JP2020112478A - Estimation method of fatty acid ester content - Google Patents

Abstract

To highly accurately and easily estimate a fatty acid ester content of an estimation object specimen.SOLUTION: An estimation method of a fatty acid ester content comprises: a measurement step (a step S110) of measuring a near-infrared spectrum of a specimen in a measurement wavelength region including a wavelength region capable of measuring a combination tone of a fatty acid ester molecule; a quantitative determination step (a step S120) for quantitatively determining a content of the fatty acid ester as the specimen; a regression step (a step S130) of performing regression analysis by defining the near-infrared spectrum data measured in the measurement step as an explanatory variable and the fatty acid ester content data quantitatively determined in the quantitative determination method as an objective variable, and acquiring a regression equation; and an estimation step (a step S140) of measuring the near-infrared spectrum of the estimation object specimen, applying the measurement result of the near-infrared spectrum of the estimation object specimen to the regression equation acquired in the regression step, and estimating content of the fatty acid ester of the estimation object specimen.SELECTED DRAWING: Figure 2

Description

The present invention relates to a method for estimating a fatty acid ester content in a liquid such as biodiesel fuel, and particularly to a method for estimating a fatty acid ester content in a sample to be estimated using near infrared spectroscopy.

Biodiesel fuel is a fatty acid ester produced by the transesterification reaction of fats and oils and alcohol, and can be used as an alternative fuel for diesel oil in diesel engines such as trucks and generators. In general, biodiesel fuel uses fats and oils derived from animals and plants as a raw material. Therefore, it is possible to apply the concept of carbon neutral that carbon dioxide emitted from combustion of biodiesel fuel is originally carbon dioxide fixed in the atmosphere. That is, by using biodiesel fuel as an alternative fuel for light oil, it is possible to suppress the generation of carbon dioxide derived from combustion of fossil fuel, which is a cause of global warming. That is, biodiesel fuel is an environmentally friendly fuel.

Biodiesel fuel can be produced by transesterification of fats and oils and alcohol. As the oils and fats, for example, a wide variety of animal and vegetable oils such as rapeseed oil, sunflower oil, palm oil, safflower oil, lard and their used oils can be used. As the alcohol, for example, alcohols such as methanol, ethanol, propanol, butanol, octanol and the like can be used. In Japan, it is common to produce biodiesel fuel from spent oil and methanol used in tempura etc. to reduce raw material costs.

Biodiesel fuel is required to have stable quality because it is used for diesel engines such as trucks and generators. Therefore, in Japan, standardization of fuel quality according to JIS (JIS K 2390: Automotive fuel-fatty acid methyl ester for mixing (FAME)) has been made only for those used for automobile fuel. The quality standard of biodiesel fuel according to this JIS standard covers 26 items in total, and analysis of all items is very time-consuming and difficult to use for daily quality control. Therefore, it is a general quality control method to confirm only the fatty acid ester content, which represents the purity itself of biodiesel fuel.

Conventionally, when measuring a fatty acid ester content, it is common to perform analysis using a gas chromatograph. However, when measuring the fatty acid ester content using a gas chromatograph, analysis of one sample requires about 2 hours of analysis time. Further, it is necessary to dilute the sample and adjust the analysis conditions before the analysis. Therefore, a simpler analysis method is eagerly desired. In addition, biodiesel fuel manufacturers rarely own gas chromatographs for financial reasons, and an analytical engineer with specialized knowledge is required to use the gas chromatographs. Therefore, the gas chromatographic analysis method cannot be said to be suitable for the routine quality control method of biodiesel fuel.

Near-infrared spectroscopy is a method of investigating the components and physicochemical properties by utilizing the absorption characteristics of near-infrared light having a wavelength of 800 nm to 2500 nm, which is between visible light and mid-infrared light. Correlation between characteristic values such as chemical analysis and physical property measurement and near-infrared absorption makes it possible to perform qualitative and quantitative analysis of target components from near-infrared absorption. It can be replaced by external spectroscopy. For example, as an analysis method using near-infrared spectroscopy, Patent Document 1 describes a method for estimating the meat quality of beef cattle, and Patent Document 2 describes a method for measuring water and protein in frozen surimi. Is described, and Patent Document 3 describes a method for quantifying free fatty acids in vegetable oils and fats.

