JP3315546B2 - Pesticide residue analysis method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for analyzing residual agricultural chemicals for determining whether the residual concentration of agricultural chemicals in agricultural products such as vegetables is below an allowable value.

[0002]

2. Description of the Related Art Conventionally, gas chromatography and liquid chromatography have been used to measure pesticide residues in agricultural products. Recently, a method for detecting pesticide residues using the antibody-antigen reaction of pesticide components (JH Gibbons: Pe
sticide Residues in Food, 37/46 Technomic Publishi
ng Co, Inc. (1992)) and an analytical method using an optical biosensor that measures the fluorescence emitted from pesticide components (M. Eld
efrawi, K. Rogers, A. Eldefrawi: Optical Biosensor
for Detection of Anticholinesterase, Reviews In P
esticide Toxicology 1,329 / 335 (1991)), instrumental analysis using capillary electrophoresis (Shigehiro Kuzuhara, Takafumi Harumi, Yoshiaki Kitamura: Tar dyes in foods using high performance capillary electrophoresis (HPCE) Analysis of Pesticide Residues, Abstracts of 1993 Annual Meeting of the Japanese Society of Agricultural Chemistry, 321 (1993)) has been proposed as a method for measuring pesticide residues.

[0003]

Consumers are increasingly interested in residual agricultural chemicals because they may gradually impair human health if agricultural chemicals remain in agricultural products such as vegetables. In response, the Ministry of Health and Welfare has established additional residue standards for more than 60 new pesticides since 1992. Against this background, in order to supply crops that are guaranteed to be safe, it is necessary to determine whether the concentration of pesticide residues is below an acceptable level within a limited time from when the crop is harvested until it is shipped. Accurate determination is required.

[0004] However, conventional chemical measurements such as gas chromatography and liquid chromatography require pretreatment such as shredding, homogenization, extraction, and / or separation and purification of agricultural products as samples, and this pretreatment requires a long time. (4-5 hours or more). In addition, since the content of the pretreatment differs for each pesticide component to be measured, skill is required for the measurement.
Therefore, in the conventional chemical measurement, it is not possible to meet the demand for terminating the measurement within a limited time from when the crop is harvested to when it is shipped, and to confirm the safety of the crop before distribution.

[0005] In addition, the above-mentioned recently proposed measurement method has the same problem as the conventional chemical measurement that requires pretreatment such as sample homogenization and extraction. However, there is also a problem that the measurable pesticide components are limited due to the selectivity of this reaction.

Accordingly, the present invention provides a method for determining, in a short time, whether or not the concentration of a residual pesticide is below an allowable value, in order to confirm the safety of the agricultural product before distribution, and for determining the residual pesticide component to be analyzed without limitation. An object of the present invention is to provide a method for analyzing pesticides.

[0007]

Means for Solving the Problems According to the present invention made to solve the above-mentioned problems, the present invention provides a method for analyzing residual agricultural chemicals, which determines whether the concentration of agricultural chemicals remaining on the surface of agricultural products is below an allowable value. A) The data of the infrared absorption spectrum of the agricultural chemical component on the surface of a plurality of agricultural products having various known values of the residual concentration of the agricultural chemical component is obtained by AT using an infrared spectrophotometer.
A first step of sampling by the R method, b) using the data collected in the first step, the plurality of crops are divided into a group of non-residue agricultural chemicals and a group of residual agricultural chemicals based on a predetermined detection limit value. A second step of deriving an expression of a canonical variable and a first boundary value corresponding to the classification by performing classification and discriminant analysis; c) using the data collected in the first step, By performing the discriminant analysis by classifying the agricultural chemical component residual agricultural crop group into two agricultural crop groups depending on whether the concentration of the agricultural chemical ingredient is equal to or less than an allowable value, the expression of the secondary discriminant function corresponding to the classification and the second And d) an ATR method using an infrared spectrophotometer, wherein the infrared concentration of the pesticide component on the surface of the crop to be analyzed whose residual concentration is unknown is determined by an ATR method using an infrared spectrophotometer. E) calculating the value of the canonical variable using the data of the canonical variable by using the data collected in the fourth step, and setting the value as a first boundary value. A fifth step of determining whether or not the pesticide component remains on the surface of the crop to be analyzed by comparison; f) when it is determined that the pesticide component remains in the fifth step; Calculating the value of the quadratic discriminant function using the data of the quadratic discriminant function using the data collected in the fourth step, and comparing the calculated value with a second boundary value to obtain the surface of the crop to be analyzed. And determining whether the concentration of the pesticide component remaining in the base material is equal to or lower than an allowable value.

