Substances 0.000 description 6
- 239000001965 potato dextrose agar Substances 0.000 description 5
- 230000001954 sterilising effect Effects 0.000 description 5
- 241000228212 Aspergillus Species 0.000 description 4
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 description 4
- 241000589516 Pseudomonas Species 0.000 description 4
- 238000004659 sterilization and disinfection Methods 0.000 description 4
- 238000005033 Fourier transform infrared spectroscopy Methods 0.000 description 3
- 241000228143 Penicillium Species 0.000 description 3
- 238000009629 microbiological culture Methods 0.000 description 3
- 241000196324 Embryophyta Species 0.000 description 2
- 241000656145 Thyrsites atun Species 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 2
- 150000001408 amides Chemical class 0.000 description 2
- 230000001580 bacterial effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 235000011187 glycerol Nutrition 0.000 description 2
- 238000011081 inoculation Methods 0.000 description 2
- 235000012054 meals Nutrition 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- UHPMCKVQTMMPCG-UHFFFAOYSA-N 5,8-dihydroxy-2-methoxy-6-methyl-7-(2-oxopropyl)naphthalene-1,4-dione Chemical compound CC1=C(CC(C)=O)C(O)=C2C(=O)C(OC)=CC(=O)C2=C1O UHPMCKVQTMMPCG-UHFFFAOYSA-N 0.000 description 1
- 229920001817 Agar Polymers 0.000 description 1
- 229910014572 C—O—P Inorganic materials 0.000 description 1
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 description 1
- 241001136487 Eurotium Species 0.000 description 1
- 241000223218 Fusarium Species 0.000 description 1
- 241000228150 Penicillium chrysogenum Species 0.000 description 1
- 244000061456 Solanum tuberosum Species 0.000 description 1
- 235000002595 Solanum tuberosum Nutrition 0.000 description 1
- 239000008272 agar Substances 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 230000009514 concussion Effects 0.000 description 1
- 238000012864 cross contamination Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
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- 238000010790 dilution Methods 0.000 description 1
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- 238000002474 experimental method Methods 0.000 description 1
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- 150000002304 glucoses Chemical class 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 238000004128 high performance liquid chromatography Methods 0.000 description 1
- 230000003053 immunization Effects 0.000 description 1
- 238000002649 immunization Methods 0.000 description 1
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Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
Abstract
The present invention provides quick determination method and its application of a kind of control pollution condition, is related to microorganism detection field.The method, includes the following steps：The grain that pollution has control fungi is uniformly mixed with sterile grain respectively, obtains polluting the grain samples of each control fungi or the grain samples of pollution various concentrations control fungi；Using ATR-FTIR Spectrometry instrument, infrared spectrogram and data of the collection pollution each sample in characteristic wave bands；Principal component analysis is carried out to the ir data of each sample, extracts principal component score value, establishing different classes of or various concentrations fungi with linear discriminant analysis or partial least squares discriminant analysis differentiates model, and verification differentiates the reliability of model；Gather infrared spectrogram and data of the grain samples to be measured in the characteristic wave bands, fungal species or the concentration for determining to pollute in grain samples to be measured using the model.The method of the present invention rapidly can carry out contaminated mold in grain qualitative and substantially quantitative.
Description
Technical field
The present invention relates to the method with infrared spectrum detection microorganism, a kind of quick detection side of control pollution condition
Method and its application.
Background technology
Grain easily moldy metamorphism under optimum conditions, not only causes economic loss, and the secondary generation of the malicious mould of most productions
Thank to product serious threat human and livestock health.At present, the detection method of mould contamination mainly includes in grain：The method of plate culture count,
High performance liquid chromatography, internal standard method for gas chromatography method, PCR and immunization etc., however, the above method exists or operates numerous
It is trivial, sensitivity is low, or it is costly and time consuming long the deficiencies of, it is difficult in real time monitoring grain in mould upgrowth situation.Therefore, it is badly in need of
Develop a kind of detection method that can quickly identify contaminated mold in grain.