JP 2001-264249 A JP, 2008-89529, A JP, 2005-135323, A

As described above, as a conventional technique, there is a method of measuring a fatty acid ester content using a gas chromatographic analysis method, but an engineer who is familiar with expensive analyzers and instrumental analysis is required. Therefore, it is required to provide a quick and simple method for measuring the content of fatty acid ester, which is an alternative to the existing analysis method using the gas chromatographic analysis method in quality control of biodiesel fuel.

On the other hand, the near-infrared spectroscope can be acquired at a relatively low price, and there is no need to dilute the sample or adjust the analysis conditions as with gas chromatographic analysis. Qualitative and quantitative analysis of is possible. However, a technique using near-infrared spectroscopy for estimating the fatty acid ester content has not yet been investigated.

The quality standards of biodiesel fuel are very strict, which requires high accuracy in estimating the fatty acid ester content. Therefore, for example, the accuracy of the method for quantifying the free fatty acid of vegetable oil as described in Patent Document 3 may not be sufficient. Specifically, the correlation coefficient (coefficient of determination) in Patent Document 3 is 0.708 to 0.978 as shown in Table 2, and is generally insufficient for use in estimating the fatty acid ester content. is there.

Therefore, the inventors of the present invention have earnestly studied about a method for measuring a fatty acid ester content in a quick and simple manner, which is an alternative to an analysis method using an existing gas chromatographic analysis method in the quality control of biodiesel fuel. It was confirmed that the fatty acid ester content can be estimated with high accuracy by using near infrared spectroscopy. Then, by performing an appropriate spectral processing on the near infrared spectrum obtained by using the near infrared spectroscopy under the predetermined condition and performing regression analysis, a high correlation with the gas chromatographic analysis quantitative value is obtained. It was confirmed that a certain calibration curve could be obtained.

An object of the present invention is to easily and accurately estimate the fatty acid ester content of a sample to be estimated.

A method for estimating a fatty acid ester content of a first aspect of the present invention for solving the above-mentioned problems is to measure a near infrared spectrum of a sample in a measurement wavelength region including a wavelength region in which a bond sound of a fatty acid ester molecule can be observed. Measuring step to quantify, the quantitative step of quantifying the content of the fatty acid ester of the sample, the content of the near-infrared spectrum measured in the measuring step as an explanatory variable, the content of the fatty acid ester quantified in the quantitative step Using the data of as a target variable, a regression step of performing a regression analysis to obtain a regression equation, measuring the near-infrared spectrum of the estimation target sample, and obtaining the measurement result of the near-infrared spectrum of the estimation target sample in the regression step. And an estimation step of estimating the fatty acid ester content of the estimation target sample by applying the regression equation.

According to this aspect, once the regression equation can be obtained, it is possible to estimate the fatty acid ester content of the estimation target sample with high accuracy only by near-infrared spectroscopy without using gas chromatographic analysis. .. Then, for example, the fatty acid ester content in the biodiesel fuel can be estimated in a few minutes, and the measurement time is significantly shorter than the required time (about 2 hours) of the conventional gas chromatographic analysis method. In addition, near-infrared spectroscopy does not require dilution of a sample or adjustment of analysis conditions, and therefore can perform measurement quickly and easily. In this way, by using the fatty acid ester content estimation method of this embodiment as a daily quality control method at the time of manufacturing, shipping, receiving, and using products, stable quality biodiesel fuel can be handled. Becomes

The method for estimating a fatty acid ester content according to the second aspect of the present invention is characterized in that, in the first aspect, the measurement wavelength region includes a wavelength region of 2000 nm or more and 2500 nm or less.

In general, the wavelength region in which the bond sound of the fatty acid ester molecule can be observed is a wavelength region of 2000 nm or more and 2500 nm or less. Therefore, according to this aspect, the fatty acid ester content of the estimation target sample can be easily estimated with high accuracy. You can

The method for estimating a fatty acid ester content according to a third aspect of the present invention is characterized in that, in the second aspect, the measurement wavelength region is only within a wavelength region of 2000 nm or more and 2500 nm or less.