[0008]

First, for a plurality of crops in which the residual concentration of a pesticide component is a known various value, the data of the infrared absorption spectrum by the pesticide component remaining on the surface is obtained by using an infrared spectrophotometer. ATR (Attenuated Total Refrect)
ance) method (first step). In other words, infrared light is incident on the ATR prism on which the leaves of the crop are adhered, and the total reflection is repeated inside to detect the infrared light transmitted through the ATR prism. Is done. Next, using the spectrum data, the plurality of agricultural products are classified into agrochemical component-non-residue crop groups and agrochemical component-residue crop groups, and discriminant analysis is performed. As a result, a positive function as a discriminant function corresponding to the classification is obtained. A first boundary value is derived as a quasi-variable equation and a discriminant point for determination (second step). Also, using the spectrum data, the agricultural chemical component residual agricultural crop group is classified into two agricultural crop groups based on whether or not the residual concentration of the agricultural chemical component is below the allowable value, and discriminant analysis is performed. An equation of the next discriminant function and a second boundary value as a discrimination point are derived (third step). Thereafter, whether the residual concentration of the pesticide component in the unknown crop is equal to or lower than the allowable value can be promptly determined by the fourth to sixth steps.

[0009] Hereinafter, when determining whether the residual concentration of the pesticide component in the unknown crop is below the allowable value,
AT using an infrared spectrophotometer as in the first step
By the R method, data of an infrared absorption spectrum by a pesticide component on the surface of the crop is collected (fourth step). Next, using the spectrum data, the value of the canonical variable is calculated by the expression of the canonical variable, and the value is set to the first value.
It is determined whether or not the pesticide component remains on the surface of the agricultural product based on whether or not the value is larger than the boundary value (fifth step). Here, when it is determined that there is a residual, the value of the expression of the quadratic discriminant function is calculated using the spectral data collected in the fourth step, and the value is calculated from the second boundary value. It is determined whether or not the concentration of the pesticidal component remaining on the surface of the agricultural product is equal to or lower than an allowable value based on whether or not is larger (sixth step).

[0010]

【Example】

[Overall Configuration] FIG. 2 is a diagram showing a hardware configuration of a pesticide residue analysis system according to one embodiment of the present invention. This pesticide residue analysis system includes an interferometer 10, an ATR measuring device 20, a control unit 30, and a personal computer (personal computer) 40.

The interferometer 10 includes a beam splitter 14, a fixed mirror 16, and a movable mirror 18, and receives infrared light emitted from the light source 12. The incident infrared light is
First, the beam is split into two light beams by the beam splitter 14,
One light beam is fixed by the fixed mirror 16 and the other light beam is
8 are reflected respectively. Both reflected light beams become one light beam again by the beam splitter 14 and exit from the interferometer. In the interferometer 10, the movable mirror 18 reciprocates linearly, thereby changing the optical path difference between the two light beams. By combining these light beams, interference light (infrared interference light) is obtained, and this interference light is emitted from the interferometer 10.

