JPH0518892A - Determination of iodine value and acid value of fats and oils - Google Patents

Abstract

PURPOSE:To obtain an optical measurement method for determining the iodine value and acid value of fats and oils by using data projectively transformed from the absorption of infrared light (absorbance). CONSTITUTION:With a device for spectrophotometer using a plurality of specific wave lengths, various output fluctuations including the temperature fluctuation of fats and oils are measured for each wave length in advance. Regarding them as vectors in the space with dimensions of the number of measured wavelengths, partial spaces perpendicular to all the vectors are obtained. By obtaining the absorbance of a plurality of fats and oils of which iodine value or acid value are known, they are converted to the data projected to the above partial spaces. A measurement curve equation indicating the relation between the projected data and the iodine value or acid value is obtained.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for quantifying the iodine value and acid value of fats and oils by utilizing infrared absorption.

[0002]

2. Description of the Related Art In conventional methods for quantifying the iodine value and acid value of fats and oils by utilizing infrared absorption, first, the iodine value (or acid value) is known using a plurality of wavelengths (for example, n). The absorbance A of the sample (liquid) is measured. Next, a calibration curve formula (for example, the following formula) representing the correlation between the data A and the iodine value (or acid value) C is determined. C = P ₁ A ₁ + P ₂ A ₂ + ... + P _n A _n + P ₀ (1) where A _i (i = 1 to n) is the absorbance of each wavelength, P _i is a coefficient,
C is an iodine value (or acid value). The coefficient P uses the absorbance measured for n or more reference samples whose iodine value (or acid value) is known by other means so that the difference between the known amount and the calculated value by the calibration curve formula is minimized. (Using, for example, the least squares method). For an unknown sample, the iodine value (or acid value) can be calculated from the absorbance using a calibration curve formula.

In the automatic esterification method disclosed in Japanese Unexamined Patent Publication No. 2-306936, the acid value is measured by an infrared absorption spectrum measuring device to control the esterification reaction.

[0004]

Since the data (absorbance) obtained by the spectroscopic measurement contains various errors, it is necessary to remove them by some method. Causes of this error include sample scattering, light source variation, and sample temperature. In the conventional method, these errors can be removed by including them evenly when measuring the sample used when obtaining the calibration curve formula. The sample temperature should be kept constant. However, in reality, it is difficult to evenly include these errors, and it is not possible to guarantee that the obtained calibration curve formula can remove these errors. Furthermore, since the temperature of the sample is kept constant, the spectroscopic device becomes complicated and the temperature control itself is difficult.

Further, hydrogenation is carried out in order to produce oils and fats having the required iodine value. This step is performed in an autoclave and the temperature is usually in the range of 100 to 200 ° C. If this is cooled and the iodine value is measured, the measurement will take time. When used in factory automation, it is required to measure and feed back as quickly as possible, so it is desirable that the absorbance can be measured at high temperature.

[0006] For a sample which solidifies at room temperature, it is necessary to measure it in a state of being melted at a high temperature.
A sample that does not solidify should be measured at room temperature. In the conventional method, it can be dealt with by creating a calibration curve for each temperature (for example, at each temperature of 100 ° C., room temperature, and 0 ° C.), but this creation requires a huge amount of samples and measurements.

The applicant of the present invention, in Japanese Patent Application No. 2-4042, has various error fluctuations (including temperature) from the spectroscopic measurement data.
A spectroscopic measurement method capable of efficiently removing the above has been disclosed. In this spectroscopic measurement method, output variation data per unit is obtained in advance for each wavelength for each error variation contained in the spectroscopically measured data, and then these various output variation data are measured in the number of measurement wavelengths. It is regarded as a vector in space, and a vector orthogonal to all these vectors is obtained.
The subspace consisting of these vectors is a space that is completely unaffected by the above-mentioned various error variations. Then, the photometric data at each wavelength of the known samples of which the number is equal to or larger than the dimension of the subspace is regarded as a vector, and the vector is projected onto this subspace. (That is, coordinate conversion is performed in the space of the dimension of the number of measured wavelengths, and converted into data that is not affected by various fluctuation errors.)
Based on this projection data, a calibration curve formula of the physical quantity or chemical quantity to be measured is obtained. Therefore, this calibration curve formula is not affected by the above-mentioned various output fluctuations. This application discloses the results of densitometry.

The present invention provides an optical measurement method for quantitatively determining the iodine value and the acid value of oils and fats by eliminating the effects of various error fluctuations, particularly temperature fluctuations, by using the data obtained by projectively converting infrared absorption (absorbance). With the goal.