According to this aspect, it is possible to prevent a region other than the wavelength region in which the binding sound of the fatty acid ester molecule can be observed from being included in the measurement wavelength region in a large amount, and to suppress a decrease in estimation accuracy of the fatty acid ester content.

In the method for estimating the fatty acid ester content according to the fourth aspect of the present invention, in the second or third aspect, the measurement wavelength region is 2250±10 nm, 2260±10 nm, 2310±10 nm, 2330±10 nm, 2350. At least one of ±10 nm and 2370±10 nm is included.

According to this aspect, it is possible to effectively include the wavelength region in which the bond sound of the fatty acid ester molecule can be observed, and it is possible to suppress a decrease in estimation accuracy of the fatty acid ester content.

A method for estimating a fatty acid ester content according to a fifth aspect of the present invention is the method for measuring near-infrared spectra of the sample and the estimation target sample according to any one of the first to fourth aspects, wherein a transmission measurement method is used. And a diffuse reflectance measurement method.

According to this aspect, the fatty acid ester content can be estimated by measuring the near-infrared spectrum of the sample and the sample to be estimated using either the transmission measurement method or the diffuse reflection measurement method.

The method for estimating the fatty acid ester content according to the sixth aspect of the present invention is the method for estimating the fatty acid ester content according to any one of the first to fifth aspects, wherein in the regression step, the data of the near-infrared spectrum measured in the measurement step is used. On the other hand, it is characterized in that the differential processing is applied and then used as an explanatory variable.

According to this aspect, by applying the differential processing to the data of the near-infrared spectrum measured in the measurement step, the disturbance can be easily excluded and the fatty acid ester content can be estimated with high accuracy.

The method for estimating a fatty acid ester content according to the seventh aspect of the present invention is characterized in that, in any one of the first to sixth aspects, the regression analysis is a partial least squares regression analysis.

According to this aspect, the fatty acid ester content can be estimated with high accuracy by using the partial least squares regression analysis as the regression analysis.

The method for estimating a fatty acid ester content according to an eighth aspect of the present invention is the method according to any one of the first to seventh aspects, wherein the fatty acid ester is at least one of alkyl oleate, alkyl linoleate and alkyl linolenate. It is characterized by including one.

According to this aspect, the fatty acid ester content can be estimated with high accuracy.

It is a near-infrared spectrum of methyl oleate in a wavelength range of 800 nm to 2500 nm. The flowchart showing an example of the estimation method of fatty acid ester content of this invention. 5 is a diagram showing a correlation between a gas chromatographic analysis quantitative value and a near infrared spectrum estimated value at the time of regression analysis in Example 1. FIG. 5 is a diagram showing a correlation between a gas chromatographic analysis quantitative value and a near-infrared spectrum estimated value at the time of regression analysis in Example 2. FIG. 8 is a diagram showing a correlation between a gas chromatographic analysis quantitative value and a near infrared spectrum estimated value at the time of regression analysis in Example 3. FIG. FIG. 5 is a diagram showing a correlation between a gas chromatographic analysis quantitative value and a near infrared spectrum estimated value at the time of regression analysis in Reference Example 1. 7 is a diagram showing a correlation between a gas chromatographic analysis quantitative value and a near infrared spectrum estimated value at the time of regression analysis in Reference Example 2. FIG.

The method for estimating the fatty acid ester content of the present invention will be described in detail below.

[Fatty acid ester]
The fatty acid ester of the present invention can be used, for example, as a biodiesel fuel. Here, the fatty acid ester in the present invention is not particularly limited as long as it is an ester compound of oil and fat and alcohol. Examples of fats and oils include linseed oil, sunflower oil, tung oil, safflower oil, cottonseed oil, corn oil, soybean oil, canola oil, rapeseed oil, sesame oil, rice oil, olive oil, peanut oil, castor oil, cocoa butter, palm oil, Examples thereof include animal and vegetable oils and fats such as palm kernel oil, coconut oil, honeywort oil, linden oil, curcas oil, beef tallow, lard, milk fat and fish oil, and used oils thereof. Examples of alcohols include methanol, ethanol, propanol, butanol, pentanol, and hexanol.

