JP6692226B2 - Mycotoxin analysis method and mycotoxin analyzer - Google Patents

Description

  TECHNICAL FIELD The present invention relates to a method for analyzing mycotoxin using vibrational spectroscopy and an apparatus for analyzing mycotoxin.

  Among the metabolites produced by fungi, those that are toxic to humans and animals are called mycotoxins. Mycotoxin is known to cause acute or chronic physiological or pathological disorders in humans, poultry, livestock and the like. Therefore, internationally, the Codex Committee (established by the United Nations Food and Agriculture Organization (FAO) and the World Health Organization (WHO) in 1963 for the purpose of protecting consumer health and ensuring fair trade in food, etc. International intergovernmental organizations) have established various norms regarding the prevention and reduction of mycotoxin contamination. In Japan, norms are established based on the Food Sanitation Law and various management guidelines of the Ministry of Agriculture, Forestry and Fisheries.

  At various sites of food and feed production and distribution, compliance with acceptable values and norms of mycotoxin must be inspected and confirmed. For that purpose, it is necessary to analyze mycotoxins easily and quickly at any place. The analysis should be done at least qualitatively and preferably quantitatively. In addition, it is desirable for rapid and efficient analysis that multiple types of mycotoxin contained in the same sample can be analyzed in parallel.

  As in the case of general chemical analysis methods, the conventional analysis of mycotoxins is the procedure of collecting a sample containing the target substance (mold poison), extracting the target substance from the sample to a solvent, purifying the extract and detecting the target substance. Done in. Methods such as liquid chromatography and gas chromatography are used in combination with detectors such as fluorescence detectors and mass spectrometers to detect mycotoxins. However, these detectors are very expensive, and the quantitative value may greatly increase or decrease due to impurities in the sample that cannot be removed by purification (see, for example, Non-Patent Document 1).

  The conventional technique using liquid chromatography or gas chromatography has a problem that the measurement result is easily influenced by the condition of impurities in the sample, and also brings an expensive detector to various sites of production and distribution of food etc. This is not always realistic. On the other hand, enzyme-immobilized immunoassay (ELISA) is used as a method to perform analysis with relatively simple equipment, but all highly specific antigen / antibody reactions are performed in one well. Since a substrate is added to an enzyme labeled with an antibody to cause reaction and color development, and the result is obtained by its absorbance, there is a problem that it is easily affected by contaminants and a false positive or false negative result is obtained.

  Instead of liquid chromatography or gas chromatography, a technique has been disclosed in which an optical method is used to eliminate the need for complicated pretreatment (for example, refer to Patent Document 1 or Non-Patent Document 2). Patent Document 1 measures the fluorescence intensity while gradually changing the excitation wavelength of the light irradiating the measurement target containing a harmful component (harm factor) such as mycotoxin and the wavelength of the fluorescence observed from the measurement target. Then, a technique is disclosed in which data called a fluorescent fingerprint (or excitation / fluorescence matrix) is acquired, and a hazard factor is detected by performing multivariate analysis on the fluorescent fingerprint data.

  According to the invention described in Patent Document 1, it is described that the harmful factor can be detected more quickly and easily than the method using liquid chromatography or gas chromatography.

  However, since the method described in Patent Document 1 is a kind of fluorescence spectroscopic analysis method, while changing the combination (wavelength condition) of the excitation wavelength and the fluorescence wavelength, the data of the optical signal intensity is acquired for each of these wavelength conditions. It is necessary (for example, 5041 wavelength condition is illustrated in paragraph “0069” of the description). In addition, it is necessary to use a known or previously measured calibration curve for quantifying the concentration of the harmful substance (paragraph “0075” in the specification). Taking these into consideration, another technological advance would be desirable in order to be able to analyze mycotoxins easily and quickly in any place.

JP, 2012-177606, A

Setsuko Tabata "Lecture Mold Inspection Method 10 Mycotoxin Analysis" Journal of Japanese Society of Antibacterial and Antifungal Vol. 43, No. 10, pp. 485-494, 2015 Fujita, Tsuta, Sugiyama "A New Method for Deoxynivalenol Discrimination by Applying Excitation Fluorescence Matrix Measurement" Journal of Food Science and Technology, Japan Vol. 55, No. 4, pp. 177-182 April 2008

  The problem to be solved by the present invention is to enable simple and quick analysis of mycotoxin in any place as much as possible. It is also desirable that plural types of mycotoxin contained in the same sample can be analyzed in parallel.