The ATR measuring device 20 includes an ATR prism 2
2, a gripper 24, and mirrors M1 to M4. A sample (crop) 26 to be analyzed is pressed against the ATR prism 22 by the gripper 24 and is in close contact with the ATR prism 22. The interference light emitted from the interferometer 10 is introduced into the ATR measuring device 20, and enters the ATR prism 22 from one end face via the mirror M1. The ATR prism 22 is made of a material having a large refractive index (for example, ZnSe, Ge, etc.) that transmits infrared light, and the interference light (infrared light) incident on the ATR prism 22 repeats total internal reflection. To Penetrate. At this time, the interference light slightly reflects on the sample 26 closely attached to the ATR prism 22 and is reflected. For this reason, by measuring the interference light after the total reflection inside the ATR prism 22, an infrared absorption spectrum due to the pesticide remaining on the surface of the sample 26 can be obtained (in this manner, the surface of the sample is measured). A method for obtaining an infrared absorption spectrum is called “ATR method”). Therefore, in this embodiment, the ATR measuring device 20 has a detector 28 for detecting infrared light.
The interference light emitted from the other end face by repeating total reflection inside the ATR prism 22 is received by the detector 28 via the mirrors M2 to M4. As a result, a detection signal Sd corresponding to the interference light emitted from the ATR prism 22 is output from the detector 28.

The control unit 30 receives the detection signal Sd and A / D converts it to obtain interference signal data. Then, the data of the infrared energy spectrum is generated by Fourier-transforming the interference signal data. When the infrared absorption spectrum of the sample 26 is actually measured by the ATR method, first, the infrared energy spectrum is measured without the sample 26. This is the background spectrum. Next, the sample 26 is brought into close contact with the ATR prism, and an infrared energy spectrum is measured. This sample 2
By dividing the infrared energy spectrum of No. 6 by the above-mentioned background spectrum, data of an infrared absorption spectrum by the ATR method (hereinafter referred to as “spectral data”) is obtained. Based on this spectrum data, an infrared absorption spectrum is displayed on a display unit in the control unit 30. This spectrum data is transferred to the personal computer 40 via an interface such as RS-232C.

The personal computer 40 has stored therein in advance the formulas of the canonical variables and the formulas of the quadratic discriminant function in its internal memory, and uses the spectrum data transferred from the control unit 30 based on these formulas. The value of the canonical variable and the value of the quadratic discriminant function are calculated. Then, based on the calculated value, the sample 26
It is determined whether or not the concentration of the pesticide remaining in the is less than the allowable value.

[Derivation of Discriminant Function Formula] In the residual pesticide analysis system having the above-described configuration, the formula of the canonical variable and the formula of the quadratic discriminant function to be stored in the memory of the personal computer 40 (hereinafter, these formulas are referred to as Collectively, this is referred to as a “discriminating function expression”) is derived by the procedure shown in FIG. Hereinafter, the derivation of the expression of the discriminant function will be described with reference to FIG.

In order to derive the equation of the discriminant function, first,
A measurement method similar to the above, that is, FTIR (Fouier Transfo
Measurement S1 by ATR method using rm Infrared Spectrophotometer (hereinafter referred to as “FTIR-ATR method”)
By setting 0, infrared absorption spectrum data (spectral data) is obtained for a plurality of samples. In addition, after performing the pretreatment S12 on these samples, the analysis S14 is performed by gas chromatography to measure the concentration of the pesticide component to be analyzed (hereinafter, this measured value is referred to as “GC value”). Next, the area intensity of the spectrum corresponding to the characteristic absorption wave number of the pesticide component to be analyzed is calculated from the spectrum data, and discriminant analysis S16 is performed using the area intensity as a variable (observed value). However, the calculation of the area intensity is performed on the absorbance spectrum obtained by performing a log conversion of the infrared absorption spectrum. In this discriminant analysis S16, the GC value is set as the true value of the residual concentration of the agricultural chemical component to be analyzed. The formula of the discriminant function is derived by such discriminant analysis, and these are stored in the memory in the personal computer 40.

In this embodiment, in the above measurement of the infrared absorption spectrum, the wave number resolution is 2 cm ^-1 and the number of integration is 100
The ATR prism 22 is made of ZnSe, has a measurement surface dimension of 7 mm × 90 mm, and an incident angle of the interference light on the sample 26 is 45 degrees.