Further, the fatty acid ester of the present invention is an ester compound of the oils and fats and alcohols mentioned above, and by an ester exchange reaction by an alkali catalyst method, an acid catalyst method, a lipase method, a supercritical alcohol method, an ion exchange resin method, or the like. Can be generated.

[Method of obtaining near infrared spectrum]
A near infrared spectroscope can be used as a method for obtaining a near infrared spectrum. The specifications of the near-infrared spectroscopic device are not limited, but those capable of using either the transmission measurement method or the diffuse reflection measurement method are preferable. As the light source of the near infrared spectroscopic device, a heat radiation light source, an LED light source, a semiconductor laser light source, a solid-state laser light source, or a supercontinuum light source can be used. As the light source, an inexpensive and stable thermal radiation light source is preferably used. As a spectral method of the near infrared spectroscopic device, a filter spectral method, a dispersion spectral method, and a Fourier transform spectral method can be used. As the spectroscopic method, a method using a dispersed spectroscopic method is preferable. A silicon photodiode, indium gallium arsenide, lead sulfide, a photomultiplier tube, or an image sensor can be used as the detector of the near-infrared spectroscopic device. The detector preferably uses an indium gallium arsenide detector.

The absorption spectrum of a molecule is observed in absorption spectroscopy such as near-infrared spectroscopy because when a molecule is irradiated with light in a certain wavelength range, the molecule absorbs light of a specific wavelength and changes from a low energy state. This is because it transits to a high energy state. In the near infrared region, electronic transitions, coupled sounds of vibrational transitions, and harmonics of vibrational transitions can be observed. As shown in FIG. 1, the absorption peak of the fatty acid ester molecule has a coupling sound in the near infrared region of 2000 nm to 2500 nm, a first overtone in the near infrared region of 1500 nm to 2000 nm, and a first harmonic in the near infrared region of 1000 nm to 1500 nm. The second harmonic can be observed as a broad band.

The near-infrared spectrum obtained by near-infrared spectroscopy may reduce the accuracy of analysis due to noise and baseline fluctuations added to the measured spectrum depending on the device specifications, measurement conditions, sample conditions, and the like. Therefore, it is desirable to perform spectrum processing in order to remove disturbances other than true information. As the spectrum processing, Kubelker-Munk conversion, differential spectrum processing, difference spectrum processing, SNV (standard normal vary) processing, MSC (multiplicative scatter correction) processing and the like can be used. Of these, it is preferable to use differential spectrum processing that can perform noise removal, correction of baseline fluctuation, and absorption band division processing all at once from the viewpoint of accuracy and easiness.

[Method for quantifying content of fatty acid ester]
A gas chromatographic analysis method can be used as a method for quantifying the content of the fatty acid ester in the sample. Hereinafter, an example of a general analysis method using a gas chromatographic analysis method will be described.

A capillary column with an inner diameter of about 0.25 mm and a stationary phase of polyethylene glycol is used as a separation column, a FID detector is used as a detector, helium is used as a carrier gas, and the sample vaporization chamber temperature is set to about 240° C. Is about 200° C., the detector temperature is about 250° C., and analysis is performed. The fatty acid ester content is quantified from the sample peak area and the internal standard peak area obtained by the gas chromatographic analysis method. Here, methyl heptadecanoate is used as an internal standard. In addition, when the viscosity of the analysis sample is high, it is desirable to appropriately dilute, and heptane, for example, can be preferably used as the diluting solution.

[regression analysis]
The near-infrared spectrum easily reflects physical characteristics such as the thickness and density of the sample, and the baseline of the spectrum easily changes. Therefore, the shape of the near infrared spectrum becomes complicated, and a large amount of numerical data must be calculated to estimate the fatty acid ester content. Therefore, as the regression analysis, it is possible to use a principal component regression analysis which is an analysis method utilizing chemometrics which is a mathematical/statistical technique, and a PLS (partial least squares) regression analysis which is a partial least squares regression analysis. it can. Among these, it is preferable to use PLS regression analysis from the viewpoint of accuracy and the like.