  For that purpose, among the optical methods, the vibrational spectroscopic analysis method that does not require repeated measurement for many wavelength conditions such as the fluorescence spectroscopic analysis (the infrared rays generated by the change of the dipole moment due to the vibration of the molecule) Infrared absorption spectroscopy for observing absorption, Raman spectroscopy for observing Raman effect caused by changes in polarizability, etc.) are promising. The equipment used for the vibrational spectroscopic analysis is easily available in a small size, so that it does not need to be selected in any place. It is desirable that the influence of background light such as fluorescence derived from impurities in the sample can be suppressed as much as possible.

  Once the spectrum data is obtained from the sample, multivariate analysis is also performed using the reference spectrum data previously acquired from the standard sample containing the target substance, and the calibration curve is virtually measured instead of being actually measured. The way to ask is promising. Such a method is disclosed in Japanese Patent No. 5780476 related to the invention of two of the inventors of the present application. It is described in paragraph “0011” of the specification of Japanese Patent No. 5780476 that the effect of being able to simultaneously determine the composition ratio of a plurality of quantitative target components is obtained according to this method. In other words, it is expected to analyze multiple species of mycotoxin in parallel.

In order to solve the above-mentioned problems, the method for analyzing mycotoxin according to the present invention is a method for analyzing mycotoxin using Raman spectroscopic analysis, in which the type of mycotoxin to be analyzed may be an initial sample. From the collected initial sample to produce an analytical sample that may contain a mold venom of the type intended for the analysis, and using the vibrational spectroscopic method, the type of the target of the analysis. Acquiring a reference spectrum from a standard sample containing fungal venom, irradiating the analysis sample with laser light over a plurality of consecutive time intervals, and emitting from the analysis sample at each of the plurality of time intervals. The Raman scattered light and the background light excluding the Raman scattered light are collected, a spectrum including the Raman scattered light and the background light is recorded, and the plurality of time intervals are recorded. From the spectrum recorded for each, using multivariate analysis, extract the time dependence of the intensity of the Raman scattered light and the intensity of the background light and the spectrum of the Raman scattered light from the spectrum of the background light. By performing a separation process to separate , obtain an analysis spectrum from the analysis sample, by performing an arithmetic process using multivariate analysis with the reference spectrum data and the analysis spectrum data as input In the case where the target type of mycotoxin in the analysis is produced in the initial sample, the spectrum of the target type of mycotoxin in the analysis is extracted from the analysis spectrum.

Further, the mold venom analyzer according to the present invention is a mold venom analyzer that can perform analysis of the mold venom using Raman spectroscopy, and the type of mold venom to be analyzed may be produced. There is a spectroscopic analysis unit capable of acquiring an analysis spectrum by using the vibrational spectroscopic analysis method from an analysis sample generated from an initial sample, and data of the analysis spectrum and a target type of the analysis. By inputting the data of the reference spectrum obtained by using the vibrational spectroscopic analysis method from the standard sample containing the mycotoxin, by performing the arithmetic processing using the multivariate analysis, the mycotoxin of the kind of the analysis is performed. There and an arithmetic processing unit capable of extracting the spectrum of types of mycotoxin of interest of the analysis in the case of producing the sample, the spectroscopic analysis unit, the laser beam irradiation The Raman scattered light scattered by the sample for analysis and the background light excluding the Raman scattered light are condensed, and the recording section capable of recording the spectrum including the Raman scattered light and the background light is continuous. When the analysis sample is continuously irradiated with laser light over a plurality of time intervals, from the spectrum recorded for each of the plurality of time intervals, using multivariate analysis, the intensity of the Raman scattered light and the By separating each time dependence of the intensity of background light and separating the spectrum of the Raman scattered light from the spectrum of the background light, a separation unit capable of obtaining the analysis spectrum is provided. Characterize.