[0009]

In an apparatus for spectrophotometry at a plurality of predetermined wavelengths, as shown in FIG. 2, output fluctuations are measured for each wavelength for each of various output fluctuation causes (including temperature). (Step S1). By including the change in the temperature of oil and fat as one of various output fluctuations,
It enables measurement that is not affected by the temperature of fats and oils. next,
Each output fluctuation data is considered as a vector in a space having a dimension of the number of measured wavelengths, and a subspace orthogonal to all the vectors is obtained (step S2). With respect to a plurality of samples of which the iodine value (or acid value) of fats and oils is known, measurement is performed at each wavelength to obtain the absorbance (step S3).
Next, the absorbance data is converted into the data projected onto the subspace (step S4). Next, a calibration curve formula representing the correlation between the projected data and the iodine value (or acid value) of the oil and fat is obtained (step S5). In the measurement of the unknown sample, the sample is subjected to spectroscopic measurement at each wavelength to obtain the absorbance (step S11). Next, the absorbance data is converted into the data projected onto the subspace (step S12). Next, the iodine value (or acid value) of the projected data is calculated using the above calibration curve formula (step S13). When obtaining the absorbance, usually, the reference sample is preliminarily measured as air, and the following equation is used to calculate the measured value of the sample to be measured.

[Equation 1] However, preferably, the reference sample is one whose measured value is close to that of the fat or oil to be measured (fatty acid, predetermined fat or oil, etc.), so that the quantitative accuracy is improved. The reference samples that were confirmed to be usable are saturated fatty acids such as fats and oils, caproic acid, lauric acid, myristic acid, palmitic acid, and stearic acid, and unsaturated compounds such as palmitoleic acid, oleic acid, linoleic acid, linolenic acid, and eicosenoic acid. Fatty acid, hexane, ethanol, triacetylene, glycerin, ethyl acetate, butyl acetate, amyl acetate, tripalmitin,
It is trimyristin. The reference sample must be a liquid in the measuring temperature range.

[0010]

[Function] In an apparatus for spectroscopic measurement at a plurality of predetermined wavelengths, various output fluctuations including temperature fluctuations of oils and fats are measured in advance for each wavelength, and are regarded as vectors in the space of the dimension of the number of measured wavelengths, and all vectors are calculated. Find orthogonal subspaces. Absorbances of a plurality of fats and oils having a known iodine value (acid value) are measured and converted into data projected on the above partial space. A calibration curve formula representing the correlation between the projected data and the iodine value (acid value) from which the effects of such temperature fluctuations have been removed is obtained. Then, the iodine value (acid value) of the fat is measured using this calibration curve formula. When the present invention is used, one and the same calibration curve can be used even if the temperature or the like fluctuates, so that the measurement can be greatly simplified.

[0011]

Embodiments of the present invention will be described below with reference to the accompanying drawings. FIG. 1 shows the configuration of a transmission type spectroscopic measurement device used in an example of the present invention. In this device, the light emitted from the light source 1 is condensed on the interference filter 3 by the lens 2 and is dispersed. Six interference filters 3 for different wavelengths are attached to the disk 4 and rotate at a speed of 15 times per second. The light transmitted through the interference filter 3 is reflected by the lens 5
Is focused on the cell 6. A liquid sample 7 is injected into the cell 6. The light transmitted through the sample 7 is focused on the sensor 9 by the lens 8. The sensor 9 converts an optical signal into an electric signal. The data processing unit 11 separates the electric signal from the sensor 9 into signals of 6 wavelengths and converts them into digital values by AD conversion. Then, using the reference (blank) data, the absorbances A _i (i = 1 to 6) of 6 wavelengths are calculated by the following formula. A _i = −log (I _i / I _0i ) (3) where I _i and I _0i are the sample transmitted light intensity and the reference (blank) transmitted light intensity at the i-th wavelength. Further, after the data processing described below is performed, the result is recorded by the recorder 1.
Output to 2.

Next, in order to avoid various error fluctuations, the output values (absorbance) A _i of the 6 wavelengths are converted into data not affected by the error fluctuations by the method described below (hereinafter, this is referred to as projective conversion). First, the output changes ΔA ₁ , ΔA ₂ , ..., ΔA ₆ of 6 wavelengths with respect to the temperature change of the sample are set as a vector T of several dimensions of the measurement wavelength. T = (ΔA ₁ , ΔA ₂ , ..., ΔA ₆ ) (4) Similarly, the variation due to the influence of the scattering of the sample and the output variation due to the instrument variation are respectively set as vectors S and M of the measurement wavelength number dimension. Then, a subspace orthogonal to the three vectors T, S, and M is obtained in the measurement wavelength dimensionally dimensional space. That is, a vector P satisfying P · S = 0 P · T = 0 (5) P · M = 0 is obtained. There are three independent solutions, which are P ₁ , P ₂ , and P ₃ . Then, the output values (absorbance) of 6 wavelengths A ₁ , A ₂ , ..., A ₆ are similarly set as a vector A of several dimensions of the measurement wavelength, and projected onto this subspace to obtain the data X _{1 which is} not affected by the error variation. , X ₂ , X ₃ . Then, based on these X ₁ , X ₂ , and X ₃ , the coefficient Q _i of the calibration curve formula for the iodine value c or the acid value d of the measurement object is determined. As the calibration curve formula, for example, the following formula is used. c = Q ₁ X ₁ + Q ₂ X ₂ + Q ₃ X ₃ + Q ₀ (6) In the determination of iodine value and acid value of an unknown sample,
An output value (absorbance) A _i (i = 1 to 6) at 6 wavelengths is obtained by using the measuring apparatus of FIG. 1, the data is converted into X _i by projective transformation, and the iodine is calculated by a calibration curve formula. Calculate the value c or the acid value d.