By performing a regression analysis using the spectrum data in the wavelength region used for the analysis as an explanatory variable and the quantitative value of the fatty acid ester content as an objective variable, the spectrum related to the fatty acid ester content can be determined as a factor to obtain a regression equation. It is necessary to evaluate the prediction accuracy of the obtained regression equation, and the root mean square (RMSE) of the error of the calibration curve, the correlation coefficient, the coefficient of determination, etc. can be used as the evaluation index. The closer the RMSE is to 0, and the closer the correlation coefficient and the determination coefficient are to 1, the higher the evaluation as the calibration curve.

The fatty acid ester content of the estimation target sample can be estimated by applying the regression equation obtained by the above regression analysis to the near-infrared spectrum data of the estimation target sample which is the target sample for estimating the fatty acid ester content. .. That is, once the regression equation can be obtained, it is possible to know the fatty acid ester content in the sample from the value of the near infrared spectrum without using the conventional gas chromatography method. Therefore, it is possible to provide a quick and simple method for measuring the fatty acid ester content. When measuring the near-infrared spectrum of the sample to be estimated, it is preferable to use the same near-infrared spectrum measuring apparatus, measurement method, and analysis method as when the regression equation was obtained.

[Example of method for estimating fatty acid ester content of the present invention]
Here, an example of the method for estimating the fatty acid ester content of the present invention will be summarized with reference to the flowchart in FIG.

First, in the measurement step of step S110, the near-infrared spectrum of the sample is measured in the measurement wavelength region including the wavelength region in which the bond sound of the fatty acid ester molecule can be observed. The sample used at this time may be one of the estimation target sample itself or the like, but may be a sample different from the estimation target sample.
Next, in the quantification step of step S120, the content of the fatty acid ester in the sample is quantified using a gas chromatographic analysis method or the like.
Next, in the regression step of step S130, the data of the near-infrared spectrum measured in the measurement step (step S110) is used as an explanatory variable, and the data of the content of the fatty acid ester quantified in the quantification step (step S120) is used as an object. As a variable, regression analysis is performed to obtain a regression formula.
Then, in the estimation step of step S140, the near-infrared spectrum of the estimation target sample is measured, and the measurement result of the near-infrared spectrum of the estimation target sample is applied to the regression equation obtained in the regression step (step S130). Then, the fatty acid ester content of the sample to be estimated is estimated.

If the above method for estimating the fatty acid ester content is performed, once the regression formula is obtained, the near-infrared spectroscopy alone can be used to obtain a high fatty acid ester content of the estimation target sample without using the gas chromatographic analysis method. The accuracy can be estimated. Then, for example, the fatty acid ester content in the biodiesel fuel can be estimated in a few minutes, and the measurement time is significantly shorter than the required time (about 2 hours) of the conventional gas chromatographic analysis method. In addition, near-infrared spectroscopy does not require dilution of a sample or adjustment of analysis conditions, and therefore can perform measurement quickly and easily. In this way, by using the fatty acid ester content estimation method of this embodiment as a daily quality control method at the time of manufacturing, shipping, receiving, and using products, stable quality biodiesel fuel can be handled. Becomes
<Example>

Specific examples will be described below. However, the present invention is not limited to the following examples.
<Example 1>

In this example, a mixture of oil and fat and fatty acid ester was used as a sample to estimate the fatty acid ester content. Triolein was used as the oil and fat, and methyl oleate was used as the fatty acid ester, and 11 kinds of samples having different mixed compositions were prepared. When the fatty acid ester content of the sample was quantified by the gas chromatographic analysis method, it was 0.0%, 9.6%, 17.6%, 27.8%, 36.2%, 46.6%, 54.1, respectively. %, 64.7%, 74.7%, 83.1%, 91.5%.

Next, the near infrared spectrum of the sample was measured. The spectrum is measured by putting the sample in a glass cup, covering the lid with a reflector, and using a near infrared spectrum measuring device, SpectraStar 2500XL-R (manufactured by BE TEC Co., Ltd.), in the near infrared spectrum in a wavelength range of 800 nm to 2500 nm. Was measured. The measurement method in SpectraStar 2500XL-R is a transmission measurement method. Further, in the SpectraStar 2500XL-R, a halogen tungsten lamp which is a thermal radiation light source is used as a light source, a dispersion type spectral method using a diffraction grating is used as a spectroscopic method, and an indium gallium arsenide detector is used as a detector.