  According to the present invention, it is possible to analyze mycotoxin easily and quickly regardless of the location. Further, it is possible to analyze a plurality of types of mycotoxin contained in the same sample in parallel.

FIG. 1 is a flowchart showing the procedure of the embodiment. FIG. 2 is a block diagram of the analyzer according to the embodiment. FIG. 3 is a flowchart showing in more detail the procedure for acquiring the spectrum for analysis. FIG. 4 is a time chart for explaining the processing of laser light irradiation and spectrum recording. FIG. 5: is a figure which illustrates the spectrum recorded in time series. FIG. 6 is a diagram showing a Raman spectrum and a fluorescence spectrum derived from fungal venom (zearalenone) separated from each other and analysis results of time dependence of their intensities. FIG. 7 is a diagram showing the results of obtaining the same spectrum as in FIG. 6 by changing the analysis conditions. FIG. 8 is a flowchart showing the procedure of the arithmetic processing in more detail. FIG. 9 is a diagram showing a Raman spectrum derived from zearalenone extracted as a result of the arithmetic processing. FIG. 10 is a diagram showing an example of a reference spectrum obtained from a preparation of zearalenone. FIG. 11 is a diagram showing Raman spectra derived from four aflatoxin species extracted as a result of the arithmetic processing. FIG. 12 is a diagram showing an example of a reference spectrum obtained from four aflatoxin preparations. FIG. 13 is a diagram showing a Raman spectrum derived from deoxynivalenol extracted as a result of the arithmetic processing. FIG. 14 is a diagram showing an example of a reference spectrum obtained from a standard sample of deoxynivalenol.

  Embodiments of the present invention will be described below with reference to the drawings. Examples of the present invention described below were obtained by adding a target substance (mold poison) to foods and the like to produce an initial sample, extracting the target substance from the initial sample into a solvent, and purifying the extract. The method of detecting a target substance from a sample for analysis using Raman spectroscopic analysis, which is one of vibration spectroscopic methods, is used to analyze mycotoxin added to foods and the like. FIG. 1 is a flowchart showing the procedure of the embodiment.

  Of the above procedures, the steps from sample generation and collection to extract purification (steps S101 and S102 in FIG. 1) are carried out, for example, as follows (in this example, the method for analyzing mycotoxin is experimentally carried out). Therefore, the sample containing mycotoxin is generated in advance.). A mixture of four aflatoxins (B1, B2, G1 and G2) in a weight ratio of 10 μg / kg, deoxynivalenol in a weight ratio of 1 mg / kg, or zearalenone in a weight ratio of 1 mg / kg was added to 10.0 g of a corn sample. Add (step S101).

  Furthermore, 40 ml of ultrapure water (MilliQ water (the same name MILLI-Q is a registered trademark, the same applies below)) is added and shaken (200 rpm, 30 minutes), and further 60 ml of methanol is added and shaken (200 rpm, 30 minutes). .. After allowing this to stand, 50 ml of the supernatant is centrifuged (7,000 rpm, 10 minutes), and 5 ml of the supernatant is concentrated to 2 ml with nitrogen gas.

  5 ml of PBS (phosphate buffered saline) is added to the above 2 ml of concentrated solution, and column trap is performed using a fungal venom concentration column (Myco6in1 + IAC column). This is washed with 10 ml of ultrapure water (MilliQ water), and mycotoxin is eluted from the column with 1.5 ml of methanol. Further, the mold venom is eluted from the column with 1.5 ml of methanol, and 2 ml of ultrapure water (MilliQ) is added to elute the mold venom which is different in water solubility or insolubility. The whole eluate obtained through the above process is dried with nitrogen gas to obtain a sample for analysis (denoted by reference numeral 10) to be subjected to spectroscopic analysis (step S102).

  Here, the configuration of the mold venom analyzer 100 according to the embodiment will be described once with reference to FIG. FIG. 2 is a block diagram of the analyzer 100. The analysis sample 10 obtained in step S102 is shown on the left side of FIG. The analyzer 100 has a configuration surrounded by a chain line in FIG. Those components are the spectroscopic analysis unit 110, the arithmetic processing unit 120, and the control unit 130. The spectroscopic analysis section 110 includes a light receiving section 111, a spectroscopic section 112, a recording section 113, and a separating section 114. The arithmetic processing unit 120 includes a generation unit 121 and an analysis unit 122.