The content of the invention
The purpose of the invention is to overcome, mould contamination procedure is complicated in existing detection grain, take it is long or into
The problem of this is higher, there is provided a kind of to carry out qualitative and substantially quantitative method to contaminated mold in grain rapidly.
The present invention adopts the following technical scheme that realization.
The quick determination method of fungal contamination situation, includes the following steps in a kind of grain：
(1) grain that pollution has control fungi is uniformly mixed with sterile grain respectively, obtains polluting each control fungi
Grain samples or the grain samples of pollution various concentrations control fungi；
(2) use ATR-FTIR Spectrometry instrument, the grain samples of each control fungi of collection pollution or
Pollute infrared spectrogram and data of the grain samples in characteristic wave bands of various concentrations control fungi；The characteristic wave bands are 4000
~800cm-1And/or 10000~4000cm-1Wave band；
(3) principal component analysis is carried out to the ir data of each sample, extracts principal component score value, with linear discriminant point
Analysis or partial least squares discriminant analysis establish different classes of or various concentrations fungi and differentiate model, and verification differentiates the reliable of model
Property；
(4) infrared spectrogram and data of the grain samples to be measured in the characteristic wave bands are gathered, is established using in step (3)
Model determine fungal species or the concentration polluted in grain samples to be measured.
The characteristic wave bands are 1800~900cm-1, 1800~1485cm-1With 10000~4000cm-1One or both of
Band above.
Using the reliability for staying cross verification verification to differentiate model.
In step (2) during collection infrared spectrogram, spectral resolution 4cm-1, each wave band to each sample at least
Detection 3 times, takes the averaged spectrum of each sample；In each detection of sample, at least scan 32 times.
The principal component analysis refers to two-dimensional principal component analysis.
Every kind of grain samples take the Duplicate Samples of more than 5.
The control fungi is Aspergillus glaucus, aspergillus candidus, yellow grey Penicillium notatum, penicillium expansum, Fusarium oxysporum.
The fungal species polluted in grain can be quickly analyzed using the method for the present invention and carry out substantially quantitative, operation letter
Just, take it is short, cost is relatively low.
Brief description of the drawings
The ATR-FTIR spectrograms of 7 kinds of mycotic spore suspension samples of Fig. 1.
PCA shot charts (1800~the 900cm of 7 kinds of mycotic spore suspension samples of Fig. 2-1)。
LDA shot charts (1800~900cm of 7 kinds of mycotic spore suspension sample infrared spectrum information of Fig. 3-1)。
Fig. 4 various concentrations Aspergillus glaucus pollutes PCA shot charts (1800~900cm of rice sample-1), each icon distinguishes table
Show the quality of the Aspergillus glaucus paddy powder added in sterile paddy, the pure bacteria control paddy powder quality for representing addition is 0.
Fig. 5 various concentrations Aspergillus glaucus pollutes LDA shot charts (1800~900cm of rice sample-1), each icon distinguishes table
Show the quality of the Aspergillus glaucus paddy powder added in sterile paddy, the pure bacteria control paddy powder quality for representing addition is 0.
Fig. 6 various concentrations Aspergillus glaucus pollutes PCA shot charts (1800~1485cm of rice sample-1), each icon difference
Represent the quality of Aspergillus glaucus paddy powder added in sterile paddy, the bacteria control paddy powder quality of pure expression addition is
0。
Fig. 7 various concentrations Aspergillus glaucus pollutes LDA shot charts (1800~1485cm of rice sample-1), each icon difference
Represent the quality of Aspergillus glaucus paddy powder added in sterile paddy, the bacteria control paddy powder quality of pure expression addition is
0。
Fig. 8 various concentrations Aspergillus glaucus pollutes PCA shot charts (10000~4000cm of rice sample-1), each icon difference
Represent the quality of Aspergillus glaucus paddy powder added in sterile paddy, the bacteria control paddy powder quality of pure expression addition is
0。
Fig. 9 various concentrations Aspergillus glaucus pollutes LDA shot charts (10000~4000cm of rice sample-1), each icon difference
Represent the quality of Aspergillus glaucus paddy powder added in sterile paddy, the bacteria control paddy powder quality of pure expression addition is
0。
LDA shot charts (1800~900cm of the different mould contamination rice samples of tri- kinds of Figure 10-1)。
LDA shot charts (1800~1485cm of the different mould contamination rice samples of tri- kinds of Figure 11-1)。
LDA shot charts (10000~4000cm of the different mould contamination rice samples of tri- kinds of Figure 12-1)。
LDA shot charts (1800~900cm of a variety of different mould contamination rice samples of Figure 13-1), icon representation is each sterile
The quality that Aspergillus glaucus 1 pollutes paddy powder is added in paddy.