In the near-infrared spectrum obtained by the measurement of the above sample, baseline fluctuation, noise of the measuring device, peak overlap, and the like occurred. Therefore, the multivariate analysis software The Unscrmller X (manufactured by Camo Software Japan Co., Ltd.) was used to apply the spectrum processing by the second derivative processing to obtain the derivative spectrum excluding the disturbance. As the conditions for the second-order differential processing, the Savitzky-Golay method was used, the differential order was 2, the polynomial order was 2, and the smoothed data score was 21.

A differential equation is used as an explanatory variable, and a fatty acid ester content quantified by a gas chromatographic method is used as an objective variable. PLS regression analysis is performed using the above multivariate analysis software, and a regression equation for estimating a fatty acid ester content from near-infrared spectrum data. Got FIG. 3 shows the results of regression analysis. The coefficient of determination for creating the calibration curve: 0.998, the root mean square (RMSE) of the error: 1.277, the coefficient of determination for the calibration curve test: 0.998, RMSE: 1. 563, which was a sufficient prediction accuracy.

Six types of estimation target samples were prepared and the fatty acid ester content was estimated. The estimation target samples include 3 types of samples containing fatty acid ester (estimation target sample 1, estimation target sample 2 and estimation target sample 3) and 3 types of samples not containing fatty acid ester (estimation target sample 4, estimation target sample 5) And an estimation target sample 6) are included. The near-infrared spectrum of the estimation target sample was measured, the second derivative processing was performed, and the above regression equation was applied to the obtained differential spectrum to estimate the fatty acid ester content of the estimation target sample. For the measurement and spectrum analysis of the near-infrared spectrum, the same device and method as those used for obtaining the above regression equation were used. Table 1 below shows the estimation result of the fatty acid ester content of the estimation target sample. As shown in Table 1, the estimated value of the fatty acid ester content of this example was not so different from the quantitative value by the gas chromatograph method. The RMSE as the evaluation result of the estimation of the fatty acid ester content was 2.46, which was a good estimation accuracy.

As described above, the wavelength range in which the combined sound can be observed is the wavelength range from 2000 nm to 2500 nm. The measurement wavelength region in this example is 800 nm to 2500 nm. Generally, the wavelength region in which the bond sound of the fatty acid ester molecule can be observed is a wavelength region of 2000 nm or more and 2500 nm or less, and thus the measurement wavelength region is set to include the wavelength region of 2000 nm or more and 2500 nm or less as in the present embodiment. By doing so, the fatty acid ester content of the estimation target sample can be easily estimated with high accuracy.
<Example 2>

In this example, the same sample as that used in Example 1 was used, and the near-infrared spectrum was measured under the same conditions as in Example 1 except for the measurement wavelength region.

In this example, the near infrared spectrum of the sample was measured in the near infrared region of 2000 nm to 2500 nm where the bond sound of the fatty acid ester molecule was observed, and the derivative spectrum was obtained by the second derivative treatment as in Example 1. , A differential spectrum was used as an explanatory variable, and a quantitative value of fatty acid ester content was used as an objective variable, and PLS regression analysis was applied to obtain a regression equation. FIG. 4 shows the results of the regression analysis. The coefficient of determination for creating the calibration curve: 0.998, RMSE: 1.287, the coefficient of determination for the calibration curve test: 0.998, RMSE: 1.577, which is a sufficient prediction. It was precision.

Table 2 below shows the results of estimating the fatty acid ester contents of the same 6 types of estimation target samples as in Example 1 using the regression equation in the wavelength region of the near infrared spectrum of 2000 nm to 2500 nm. As shown in Table 2, the estimated value of this example was similar to the quantitative value by the gas chromatographic method. The RMSE as the evaluation result of the estimation of the fatty acid ester content was 1.42, which was a better estimation accuracy than that of Example 1. Further, 2250±10 nm, 2260±10 nm, 2310±10 nm, 2330±10 nm, 2350±10 nm, and 2370±10 nm were revealed as important spectral regions related to the estimation of the fatty acid ester content.