  In the embodiment, the light emitting unit 20 including the laser light source is also used. The analysis device 100 may include the light emitting unit 20. The light emitting unit 20 and the light receiving unit 111 can be configured to correspond to optical systems of various commercialized Raman spectroscopic analyzers (detailed description thereof will be omitted here).

  The above-described configuration of the analysis device 100 can be realized by using various means including hardware or software, and a block of hardware or software clearly divided as in each of the above configurations is not necessarily required. It does not imply that it is present. In FIG. 1, solid lines with arrows show the flow of signals to be measured and processed, and broken lines with arrows show the flow of control signals.

  The light emitting unit 20 can irradiate an object such as the analysis sample 10 with laser light. The light receiving unit 111 collects Raman scattered light, fluorescence and other background light scattered from the object as a result of laser irradiation. The spectroscopic unit 112 analyzes the light condensed by the light receiving unit 111 and displays the spectrum on a plane having Raman shift on one axis (for example, the horizontal axis) and light intensity on the other axis (for example, the vertical axis). Can be plotted. The Raman shift axis may be replaced with an axis whose unit is either the wavelength of light or the frequency of light. The recording unit 113 can record the data of the plotted spectrum.

  The separation unit 114 is realized by, for example, software installed in a personal computer (PC), and performs separation processing including multivariate analysis described below on the spectrum data recorded in the recording unit 113 to generate Raman scattered light. Alternatively, it is possible to obtain a spectrum for analysis including Raman scattered light in which the time series of the signal intensity of the background light and the signal-to-noise ratio (SNR) are improved.

  The generation unit 121 and the analysis unit 122 of the arithmetic processing unit 120 are realized by software installed in a PC, for example. The generation unit 121 can obtain the analysis spectrum described above and the reference spectrum described later, and generate analysis target data that can be represented as a matrix. The analysis unit 122 obtains the above-mentioned data to be analyzed and performs a calculation process including a multivariate analysis described later to obtain a spectrum and a signal intensity profile (generally, detected mycotoxin of the mycotoxin contained in the analysis sample 10). , Which has a linear relationship with the quantity of.

  The control unit 130 is realized by software installed in a PC, for example. The control unit 130 can give an instruction necessary for performing data acquisition and analysis to the light emitting unit 20, the spectroscopic analysis unit 110, and the arithmetic processing unit 120, and can receive the result.

  The specific configuration of the analysis device 100 is not limited to the above. Each part may be configured mainly by hardware or firmware, hardware or firmware and software may be appropriately combined, or the program according to the present invention may be installed in a commercialized spectroscopic analyzer. Good.

  Returning to FIG. 1, the procedure of the embodiment will be described from step S103. In this step, in place of the analytical sample 10 in FIG. 2, a standard sample containing a mold venom of the type to be analyzed (for example, the sample of the mold venom itself or a mixture of the sample and a known solvent) is used. On the other hand, laser light is emitted from the light emitting unit 20, and Raman scattered light from the standard sample is received by the light receiving unit 111. The received Raman scattered light is dispersed by the spectroscopic unit 112 and recorded in the recording unit 113 as a reference spectrum (step S103).

  When the standard sample is prepared using a solvent, the difference between the spectrum obtained from the standard sample and the spectrum obtained only from the solvent may be recorded in the recording unit 113 as a reference spectrum. An example of the reference spectrum obtained from the standard sample of mycotoxin is shown in FIG.

  Next, the process proceeds to step S104. First, the light emitting unit 20 irradiates the analysis sample 10 with laser light, and Raman scattered light derived from the mycotoxin to be analyzed and components other than the mycotoxin (referred to as impurities). Background light such as fluorescence derived from (..) is received by the light receiving unit 111, and further, the spectrum obtained by being separated by the spectroscopic unit 112 is recorded in the recording unit 113. In this step, there is a problem that the Raman spectrum derived from mycotoxin is buried in the spectrum of background light such as fluorescence derived from contaminants contained in the analysis sample 10 and is difficult to detect.