LDA shot charts (1800~1485cm of a variety of different mould contamination rice samples of Figure 14-1), icon representation is each sterile
The quality that Aspergillus glaucus 1 pollutes paddy powder is added in paddy.
LDA shot charts (10000~4000cm of a variety of different mould contamination rice samples of Figure 15-1), each nothing of icon representation
The quality that Aspergillus glaucus 1 pollutes paddy powder is added in bacterium paddy.
Embodiment
With reference to embodiment, the present invention will be further described, it should be understood that these embodiments are only used for illustration
Purpose, be in no way intended to limit protection scope of the present invention.Chosen in the part Common detrimental mould in paddy it is one or more into
Row experiment：Including：(ash is abbreviated as purchased from the Aspergillus glaucus CGMCC3.3975 of China General Microbiological culture presevation administrative center
Green aspergillus 1), Aspergillus glaucus CGMCC3.0100 (being abbreviated as Aspergillus glaucus 2) and yellow grey mould CGMCC3.5243, purchased from Chinese work
The aspergillus candidus CICC40475 (being abbreviated as aspergillus candidus) of industry Microbiological Culture Collection administrative center, mould CICC41489 (with
Under be abbreviated as mould 1), penicillium expansum CICC41063 (being abbreviated as penicillium expansum), Fusarium oxysporum CICC2532 (be abbreviated as point
Fusarium oxysporum 1), Fusarium oxysporum CICC41029 (being abbreviated as Fusarium oxysporum 2), purchased from Chinese agriculture Microbiological Culture Collection
Mould ACCC30106 (being abbreviated as mould 2), the Fusarium oxysporum ACCC31369 (being abbreviated as Fusarium oxysporum 3) of administrative center.
The infrared spectrum detection of 1 seven kinds of fungal spore suspensions of embodiment
1. the culture of mould
Cultivated using potato dextrose agar (PDA).500mL triangular flasks load 400mL potato glucoses
Agar medium, after 121 DEG C sterilize 20min, when culture medium is cooled to 55 DEG C or so, is poured into what is sterilized by culture medium
It is after the culture medium solidification in culture dish, Aspergillus glaucus 1, aspergillus candidus, yellow grey mould, extension is blue or green in batch cultur ware
Mould, Fusarium oxysporum 1, Fusarium oxysporum 2, Fusarium oxysporum 3 are inoculated into PDA culture medium respectively, are cultivated in the incubator, training
It is 28 DEG C to support temperature.
2. harvest and the processing of spore suspension
The mould after 5d will be cultivated to take out, taking the glycerine water solution that 4mL sterilizes, (glycerine and water volume ratio are 1:10) in training
Primary surface is supported, after slight concussion, the spore suspension of media surface is pipetted in EP pipes, it is spare to be placed in -20 DEG C of preservations.