An example of determining the iodine value of edible oil is shown below. Here, the measurement wavelength is 1020, 1040, 1180, 121
0,1300,1330,1400,1445,1480,1
680, 1730, 1780, 1820, 1850, 188
0,1910,1950,2000,2050,2090,2
100,2140,2160,2180,2210,227
Six wavelengths were selected from 0.2340 (unit nm) and used. In the measurement examples below, the used wavelengths are 1020 and 118.
0, 1210, 1300, 1330, 1480 nm. Also, a reference sample (blank) for determining absorbance
For this, edible oil was used.

First, the temperature of typical edible oil is set to 2
The change in absorbance when the temperature was changed from 0 ° C. to 70 ° C. was obtained and used as an error variation vector T depending on temperature. T = (0.0038,0.0027,0.0019,0,3.001,0.001 9,0.0084) (7) Further, assuming that the device fluctuation does not have wavelength dependency, the error fluctuation vector M Was set to M = (1,1,1,1,1,1,1) (8). The fluctuation due to scattering of the sample was not considered.

Four vectors P _j orthogonal to the two vectors T and M were obtained. The projected subspace is represented by these four vectors. P ₁ = (− 0.76, 0.62, 0, 0, 0, 0.14) P ₂ = (− 0.17, −0.41, −0.27, 0, 0, 0.85) _{P 3 = (- 0.17, -0.24} , 0.81, -0.5, 0, 0.11) P 4 = (- 0.32, -0.33, -0.06, 0. 12, 0.84, -0.24) (9) Six wavelengths of measurement data A _i (i = 1 to 6) are used as absorbance vectors A = (A ₁ , A ₂ , A ₃ , A ₄ , A ₅ , A) ₆ ) If (10), the data X _j (j = 1 to 4) projected onto the subspace
X _j = P _j · A (j = 1 to 4) (11)

Next, the absorbance was measured for 60 reference samples of edible oil having an iodine value of 60 to 150, and the data X _j (j = 1 to 4) projected on the subspace were obtained. Using this data, the following calibration curve formula is used to minimize the difference between the true iodine value and the calculated value obtained by the calibration curve formula.
(Least squares method) was used for calculation. c = Q ₁ X ₁ + Q ₂ X ₂ + Q ₃ X ₃ + Q ₄ X ₄ + Q ₀ (12) Here, c is an iodine value and Q _i (i = 0 to 4) is a coefficient.
The true iodine value was determined by the analysis method prescribed by the Oil and Fat Testing Association. In addition, this measurement was performed at 65 ° C. in consideration of the melting point of an extremely hydrogenated oil (one obtained by adding hydrogen to all unsaturated portions (double bonds) of fatty acids in fats and oils).

Next, cooking oil (with an iodine value of 60 to 15)
Regarding 0), the absorbance was measured to obtain the data projected on the subspace, and the iodine value was calculated using the calibration curve formula obtained previously. Table 1 shows the calculation results with respect to the true iodine value. This measurement was performed at an appropriate temperature at which the edible oil did not solidify. The true value was determined by the analysis method prescribed by the Oil and Fat Testing Association.

For comparison, the subspace to be used for projection is determined without considering the fluctuation of the output due to temperature, a calibration curve formula is prepared using the same edible oil as above, and the same edible oil is quantified. went. The results at this time are shown in Table 2. Comparing Table 1 and Table 2, it can be seen that the quantitative accuracy is obviously improved by considering the temperature variation.

[Table 1]

[Table 2]

Table 3 shows the reference sample (blank).
The measured values when air is used as the above are shown. Table 3 and Table 1
From the comparison, it can be seen that even if air is used as a blank, the quantitative accuracy is obviously improved by considering the temperature variation.