  FIG. 3 is a flowchart showing the processing procedure in step S104 in more detail. It is known that the intensity of fluorescence derived from impurities in a sample is attenuated with time when the sample is continuously irradiated with laser light (this phenomenon is called quenching). In the process shown in the flowchart of FIG. 3, the fluorescence quenching phenomenon is used as follows.

  First, the light emitting unit 20 continuously irradiates the analysis sample 10 with laser light for a certain period of time (step S301). Then, the spectrum (including the spectrum of the Raman scattered light and the background light) obtained from the analysis sample 10 is recorded in the recording unit 113 at each time interval that divides the irradiation time of the laser light (step S302).

  The control unit 130 can divide the laser light irradiation time into a plurality of continuous time intervals. The recording unit 113 can record the spectrum plotted by the spectroscopic unit 112 in chronological order (that is, in the order of a plurality of time intervals instructed by the control unit 130).

  FIG. 4 is a time chart explaining the processing of steps S301 and S302. The horizontal axis of the figure is the time axis. At the “0” point on the time axis, irradiation of laser light from the light emitting unit 20 to the analysis sample 10 is started. The control unit 130 causes the recording unit 113 to record the spectrum obtained from the analysis sample 10 at each timing of T, 2T, ..., NT (T is time, N is a natural number) on the time axis.

  FIG. 5: is a figure which illustrates the spectrum recorded in time series as mentioned above (The sample 10 for analysis is what solidified the IMC column extraction constant volume liquid of the sample which added zearalenone to corn. The wavelength of the excitation light is 532 nm, T = 5 seconds, and N = 20.) Each plot in FIG. 5 shifts from top to bottom with the passage of time. That is, it can be seen that the intensity of the fluorescence derived from the contaminant, which is the dominant component in this spectrum, decreases with the passage of time.

  The spectrum data recorded for all time intervals (hereinafter, referred to as all spectrum data) includes, for example, the row number by the position (pixel) on the Raman shift axis, and the column number by the above time series. It can be expressed in the form of a matrix defined by the order. Assuming that the number of pixels is M, all spectrum data are represented as a matrix of M rows and N columns (hereinafter referred to as symbol A).

  Next, processing (separation processing) of all spectrum data performed by the separation unit 114 will be described. For example, when it is known or presumed that the components constituting the analytical sample 10 can be divided into two types, that is, mycotoxin (contribution to Raman spectrum) and contaminant (contribution to fluorescence spectrum), a matrix is formed. Factor A into a matrix W of M rows and 2 columns consisting of column vectors representing the spectrum data of each component and a matrix H of 2 rows N columns consisting of row vectors representing time series data of the intensity of each component. Think to disassemble. Then, the matrix A is expressed by the "equation 1" and the matrices W and H are expressed by the "equation 2", respectively. The "actually measured spectrum (kT)" in the equation 1 represents the spectrum actually measured and recorded at the timing "kT" (1≤k≤N) on the time axis of FIG.

  If the matrix W can be obtained from the above equations 1 and 2, the influence of Gaussian noise can be reduced by separating from the fluorescence spectrum derived from contaminants and integrating them in time series. Raman spectra derived from mycotoxin are obtained. Although an analytical solution of the equation (1) cannot be obtained, an initial value is given to the matrix W to obtain an approximate solution of the matrix H by a known least squares method, and then an approximate solution of W is further obtained. It is known that an approximate solution can be obtained by the alternating least squares method that iterates until the convergence condition of is satisfied.

In the alternating least squares method described above, the squared norm of residuals || A−W · H || ₂ of the matrix A whose actual measurement value is an element and the matrix W · H whose approximate value is an element are either the matrix W or H. One of the matrices W or H is approximated to the next stage by minimizing the other. As a mathematical device for making this minimization operation simpler and more accurate, at least all the elements of the matrix A are represented by non-negative values and the regularization term ( For example, it is known to impose a constraint condition of adding the L1 norm or the L2 norm). Moreover, since the time-series data of the intensity of the Raman spectrum does not have a remarkable time dependency, it is possible to impose a condition that the value in the first row of the matrix H is a constant.