3. count
Spore suspension is placed on miniature vortex mixed instrument and vibrates 10s, takes 50uL spore suspensions in blood counting chamber
On, observe and count under 30 biomicroscopes of EX (Shun's space optics science and technology (group) Co., Ltd), seven kinds of mycotics spore are initial
The concentration of suspension is respectively：Penicillium expansum：(5.5±0.3)×106Cfu/mL, yellow ash mould：(5.4±0.2)×106cfu/
ML, Fusarium oxysporum 1：(1.9±0.1)×107Cfu/mL, Fusarium oxysporum 2：(1.4±0.1)×107Cfu/mL, sharp spore sickle
Knife bacterium 3：(6.9±0.2)×106Cfu/mL, Aspergillus glaucus 1：(3.4±0.3)×106Cfu/mL, aspergillus candidus：(1.1±
0.2)×107Cfu/mL, i.e., the concentration comparable of seven kinds mycotic spore suspension.It is verification ATR-FTIR specific to mould spectrum
And the influence of different spore suspension concentration, 10 times and 20 times are diluted to above sample respectively, each dilution factor takes three to put down
Row sample, obtains 63 parts of samples, is detected analysis altogether.
4.ATR-FTIR spectra collections
Using the FTIR instrument (Fourier Transform Infrared Spectrometer, model TENSOR27) of German Brooker company, with reference to red
Outer ATR (decay total reflection) annex (Pike companies, the U.S.) gathers the infrared spectrum information of 63 parts of samples.First scanning background is (empty
Gas), the sample for then pipetting 4uL is detected on infrared ATR annexes, is scanned 32 times, resolution ratio 4cm-1, spectral region
4000~800cm-1, each sample at least detects 3 times, takes average spectrum to model.Different sample rooms need to be wiped flat with absolute ethyl alcohol
Platform is to avoid cross contamination.
Fig. 1 is the ATR-FTIR spectrograms of 63 parts of samples.Spectrum figure analysis is understood, in 3700~2996cm-1Place be with
The related absorption of O-H, N-H stretching vibration, 1800~1450cm-1Place is the absorption on II band of protein amide Ⅰ and acid amides,
1185~900cm-1Locate the stretching vibration band for C-O-C and C-O-P.Examine and understand, the spectrogram of different mould samples exists
1800~900cm-1There is some difference, shows that there are nuance for its internal component.
5. data analysis
The spectroscopic data of all samples is analyzed using TQAnalyst v6, SPSS 16.0 software, including：With
TQAnalyst v6 carry out original ir data principal component analysis, extraction each sample original infrared spectrum principal component point
Value, then principal component score value is imported into 16.0 softwares of SPSS, be respectively adopted partial least squares discriminant analysis (PLS-DA) and
Linear discriminant analysis (LDA), which is established, differentiates model.Finally use and stay a cross verification to verify each discriminating model performance.
Principal component analysis refers to two-dimensional principal component analysis.
Fig. 2 is the shot chart of the first two principal component of 63 parts of sample spectra information.The results show that from the point of view of Pseudomonas, sharp spore
Difference between 3 kinds of Fusarium, Penicillium and aspergillus Pseudomonas is more obvious, and aspergillus class sample can distinguish over other 2 classes completely.
In addition to the sample from Penicillium mixes with other classifications individually, most of sample can be distinguished well.
The Clustering Tendency for further looking at 7 class mould samples is understood, except 3 kinds of Fusarium oxysporum samples and yellow grey mould sample room exist
Outside partly overlapping, remaining 3 kinds of mould can be distinguished well.The result shows that the Infrared spectra adsorption of different mould sample suspensions
Intensity is distinct, and PCA can extract the different information of different sample rooms, is identified using ATR-FTIR methods different mould in paddy
Bacterium has feasibility.
Fig. 3 is the LDA function shot charts of 7 kinds of mycotic spore infrared spectrum information.The results show that different classes of mould sample
Position in the horizontal direction is apart from each other, and difference is obvious, in addition to occurring partly overlapping between Eurotium between Penicillium, remaining
Sample can be distinguished completely, its result is better than PCA.The discriminating model established with linear discriminant analysis, using staying an interaction
The reliability of the model is evaluated in verification, and the results are shown in Table 1, overall to differentiate that accuracy is 87.1%, wherein only Fusarium oxysporum 3
Differentiation accuracy it is relatively low, 3 samples are mistaken for Fusarium oxysporum 1, remaining result is all higher than or equal to 80%.Fusarium oxysporum 1
It is 100% with the differentiation accuracy highest of yellow grey mould.In addition, examining discovery, erroneous judgement occurs in different Pseudomonas
Interior, the differentiation accuracy between 3 class Pseudomonas is all 100%.