As described above, the measurement wavelength range is limited to a range of 2000 nm or more and 2500 nm or less, which is narrower than the wavelength range of 800 nm or more and 2500 nm or less that is the measurement wavelength range of Example 1, thereby It is possible to prevent a region other than the wavelength region in which the combined sound can be observed from being included in the measurement wavelength region in a large amount, and it is possible to suppress a decrease in estimation accuracy of the fatty acid ester content.
<Example 3>

In this example, the same sample as that used in Example 1 was used, and the near-infrared spectrum was measured under the same conditions as in Example 1 except for the measurement wavelength region.

In this example, the important spectral regions (2250±10 nm, 2260±10 nm, 2310±10 nm, 2330±10 nm, 2350±10 nm, 2370±10 nm) related to the estimation of the fatty acid ester content revealed in Example 2 were obtained. 2), 2268 nm, 2312 nm, 2339 nm, 2351 nm, and 2378 nm, the fatty acid ester content was estimated. The near-infrared spectrum of the sample was measured in the near-infrared region of 2254 nm, 2268 nm, 2312 nm, 2339 nm, 2351 nm, and 2378 nm, and the derivative spectrum was obtained by the second derivative treatment as in Example 1, and then the derivative spectrum was used as an explanatory variable. , PLS regression analysis was applied with the quantitative value of the fatty acid ester content as an objective variable to obtain a regression equation. FIG. 5 shows the results of the regression analysis. The coefficient of determination for creating the calibration curve: 0.998, RMSE: 1.208, the coefficient of determination for the calibration curve test: 0.998, RMSE: 1.468, and sufficient prediction accuracy. Met.

Table 3 shows the results of estimating the fatty acid ester contents of the same 6 types of estimation target samples as in Example 1 using the regression equations in the near infrared region 2254 nm, 2268 nm, 2312 nm, 2339 nm, 2351 nm, and 2378 nm. As shown in Table 3, the estimated value of the present Example is similar to the quantitative value by the gas chromatographic method, and the RMSE as the evaluation result of the estimation of the fatty acid ester content is 1.72. The estimation accuracy was better than that of Example 1.

As described above, by making the measurement wavelength region include at least one of 2250±10 nm, 2260±10 nm, 2310±10 nm, 2330±10 nm, 2350±10 nm and 2370±10 nm, a fatty acid ester can be obtained. It is possible to effectively include a wavelength region in which a molecular bonding sound can be observed, and it is possible to suppress a decrease in estimation accuracy of the fatty acid ester content.
<Reference Example 1>

In Reference Example 1, the same sample as that used in Example 1 was used, and the near-infrared spectrum was measured under the same conditions as in Example 1 except for the measurement wavelength region.

In Reference Example 1, the near-infrared spectrum of the sample is measured in the near-infrared region of 1500 nm to 2000 nm where the first overtone of the fatty acid ester molecule is observed, and a derivative spectrum is obtained by the second derivative treatment as in Example 1. After that, a differential equation was used as an explanatory variable, and a quantitative value of the fatty acid ester content was used as a target variable, and PLS regression analysis was applied to obtain a regression equation. FIG. 6 shows the results of regression analysis. The coefficient of determination for preparing the calibration curve: 0.999, RMSE: 1.039, the coefficient of determination for the calibration curve test: 0.999, RMSE: 1.222.

Table 4 shows the results of estimating the fatty acid ester contents of the same six types of estimation target samples as in Example 1 using the regression equation in the wavelength region of the near infrared spectrum from 1500 nm to 2000 nm. As shown in Table 4, the estimated value of Reference Example 1 greatly deviated from the quantitative value by the gas chromatograph method, and the RMSE as the evaluation result of the estimation of the fatty acid ester content was 79.4. That is, it was revealed that it is difficult to estimate the fatty acid ester content by the regression equation in the wavelength region of 1500 nm to 2000 nm.

〈参考例２〉

<Reference example 2>

In Reference Example 2, the same sample as that used in Example 1 was used, and the near-infrared spectrum was measured under the same conditions as in Example 1 except for the measurement wavelength region.