  FIG. 6 is a diagram showing an approximate solution of each column vector of the matrix W and each row vector of the matrix H of the “Equation 2” obtained by performing the above separation processing from all the spectrum data shown in FIG. The diagram on the left side of FIG. 6 shows the fluorescence spectrum (No. 1) derived from contaminants and the Raman spectrum (No. 2) derived from mycotoxin with the Raman shift as the horizontal axis. In the diagram on the right side of FIG. 6, the measurement number (1 ≦ N ≦ 20) on the time series is plotted on the horizontal axis, and the time dependence of fluorescence intensity (No. 1, practice) is shown (time dependence of Raman spectrum ( It is assumed that the number 2 and the broken line) are zero) (step S303).

  When it is known or inferred that the components contained in the analytical sample 10 can be divided into, for example, four types, the matrix A is an M-row, 4-column matrix composed of column vectors representing the spectrum data of the respective components. Consider factorization into W and a matrix H of 4 rows and N columns consisting of row vectors representing time series data of intensity of each component. Then, the matrices W and H are represented by the formula "Equation 3".

  An approximate solution of the matrices W and H can be obtained from the equations 1 and 3 by using the alternating least squares method similar to the above. Also in this case, the condition that all the elements of the matrix A are represented by non-negative values and the constraint condition of the regularization term are used. Further, it is possible to impose a condition that all elements of the matrices W and H are represented by non-negative values.

  FIG. 7 is a diagram showing an approximate solution of each column vector of the matrix W and each row vector of the matrix H of the “Formula 3” obtained by performing the above separation processing from all the spectrum data shown in FIG. The diagram on the left side of FIG. 7 shows the spectrum of each component (numbers 1 to 4) with the Raman shift as the horizontal axis. The diagram on the right side of FIG. 7 shows the time dependence of each component (numbers 1 to 4) with the measurement number (1 ≦ N ≦ 20) on the time series as the horizontal axis. It can be seen that the components of No. 1 and No. 2 are in good agreement with the fluorescence spectrum (No. 1) and Raman spectrum (No. 2) of FIG. 6, respectively. Thus, even if the types of components contained in the analysis sample 10 increase, the Raman spectrum derived from mycotoxin can be separated from the background light derived from impurities (step S303).

  As described above, paying attention to the time dependence of the fluorescence intensity derived from the contaminants contained in the analysis sample 10, the Raman spectrum derived from the mold must be separated and obtained as the analysis spectrum (step S304, step). S104). Subsequently, the Raman spectrum derived from mycotoxin is extracted by performing arithmetic processing using multivariate analysis with the reference spectrum obtained in step S103 and the analysis spectrum obtained in step S104 as inputs (step S105). .. FIG. 8 is a flowchart showing the procedure of the process in step S105 in more detail.

  The generation unit 121 reads the reference spectrum obtained in step S103 from the recording unit 113 and multiplies it by a plurality of coefficients (real numbers) to obtain a plurality of product data (step S801). Next, the generation unit 121 obtains the analysis spectrum obtained in step S104 (or S304) from the separation unit 114, and adds the analysis spectrum to each of the above-described plurality of product data to obtain a plurality of sum spectrum data. Get (step S802). The above-mentioned data of a plurality of sum spectra is equivalent to the data of a spectrum measured each time when a standard sample having a plurality of concentrations is added to a sample to be analyzed in order to draw a calibration curve in real space.

  The generation unit 121 differentiates the data of the above-described plurality of sum spectra in the direction of the Raman shift axis (or the corresponding wavelength axis or frequency axis) 0 times or more, and obtains the obtained data as a column vector. To form a matrix and generate the matrix as analysis target data (step S803). The matrix of the data to be analyzed is, like the matrix of all spectrum data obtained in step S302, a matrix composed of two column vectors representing spectrum data of each component other than mycotoxin and a spectrum for reference. Can be factored into a product of a matrix composed of two row vectors representing the intensity profile of each component corresponding to the coefficient (corresponding to the concentration of the standard sample in the real space) multiplied by.