The LDA models of 17 kinds of mycotic spore suspension samples of table stay a validation-cross result
Established with PLS-DA discriminant analyses and differentiate model, the results are shown in Table 2 for differentiation of the model to each sample.As a result
It has been shown that, model is optimal to the discrimination precision of two class sample of Fusarium oxysporum 1 and Aspergillus glaucus, to Fusarium oxysporum 3, penicillium expansum
It is slightly worse with the precision of aspergillus candidus.Between the differentiation accuracy of 7 class samples is 79.2%~99.1%, ensemble average differentiates correct
Rate is 87.3%, similar with LDA methods.
27 class mould sample of table stays a validation-cross PLS-DA Model checking results
This example demonstrates that identify that the species of fungi and concentration are feasible in paddy using the method for the present invention.
The qualitative and quantitative detection of Aspergillus glaucus is polluted in 2 paddy of embodiment
1. the preparation of the rice sample containing Aspergillus glaucus：Aspergillus glaucus 1 is inoculated into the sterile paddy of irradiated sterilizing
On in 28 DEG C of cultures, the tenth day paddy for taking out culture after inoculation, with high speed Universal pulverizer (model FW100, Tianjin it is safe this
Special Instrument Ltd.) crush it is spare；It is at the same time that the sterile paddy meal of irradiation sterilization is broken as control rice sample.In aseptic rice
Paddy powder 2g, 5g, 10g, 20g and 50g obtained above containing Aspergillus glaucus are separately added into paddy, is made after mixing
Rice sample containing various concentrations Aspergillus glaucus, the gross mass of every part of rice sample is 50g, is trained through PDA culture medium tradition
Support and count, the Aspergillus glaucus quantity polluted in each concentration rice sample is respectively 770,1 300,3 500,5 000 and 92
000cfu/g。
2. the collection and analysis of ir data：
Using the FTIR instrument (model TENSOR 27) of German Brooker company, with reference to ATR annexes (Pike companies, the U.S.)
Above-mentioned each rice sample (including control rice sample) is directly gathered in the ir data of characteristic wave bands, herein characteristic wave
Section refers to 1800~900cm-1, 1800~1485cm-1With 10000~4000cm-1Wave band.
The spectroscopic data of all samples is analyzed using TQAnalyst v6, SPSS 16.0 software, including：With
TQAnalyst v6 carry out original ir data principal component analysis, extraction each sample original infrared spectrum principal component point
Value, then principal component score value is imported into 16.0 softwares of SPSS, be respectively adopted partial least squares discriminant analysis (PLS-DA) and
Linear discriminant analysis (LDA), which is established, differentiates model.Finally use and stay a cross verification to verify each discriminating model performance.
Principal component analysis refers to two-dimensional principal component analysis.
Fig. 4 and Fig. 5 is in 1800~900cm respectively-1Wave band various concentrations Aspergillus glaucus pollutes the PCA scores of rice sample
Figure and LDA shot charts, table 3 is in 1800~900cm-1The LDA models of various concentrations Aspergillus glaucus pollution rice sample stay a friendship
Mutual verification result；
3 various concentrations Aspergillus glaucus of table pollution rice sample LDA models stay a validation-cross result (1800~
900cm-1)
Fig. 6 and Fig. 7 is in 1800~1485cm respectively-1The PCA of wave band various concentrations Aspergillus glaucus pollution rice sample is obtained
Component and LDA shot charts, table 4 are in 1800~1485cm-1The LDA models of various concentrations Aspergillus glaucus pollution rice sample stay one
Validation-cross result；
4 various concentrations Aspergillus glaucus of table pollution rice sample LDA models stay a validation-cross result (1800~
1485cm-1)
Fig. 8 and Fig. 9 is in 10000~4000cm respectively-1The PCA of wave band various concentrations Aspergillus glaucus pollution rice sample is obtained
Component and LDA shot charts, table 5 are in 10000~4000cm-1The LDA models of various concentrations Aspergillus glaucus pollution rice sample stay
One validation-cross result.