In Reference Example 2, the near-infrared spectrum of the sample is measured in the near-infrared region of 1000 nm to 1500 nm where the second overtone of the fatty acid ester molecule is observed, and a derivative spectrum is obtained by the second derivative treatment as in Example 1. After that, a differential equation was used as an explanatory variable, and a quantitative value of the fatty acid ester content was used as a target variable, and PLS regression analysis was applied to obtain a regression equation. FIG. 7 shows the results of regression analysis. The coefficient of determination for preparing the calibration curve: 0.997, RMSE: 1.719, the coefficient of determination for the calibration curve test: 0.994, RMSE: 2.599.

Table 5 shows the results of estimating the fatty acid ester content of the same six types of estimation target samples as in Example 1 using the regression equation in the wavelength region of the near infrared spectrum from 1000 nm to 1500 nm. As shown in Table 5, the estimated value of Reference Example 2 largely deviated from the quantitative value by the gas chromatograph method, and the RMSE as the evaluation result of the estimation of the fatty acid ester content was 18.0. That is, it was revealed that it is difficult to estimate the fatty acid ester content by the regression equation in the wavelength region of 1000 nm to 1500 nm.

The present invention is not limited to the above embodiments, and various modifications can be made within the scope of the invention described in the claims, and it goes without saying that they are also included in the scope of the present invention. For example, other fatty acid ester may be used instead of methyl oleate as the fatty acid ester. It should be noted that if a fatty acid ester containing at least one of alkyl oleate, alkyl linoleate and alkyl linolenate is used, it is possible to estimate the fatty acid ester content of the estimation target sample with high accuracy, as in the above-mentioned Examples. confirmed.

By using the present invention, the content of fatty acid ester contained in biodiesel fuel and the like can be estimated in a few minutes, and the measurement time is remarkably shortened as compared with the conventional gas chromatograph analysis method of about 2 hours. .. In addition, near-infrared spectroscopy does not require dilution of a sample or adjustment of analysis conditions, and therefore can perform measurement quickly and easily. By using this method as a daily quality control method when manufacturing, shipping, receiving, and using products, it is possible to handle biodiesel fuel with stable quality.

Claims (8)

A measurement step of measuring the near-infrared spectrum of the sample in a measurement wavelength range including a wavelength range in which the bond sound of the fatty acid ester molecule can be observed,
A quantification step of quantifying the content of the fatty acid ester of the sample,
Data of the near-infrared spectrum measured in the measurement step as an explanatory variable, the data of the content of the fatty acid ester quantified in the quantification step as an objective variable, a regression step to obtain a regression equation by regression analysis,
By measuring the near-infrared spectrum of the estimation target sample, and applying the measurement result of the near-infrared spectrum of the estimation target sample to the regression equation obtained in the regression step, the fatty acid ester content of the estimation target sample An estimation process for estimating
A method for estimating a fatty acid ester content, comprising: The method for estimating the fatty acid ester content according to claim 1,
The method for estimating a fatty acid ester content, wherein the measurement wavelength region includes a wavelength region of 2000 nm or more and 2500 nm or less. The method for estimating the fatty acid ester content according to claim 2, wherein
The method for estimating a fatty acid ester content, wherein the measurement wavelength region is only within a wavelength region of 2000 nm or more and 2500 nm or less. The method for estimating the fatty acid ester content according to claim 2 or 3,
The method for estimating a fatty acid ester content, wherein the measurement wavelength region includes at least one of 2250±10 nm, 2260±10 nm, 2310±10 nm, 2330±10 nm, 2350±10 nm, and 2370±10 nm. The method for estimating the fatty acid ester content according to any one of claims 1 to 4,
The method for estimating a fatty acid ester content, characterized in that the near-infrared spectrum of the sample and the sample to be estimated is measured using either a transmission measurement method or a diffuse reflection measurement method. The method for estimating the fatty acid ester content according to any one of claims 1 to 5,
In the regression step, a method of estimating the fatty acid ester content, which comprises applying a differentiation process to the data of the near-infrared spectrum measured in the measuring step and then using the differentiation process as an explanatory variable. The method for estimating a fatty acid ester content according to any one of claims 1 to 6,
The method of estimating fatty acid ester content, wherein the regression analysis is a partial least squares regression analysis. The method for estimating a fatty acid ester content according to any one of claims 1 to 7,
The method for estimating fatty acid ester content, wherein the fatty acid ester contains at least one of alkyl oleate, alkyl linoleate and alkyl linolenate.

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