In this example, the inner tip of the outermost leaf in 76 actually grown lettuce was used as a sample, and the pesticide component to be analyzed was Tetrachlor.
oisophthalonitrile (hereinafter "TPN").
Here, lettuce is used by spraying daconil, a fungicide containing TPN, at a frequency of 0 to 3 times at weekly intervals, and spraying 14 days before harvesting. In a single application, a 1000-fold diluted solution of daconil, a standard concentration and amount normally applied,
It is sprayed at a rate of 0.4 m ³ per 100 m ² . Pesticides other than daconil are sprayed according to the lettuce cultivation practice.

The variable of the discriminant function in this embodiment is TP
The area intensities of the absorbance spectra at three wavenumber bands, which are the characteristic absorption wavenumbers of N., ie, 1378.3 cm ⁻¹ , 1265.5 cm ⁻¹ ,
Each 980.0Cm ^-1 centered wavenumber is the area intensity obtained by integrating the spectra area of ± 5 cm ^-1. In the discriminant analysis S16 in the present embodiment, first, as shown in FIG. 3, the samples are classified into three groups based on the TPN measurement values (GC values) by the gas chromatography S14. That is,
Samples with a GC value of less than 0.005 ppm were group A, 0.005 ppm to 1.0 ppm
The sample of No. is referred to as Group B, and the sample exceeding 1.0 ppm is referred to as Group C. Next, using the spectrum data for each sample obtained by the measurement S10 by the FTIR-ATR method, the area intensity of the spectrum in the three wavenumber bands is calculated for each sample, and the canonical value is calculated using the calculated value. Perform analysis (references:
Tanaka, Tarumi, Wakimoto, Statistical Analysis Handbook II, 72/1
59, Kyoritsu Shuppan (1988)). That is, the first canonical variable Z1
Z1 = a1 + b11 · A1 + b21 · A2 + b31 · A3 (1), and the ratio SB between the group sum of squares SB and the group sum of squares SW for the first canonical variable Z1 for the groups A to C shown in FIG. /
Coefficients b11 and b2 in the above equation so that SW is maximized.
1. Determine the value of b31. Where A1, A2 and A3 are TP
It is the area intensity of the spectrum in the characteristic absorption wavenumber band of N.
Since the constant a1 is not essential in discriminant analysis, a value convenient for the subsequent processing may be appropriately selected.

Next, a second canonical variable is determined in order to examine the discrimination of the sample group in the two-dimensional feature space. That is, the second canonical variable Z2 is set as Z2 = a2 + b21 · A1 + b22 · A2 + b23 · A3 (2), and the above equation is set so that the correlation between the first canonical variable Z1 and the second canonical variable Z2 is the lowest. Constant a2 and coefficient b1 in
2. Determine the values of b22 and b32.

As described above, the first and second canonical variables Z
1. When Z2 is obtained, Z1 = 0.618 + 0.031A1 + 0.308A2 + 0.768A3 (3) Z2 = 1.532 + 0.619A1-0.067A2 + 0.804A3 (4) is obtained.

FIG. 4 is a scatter diagram of a sample group in a two-dimensional feature space based on the two canonical variables Z1 and Z2. That is, FIG. 4 shows the equation (3) of the first canonical variable and the equation (4) of the second canonical variable determined by the canonical analysis using the spectral data of each of the 76 individual lettuce samples. Is calculated and shown in a two-dimensional space. In FIG. 4, samples in Group A (samples whose GC values are less than 0.005 ppm, which is the detection limit of gas chromatography, ie, samples in which TPN is not detected) are marked with “□”.
Samples of group B (GC values of 0.005 ppm to 1.0 ppm) were marked with "○"
And the sample of group C (sample whose GC value exceeds 1.0 ppm) is '●'
Indicated by As is clear from FIG. 4, the group in which TPN is not detected by gas chromatography (the group of samples indicated by “□”) can be clearly distinguished by the sign of the first canonical variable Z1. However, in the fourth quadrant of FIG.
Samples of group B (samples indicated by 'O') and samples of group C ('●'
And the sample indicated by. Therefore, TP
Based on the canonical variables Z1 and Z2, T.
It is difficult to divide the two groups with a PN concentration of 1 ppm as a boundary.