5 various concentrations Aspergillus glaucus of table pollution rice sample LDA models stay a validation-cross result (10000~
4000cm-1)
From above experimental result, infrared band (1800~900cm in-1, 1800~1485cm-1Wave band)
Spectroscopic data and near infrared band (10000~4000cm-1Wave band) spectroscopic data can realize that Aspergillus glaucus is dense in paddy
Effective differentiation of degree, but the differentiation accuracy rate higher of near infrared spectrum data.
The above results illustrate, can accurately differentiate the content of Aspergillus glaucus in paddy using the present embodiment method.
For the rice sample that infection Aspergillus glaucus concentration is unknown, directly crushed with high speed Universal pulverizer, gather spectrum
After data, the discriminating model established by LDA methods is substituted into the present embodiment, is determined by the verification result of model grayish green in sample
The pollution level of aspergillus.
The detection research of different moulds is polluted in 3 paddy of embodiment
The preparation of rice sample containing Aspergillus glaucus：By Aspergillus glaucus 1, Aspergillus glaucus 2 and one plant of mould be inoculated into through
In 28 DEG C of cultures, the tenth day paddy for taking out culture after inoculation, with high speed Universal pulverizer (type on the sterile paddy of irradiation sterilization
Number FW100, Tianjin Stettlen Instrument Ltd.) it is ground into powder；At the same time using the sterile paddy meal of irradiation sterilization it is broken as
Compare rice sample.The paddy powder of Aspergillus glaucus 1, Aspergillus glaucus 2 and one plant of mould is separately added into sterile paddy, is mixed
The rice sample containing different moulds is made after uniformly, the gross mass of every part of rice sample is 50g, through PDA culture medium tradition
Culture counts, and the content of molds in each mould contamination paddy is respectively：The paddy content of molds that Aspergillus glaucus 2 pollutes is 1300cfu/g；
The paddy content of molds that Aspergillus glaucus 1 pollutes is 370cfu/g；The paddy content of molds of mould pollution is 60cfu/g.
Use ir data of the method collection with analyzing each rice sample in embodiment 2.
Figure 10, Figure 11 and Figure 12 are respectively 1800~900cm in spectral band-1, 1800~1485cm-1With 10000~
4000cm-1When three kinds of different mould contamination rice samples LDA shot charts.
Table 6, table 7 and table 8 are respectively 1800~900cm in spectral band-1, 1800~1485cm-1With 10000~
4000cm-1When three kinds of different mould contamination rice samples LDA models stay a validation-cross result.
The LDA models of the different mould contamination rice samples of 6 three kinds of table stay a validation-cross result (1800~900cm-1)
The LDA models of the different mould contamination rice samples of 7 three kinds of table stay a validation-cross result (1800~1485cm-1)
The LDA models of the different mould contamination rice samples of 8 three kinds of table stay a validation-cross result (10000~4000cm-1)
From above experimental result, infrared band (1800~900cm in-1, 1800~1485cm-1Wave band)
Spectroscopic data and near infrared band (10000~4000cm-1Wave band) spectroscopic data can effectively differentiate what is infected in paddy
Fungal species, but the differentiation accuracy rate higher of near infrared spectrum data.
Detection and quantitative study to wherein a certain fungi after a variety of different moulds are polluted in 4 paddy of embodiment
Tested using method and steps same as Example 3, difference is divided in the paddy in irradiation sterilization
Jie Zhong not Aspergillus glaucus 1, Aspergillus glaucus 2, mould 1 and mould 2.The paddy for taking Aspergillus glaucus 2, mould 1 and mould 2 individually to pollute
Each 1g of powder, the paddy powder 0.1,1,10,30 and 47g polluted respectively with Aspergillus glaucus 1 are mixed, then added to corresponding nothing
In bacterium paddy powder, the paddy powder to be checked that gross mass is 50g is made, detects different infrared band spectroscopic datas to four kinds of moulds
The testing result of paddy is polluted, wherein, the content of molds for polluting Aspergillus glaucus in paddy respectively may be about：50、500、3000、10 000
With 100 000cfu/g.