  The analysis unit 122 obtains the above-described data to be analyzed and, for example, by using the alternate least squares method in which the intensity profile of components other than the mycotoxin is constant and the constraint condition for adding the regularization term is imposed, the mycotoxin is It is possible to extract the Raman spectrum and the signal intensity profile derived from it (see Japanese Patent No. 5780476).

  FIG. 9 shows a Raman spectrum derived from zearalenone extracted by the processes of steps S801 to S804 using the analysis spectrum derived from zearalenone obtained in step S104 (S304) and the reference spectrum obtained from the zearalenone preparation. It is a figure. The solid line (uppermost plot) in the figure is the analysis spectrum after being separated from the fluorescence. The dotted line in the figure (the plot immediately below the top row) is the spectrum derived from components other than zearalenone. The alternate long and short dash line (bottom plot) in the figure is the Raman spectrum derived from zearalenone.

  FIG. 10 shows an example of a reference spectrum obtained from a preparation of zearalenone. Since the plot at the bottom of FIG. 9 has the same characteristics as the plot in FIG. 10, it is confirmed that the Raman spectrum of zearalenone could be extracted by this example.

  FIG. 11 is a diagram showing Raman spectra derived from those mold venoms extracted from a sample containing four types of aflatoxins (G1, G2, B1 and B2) as a mold toxicant, similar to FIG. 9. The solid line (uppermost plot) in the figure is the analysis spectrum after being separated from the fluorescence. The dotted line in the figure (the plot immediately below the top row) is the spectrum derived from components other than the four aflatoxins. Four dashed-dotted lines (lowermost plot) in the figure are Raman spectra derived from four aflatoxins. It is confirmed that the Raman spectra of the four types of aflatoxins could be extracted by comparing with the reference spectra of the four types of aflatoxin preparations in FIG. This is an example in which multiple types of mycotoxin contained in the same sample were analyzed and extracted in parallel.

  FIG. 13: is a figure which shows the Raman spectrum derived from deoxynivalenol extracted from the sample which contains deoxynivalenol as a mold poison similarly to FIG. The solid line (uppermost plot) in the figure is the analysis spectrum after being separated from the fluorescence. The dotted line in the figure (the plot immediately below the top row) is the spectrum derived from components other than deoxynivalenol. The alternate long and short dash line (bottom plot) in the figure is a Raman spectrum derived from deoxynivalenol. It is confirmed that the Raman spectrum of deoxynivalenol could be extracted by comparing with the reference spectrum of the standard sample of deoxynivalenol in FIG.

  According to the examples of the present invention described above, it was confirmed that the Raman spectrum derived from mycotoxin can be extracted while suppressing the influence of background light such as fluorescence derived from contaminants in the sample. In the embodiment, the processes of steps S301 to S304 are executed to acquire the analysis spectrum (step S104), but depending on the type and characteristics of the sample, these processes may be omitted to acquire the analysis spectrum. Although Raman spectroscopy was used in the examples, the method of the present invention shown in the flowchart of FIG. 1 can also be carried out using infrared absorption spectroscopy.

  Although the example explained that the extract is purified in step S102 in FIG. 1, the extract may be omitted depending on the characteristics of the initial sample containing the mycotoxin, and the initial sample may be directly used as the analytical sample.

10 Analysis Sample 20 Light Emitting Part 100 Analyzing Device 110 Spectroscopic Analyzing Part 111 Light Receiving Part 112 Spectroscopic Part 113 Recording Part 114 Separing Part 120 Operation Processing Part 121 Generating Part 122 Analyzing Part 130 Control Part

Claims (8)