[Table 3]

Next, an example of determining the acid value of fats and oils will be shown for edible oils. Here, the measurement wavelength is 1020,1180,121
Six wavelengths of 0, 1300, 1330, and 1480 (unit nm) were used. Further, edible oil was used as a reference sample (blank) for obtaining the absorbance. First, with respect to a typical edible oil, the change in the absorbance when the temperature was changed from 20 ° C. to 70 ° C. was obtained and used as an error variation vector T depending on the temperature. T = (0.38, 0.27, 0.19, 0, 3.1, 0.19, 0.84) (13) Further, it is assumed that the device fluctuation does not have wavelength dependence, and the error fluctuation vector M is M = (1,1,1,1,1,1,1) (14) The fluctuation due to scattering of the sample was not considered. Four vectors P _j orthogonal to these two vectors T and M were obtained. The projected subspace is represented by these four vectors. _{P 1 = (- 0.76, 0.62} , 0, 0, 0, 0.14) P 2 = (- 0.17, -0.41, -0.27, 0, 0, 0.85) _{P 3 = (- 0.17, -0.24} , 0.81, -0.5, 0, 0.11) P 4 = (- 0.32, -0.33, -0.06, 0. 12, 0.84, -0.24) (15) Measured data A _i (i = 1 to 6) of 6 wavelengths is represented by an absorbance vector A = (A ₁ , A ₂ , A ₃ , A ₄ , A ₅ , A). ₆ ) (16), the data X _j (j = 1 to 4) projected onto the subspace
X _j = P _j · A (j = 1 to 4) (17)

Here, the absorbance was measured for 30 samples of edible oil having an acid value of 0.1 to 0.5, and the data X _j (j = 1 to 4) projected on the subspace was obtained. Using this data, the following calibration curve equation was calculated using the method of least squares. d = R ₁ X ₁ + R ₂ X ₂ + R ₃ X ₃ + R ₄ X ₄ + R ₀ (18) Here, d is an acid value and R _i (i = 0 to 4) is a coefficient. The true acid value was determined by the analysis method prescribed by the Oil and Fat Testing Association. The measurement was performed at 65 ° C.

Next, the absorbance of edible oil (with an acid value of 0.1 to 0.5) was measured to obtain the data projected on the subspace, and the acid value was calculated using the calibration curve formula obtained previously. I calculated.
Table 4 shows the calculation results with respect to the true acid value. This measurement was performed at an appropriate temperature at which the edible oil did not solidify. The true value was determined by the analysis method prescribed by the Oil and Fat Testing Association.

[Table 4]

[0023]

The same calibration curve can be used in the spectroscopic measurement of the iodine value and the acid value of fats and oils, so that the measurement can be greatly simplified even if the temperature changes. Even if a calibration curve is not created for each temperature, the iodine value and acid value of fats and oils can be accurately measured without being affected by fluctuations such as temperature. Therefore, an enormous amount of samples and measurements for creating a calibration curve that incorporates the effect of temperature fluctuations are unnecessary. Further, the step of hydrogenation for producing a fat and oil having a required iodine value is usually carried out in an autoclave in the range of 100 to 200 ° C, but the absorbance can be measured at a high temperature.

[Brief description of drawings]

FIG. 1 is a diagram showing a configuration of an infrared transmitted light measuring device.

FIG. 2 is a flowchart for determining a calibration curve for iodine value and acid value.

FIG. 3 is a flowchart for measuring iodine value and acid value.

[Explanation of symbols]

3 ... Filter, 6 ... Cell, 7 ... Sample, 9 ...
Sensor, 11 ... Data processing device.

Claims (4)

[Claims] 1. An apparatus for spectrophotometry at a plurality of predetermined wavelengths, for each of the various output fluctuation causes including the temperature change of oil and fat, the output fluctuation is measured for each wavelength, and then each output fluctuation data is respectively measured. Considered as a vector in the space of the dimension of the number of measurement wavelengths, determine the subspace orthogonal to all these vectors, for a plurality of samples for which the iodine value of fats and oils is known,
Measurement is performed at each wavelength to obtain the absorbance, then the absorbance data is converted into data projected onto the above subspace, and then a calibration curve showing the correlation between the projected data and the iodine value of oil and fat. A method for determining the iodine value of fats and oils, characterized by obtaining a formula. 2. The iodine value determination method for fats and oils according to claim 1, wherein the absorbance is determined using a fatty acid or a predetermined fat and oil as a reference sample. 3. In an apparatus for spectrophotometry at a plurality of predetermined wavelengths, output fluctuation is measured for each wavelength for each of various output fluctuation causes including temperature change of oil and fat, and then each output fluctuation data is measured. Considered as a vector in the space of the dimension of the number of wavelengths, determine the subspace orthogonal to all the vectors, multiple samples for which the acid value of fats and oils is known, perform measurement at each wavelength, determine the absorbance, and then A method for quantifying the acid value of fats and oils, which comprises converting the absorbance data into data projected onto the above-mentioned subspace, and then obtaining a calibration curve formula representing the correlation between the projected data and the acid value of the fats and oils. 4. The method for determining the acid value of oil or fat according to claim 3, wherein the absorbance is determined using a fatty acid or a predetermined oil or fat as a reference sample.