Figure 13, Figure 14 and Figure 15 are respectively 1800~900cm in spectral band-1, 1800~1485cm-1With 10000~
4000cm-1When a variety of different mould contamination rice samples LDA shot charts.
Table 9, table 10 and table 11 are respectively 1800~900cm in spectral band-1, 1800~1485cm-1With 10000~
4000cm-1When the LDA models of a variety of different mould contamination rice samples stay a validation-cross result.
The LDA models of the different mould contamination rice samples of table kind more than 9 stay a validation-cross result (1800~900cm-1)
The LDA models of the different mould contamination rice samples of table kind more than 10 stay a validation-cross result (1800~1485cm-1)
The LDA models of the different mould contamination rice samples of table kind more than 11 stay a validation-cross result (10000~4000cm-1)
It can be seen from the above result that either to the rice sample for being inoculated with different kinds of bacterial strains, or to being inoculated with same bacterial strain
But the rice sample of various concentrations, fourier infrared and near infrared spectrum can be distinguished, and correct decision rate is big
In 80%.Near-infrared correct decision rate higher, is almost 100%.
Claims (5)
1. the quick determination method of fungal contamination situation in a kind of grain, it is characterised in that include the following steps：
（1）The grain that pollution has control fungi is uniformly mixed with sterile grain respectively, obtains polluting the grain of each control fungi
Sample or the grain samples of pollution various concentrations control fungi；
（2）Using ATR-FTIR Spectrometry instrument, the grain samples of each control fungi of collection pollution or pollution
Infrared spectrogram and data of the grain samples of various concentrations control fungi in characteristic wave bands；The characteristic wave bands for 10000~
4000 cm-1Wave band；
（3）Principal component analysis is carried out to the ir data of each sample, extracts principal component score value, with linear discriminant analysis or
Partial least squares discriminant analysis establishes different classes of or various concentrations fungi and differentiates model, and verification differentiates the reliability of model；
（4）Infrared spectrogram and data of the grain samples to be measured in the characteristic wave bands are gathered, using step（3）The mould of middle foundation
Type determines fungal species or the concentration polluted in grain samples to be measured；
The control fungi is Aspergillus glaucus, aspergillus candidus, yellow grey mould, penicillium expansum, Fusarium oxysporum.
2. according to claim 1 in grain fungal contamination situation quick determination method, it is characterised in that using staying a friendship
Mutual proof method verification differentiates the reliability of model.
3. according to claim 2 in grain fungal contamination situation quick determination method, it is characterised in that step（2）In adopt
During collecting infrared spectrogram, spectral resolution is 4 cm-1, each sample is at least detected 3 times in each wave band, takes each sample
Averaged spectrum；In each detection of sample, at least scan 32 times.
4. according to claim 3 in grain fungal contamination situation quick determination method, it is characterised in that the principal component
Analysis refers to two-dimensional principal component analysis.
5. according to claim 4 in grain fungal contamination situation quick determination method, it is characterised in that every kind of grain sample
Product take the Duplicate Samples of more than 5.
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| CN108663339B (en) * | 2018-05-15 | 2021-01-26 | 南京财经大学 | On-line detection method for mildewed corn based on spectrum and image information fusion |
| CN111665216A (en) * | 2020-06-02 | 2020-09-15 | 中南民族大学 | Method for judging pollution degree of escherichia coli and staphylococcus aureus in quick-frozen rice-flour product |
| 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 |
| CN114136889A (en) * | 2021-12-10 | 2022-03-04 | 北京燕京啤酒股份有限公司 | Method for qualitatively identifying common fungus-polluted microorganisms on surface of malt based on near infrared spectrum technology |
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