Therefore, the discriminant analysis of this embodiment utilizes a quadratic discriminant function. The quadratic discriminant function is a discriminant method for classifying samples into groups having smaller Mahalanobis generalized distances, and is applied when the variance-covariance matrices of the two groups to be classified are different (references: Tanaka, Tarumi, Wakimoto, "Statistical Analysis Handbook II", 72/159, Kyoritsu Publishing (1988)). Therefore, as shown in FIG. 3, the sample groups in which TPN was detected by gas chromatography were classified into two groups (Group B and Group C) using 1 ppm, which is the standard concentration for registration reservation of the Ministry of Health and Welfare, as a boundary value. And confirm that they are different. Then, a discriminant analysis based on the classification of the groups B and C is performed by using the same three area intensities A1, A2, and A3 as variables as in the case of the canonical analysis to derive a secondary discriminant function. Using spectral data for the 39 individuals lettuce TPN is detected by gas chromatography S14 of lettuce the 76 individuals, by performing such discriminant analysis, as a secondary discriminant function Q, Q = -0.091A1 ^{2 + 0.038A2 2 -1.082A3 2 -0.077A1A2-0.144A2A3 -0.825A3A1-1.493A1-0.88A2-3.55A3 +} 0.335 ... (5) is obtained.

The TPN is determined by gas chromatography S14.
When the value of the quadratic discriminant function (hereinafter, referred to as “Q value”) is calculated from the above equation (5) using the spectrum data for the lettuce of 39 individuals in which is detected, the result is as shown in FIG. In FIG. 5, 39 samples (lettuce) were determined depending on whether the GC value indicating the residual concentration of TPN was 1 ppm or less.
Are classified into two groups, a group B and a group C. From FIG. 5,
When the boundary value is determined as Q = 0 or when the boundary value is Q =-
When it is determined as 0.5, 88.2% of the samples in the group B where the residual concentration of TPN is below the allowable value of 1 ppm is correctly determined, and 72.7% of the samples in the group C where the residual concentration of TPN exceeds the allowable value of 1 ppm. Is correctly determined.
In addition, by adjusting the boundary value, it is possible to more accurately determine a sample in which a pesticide having a concentration exceeding the allowable value remains. For example, assuming that the boundary value is Q = 0.5, the correct answer rate for the group C is 90.9% as shown in FIG. This means that for samples where the concentration of pesticide residues exceeds the tolerance,
It means that 90% or more thereof can be correctly discriminated by the above-mentioned quadratic discriminant function. As a result of testing the difference between the variance-covariance matrices of the groups B and C, it was confirmed that the variance-covariance matrices of these two groups were different with a significant difference of 5%. Based on the above, the Ministry of Health and Welfare registration suspension standard concentration of 1 pp
The application of a quadratic discriminant function is effective in discriminating lettuce into two groups with m as a boundary.

As can be seen from the above description, to determine whether a sample (lettuce) belongs to group A (whether or not TPN is detected) using spectral data, the expression of the discriminant function is The equation (3) of 1 canonical variable may be used, and 0 may be adopted as a discrimination point (boundary value of Z1) (see FIG. 4). In addition, the sample (lettuce)
Belongs to group B or group C (the residual concentration of TPN is
1.0 ppm or less) is determined using the quadratic discriminant function equation (5) as the discriminant function equation, and an appropriate discriminant point (boundary value of Q) in the range of -0.5 to 0.5. A value may be adopted (see FIG. 5).

Therefore, in the present embodiment, in order to analyze pesticide residues from an unknown sample, equation (3) of the first canonical variable and equation (5) of the quadratic discriminant function correspond to the boundary of Z1 corresponding to them. The value and the boundary value of Q are stored in a memory in the personal computer 40.

[Analysis of Pesticide Residues] The formula of the discriminant function (the formula of the first canonical variable and the formula of the quadratic discriminant function) is derived, and when this is stored in the memory of the personal computer 40, it is an unknown sample. Analysis of pesticide residues (TPN) in crops (lettuce) becomes possible. The analysis of the residual pesticide is performed according to the procedure shown in FIG.