In the method of analyzing mycotoxin using Raman spectroscopy,
Collecting an initial sample that may produce the type of mycotoxin for the purpose of analysis,
From the collected initial sample, generate an analytical sample that may contain a mold venom of the type intended for the analysis,
Using Raman spectroscopy, obtain a reference spectrum from a standard sample containing the type of mycotoxin of interest for the analysis,
Irradiating the analysis sample with laser light over a plurality of consecutive time intervals,
For each of the plurality of time intervals, while condensing the Raman scattered light scattered from the analysis sample and the background light excluding the Raman scattered light, record a spectrum containing the Raman scattered light and the background light,
From the spectra recorded for each of the plurality of time intervals, using multivariate analysis, the time dependence of the intensity of the Raman scattered light and the intensity of the background light and the spectrum of the Raman scattered light is extracted. By performing a separation process to separate from the spectrum of background light, to obtain an analysis spectrum from the analysis sample,
By performing arithmetic processing using the multivariate analysis with the data of the reference spectrum and the data of the analysis spectrum as an input, in the case where the type of mycotoxin of the type of the analysis is produced in the initial sample, A method for analyzing a mycotoxin, which comprises extracting a spectrum of a mycotoxin of a type intended for the analysis from the spectrum for analysis. The arithmetic processing is
From a plurality of sum spectrum data obtained by adding each of a plurality of product data obtained by multiplying the reference spectrum data by a plurality of coefficients, a matrix Generate analysis target data that can be expressed by
The method for analyzing mycotoxin according to claim 1, wherein a spectrum and signal intensity profile of the type of mycotoxin targeted for the analysis are extracted from the data to be analyzed using multivariate analysis. In the case where there are multiple types of mycotoxin of the type of the analysis,
Obtaining the reference spectrum for each of the plurality of types of mycotoxin,
The method for analyzing a mycotoxin according to claim 1, wherein the arithmetic processing is performed for each target type of the plurality of analyses. Multivariate analysis in the separation process,
A first matrix containing the recorded spectrum as a column vector of the spectrum of the Raman scattered light and the spectrum of the background light as a column vector, and a signal intensity profile of the Raman scattered light corresponding to the order of the plurality of time intervals. And when decomposed into a second matrix including the signal intensity profile of the background light corresponding to the order of each of the plurality of time intervals as a row vector,
Using the least squares method that imposes at least the condition that the recorded spectrum is represented by a non-negative matrix and a constraint condition that adds a regularization term to an error, the first matrix and the second matrix The method for analyzing mycotoxin according to claim 1, wherein the calculation for alternately obtaining is repeated until a predetermined convergence condition is satisfied.   The sample for analysis is produced by subjecting the initial sample to an extraction operation and a purification operation using a solvent suitable for the type of mycotoxin targeted for the analysis. Method for analysis of mycotoxin.   The mold according to any one of claims 1 to 5, wherein the mold venom contains one or more of four types of aflatoxins (B1, B2, G1 and G2), deoxynivalenol and zearalenone. Poison analysis method. In a mold venom analyzer capable of analyzing mold venom using vibrational spectroscopy,
From an analytical sample produced from an initial sample in which the type of mycotoxin of interest may be produced, a spectroscopic analysis unit capable of obtaining an analytical spectrum using the vibrational spectroscopic analysis method,
The data of the spectrum for analysis and the data of the spectrum for reference obtained by using the vibrational spectroscopic analysis method from the standard sample containing the type of mycotoxin targeted for the analysis are input, and arithmetic processing using multivariate analysis is performed. By carrying out, a processing unit capable of extracting the spectrum of the target fungal venom of the analysis when the target fungal venom of the analysis is produced in the sample ,
The spectroscopic analysis unit,
A recording unit capable of recording a spectrum including the Raman scattered light and the background light by condensing the Raman scattered light scattered by the analysis sample irradiated with laser light and the background light excluding the Raman scattered light. When,
When the analysis sample is continuously irradiated with laser light over a plurality of continuous time intervals, from the spectrum recorded for each of the plurality of time intervals, using multivariate analysis, the intensity of the Raman scattered light. And separating the spectrum of the Raman scattered light from the spectrum of the background light while extracting the respective time dependence of the intensity of the background light, and a separation unit capable of acquiring the analysis spectrum . A mold venom analyzer characterized in that The arithmetic processing unit,
From a plurality of sum spectrum data obtained by adding each of a plurality of product data obtained by multiplying the reference spectrum data by a plurality of coefficients, a matrix A generation unit that can generate analysis target data that can be represented by
An analysis unit capable of extracting a spectrum and a signal intensity profile of a mold venom of a type intended for the analysis from the data to be analyzed by using a multivariate analysis. Mycotoxin analyzer.

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