That is, first, the infrared absorption spectrum of the agricultural product as a sample is measured by the measurement S20 using the FTIR-ATR method using the interferometer 10, the ATR measuring device 20, and the control unit 30. The data of the infrared absorption spectrum (spectrum data) is transferred to the personal computer 40, and the personal computer 40 performs the determination S22 based on the canonical variables. That is, using the spectrum data of the sample, the value of the equation Z1 = 0.618 + 0.031A1 + 0.308A2 + 0.768A3 of the first canonical variable stored in the memory in the personal computer 40 is calculated, and this value is calculated as the boundary value of Z1. By comparing with a certain 0, it is determined whether or not the sample is “non-defective”. That is, if Z1 ≦ 0, TP, which is a residual pesticide from the sample,
N. is determined not to be detected, and the result of the determination of “good” is output to the display unit of the personal computer 40.

On the other hand, if Z1> 0, it is determined that a TPN has been detected, and a determination S24 is made by a secondary determination function in order to determine whether or not the residual concentration of the TPN is equal to or less than an allowable value. That is, using the spectral data of the sample, wherein the quadratic discriminant function stored in the memory of the personal computer ^{40 Q = -0.091A1 2 + 0.038A2 2} -1.082A3 2 -0.077A1A2-0.144A2A3 -0.825A3A1-1.493 A value of A1−0.88A2−3.55A3 + 0.335 is calculated, and this value is compared with the boundary value of Q corresponding to the allowable value to determine whether the sample is “good” or “defective”. As described above, 1 ppm, which is the standard concentration for registration registration of the Ministry of Health and Welfare, is adopted as an allowable value. Here, 0 is adopted as a boundary value of Q corresponding to this allowable value of 1 ppm. In this case, if Q ≧ 0, it is determined that the residual concentration of TPN in the sample is equal to or less than the allowable value of 1 ppm, and a determination result of “good” is output to the display unit of the personal computer 40. It is determined that the residual concentration of TPN exceeds the allowable value of 1 ppm, and the result of the determination of "defective" is output to the display unit of the personal computer 40.

[Effect] The pesticide residue analysis system of the present embodiment does not require pretreatment as in the conventional analysis using a chromatograph or the like. The time required for the measurement S20 by the FTIR-ATR method is about 10 minutes, and the data processing for discrimination by the personal computer 40 is about 5 minutes thereafter. Therefore, according to the present embodiment, the time required to obtain an analysis result is significantly reduced as compared with a conventional analysis system requiring 4 to 5 hours or more. Further, the discriminant analysis adopted in this example can be applied to other pesticide components other than TPN as long as the pattern of the infrared absorption spectrum is clear. Therefore, the pesticide components that can be analyzed as in the case of utilizing the antibody-antigen reaction are not limited.

[Modification] In the above embodiment, the analysis of the TPN remaining in the lettuce is performed, but the present invention is not limited to the sample of the lettuce. For example, the residual pesticide analysis system having the same configuration as that of the above-described embodiment (the equation of the discriminant function is the same as that obtained for lettuce) is used to determine whether TPN remaining in Chinese cabbage or celery is detected, and whether the residual concentration of TPN is determined. A correct answer rate of about 80% was obtained in determining whether the content was 1 ppm or less. Therefore, the pesticide residue analysis system of the above embodiment can be applied to other agricultural products such as Chinese cabbage and celery.

In the above embodiment, the spectrum data obtained by the FTIR-ATR method is transferred from the control unit 30 to the personal computer 40, and the personal computer 40 performs the discrimination by the discriminant function. Alternatively, in the case where the control unit 30 is realized by a data processing device having the same data processing capability, the control unit 30 may perform the determination using the above-described determination function.

[0033]

As described above, according to the present invention, the time required to determine whether the concentration of a pesticide remaining in lettuce, Chinese cabbage, celery, etc. is below an allowable value is greatly reduced as compared with the conventional method. Is done. For this reason, the analysis of the residual pesticide can be completed within a limited time from when the crop is harvested to when it is shipped, and the safety of the crop can be confirmed before distribution. In addition, in the present invention, the analysis can be performed if a clear pattern of the infrared absorption spectrum is obtained, so that the pesticide component that can be analyzed is not limited as in the case of using an antibody-antigen reaction.

[Brief description of the drawings]

FIG. 1A is a diagram showing a procedure for deriving a discriminant function in a pesticide residue analysis system according to one embodiment of the present invention, and FIG. 1B is a diagram showing an analysis procedure.

FIG. 2 is a diagram showing a hardware configuration of a pesticide residue analysis system according to one embodiment of the present invention.

FIG. 3 is a diagram showing classification of samples according to residual concentrations of pesticides.

FIG. 4 is a scatter diagram of a sample group in a two-dimensional feature space using two canonical variables.

Fig. 5 Pesticide residue TP by gas chromatography
The figure which shows the value of the quadratic discriminant function about each sample from which N. was detected.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 ... Interferometer 20 ... ATR measuring device 30 ... Control part 40 ... Personal computer S10 ... Measurement by FTIR-ATR method S16 ... Discriminant analysis S20 ... Measurement by FTIR-ATR method S22 ... Discrimination by canonical variables S24 ... Second discriminant function Discrimination by

──────────────────────────────────────────────────の Continued on the front page (72) Inventor Eiji Toba 14-6 Ueno, Ueda City, Nagano Prefecture (72) Inventor Katsuhiko Ichimura 1 Nishinokyo Kuwaharacho, Nakagyo-ku, Kyoto Shimazu Works Sanjo Plant (56) Reference Document JP-A-3-166343 (JP, A) JP-A-2-312543 (JP, A) JP-A-3-30657 (JP, A) Transactions of the Society of Instrument and Control Engineers, Japan, August 31, 1993, V29, N8, p993-999 Transactions of the Society of Instrument and Control Engineers, Japan, December 31, 1994, V30N12, p1436-1441 (58) Fields investigated (Int. Cl. ⁷ , DB name) G01N 21/00-21 / 01 G01N 21/17-21/61 JICST file (JOIS) Practical file (PATOLIS) Patent file (PATOLIS)

Claims (1)

(57) [Claims] 1. A method for analyzing residual pesticides, which determines whether the concentration of the pesticide component remaining on the surface of the agricultural product is below an allowable value, comprising: a) a method in which the residual concentration of the pesticide component is a known value; The data of the infrared absorption spectrum by the pesticide component on the surface of the crop of
A first step of sampling by the R method, b) using the data collected in the first step, the plurality of crops are divided into a group of non-residue agricultural chemicals and a group of residual agricultural chemicals based on a predetermined detection limit value. A second step of deriving an expression of a canonical variable and a first boundary value corresponding to the classification by performing classification and discriminant analysis; c) using the data collected in the first step, By performing the discriminant analysis by classifying the agricultural chemical component residual agricultural crop group into two agricultural crop groups depending on whether the concentration of the agricultural chemical ingredient is equal to or less than an allowable value, the expression of the secondary discriminant function corresponding to the classification and the second And d) an ATR method using an infrared spectrophotometer, wherein the infrared concentration of the pesticide component on the surface of the crop to be analyzed whose residual concentration is unknown is determined by an ATR method using an infrared spectrophotometer. E) calculating the value of the canonical variable using the data of the canonical variable by using the data collected in the fourth step, and setting the value as a first boundary value. A fifth step of determining whether or not the pesticide component remains on the surface of the crop to be analyzed by comparison; f) when it is determined that the pesticide component remains in the fifth step; Calculating the value of the quadratic discriminant function using the data of the quadratic discriminant function using the data collected in the fourth step, and comparing the calculated value with a second boundary value to obtain the surface of the crop to be analyzed. A sixth step of determining whether the concentration of the pesticide component remaining in the soil is below an allowable value.