KR20220058798A - A method for quality evaluation method of wheat using near-infrared spectroscopy - Google Patents

Abstract

The present invention relates to a quality evaluation method for wheat. The quality evaluation method for wheat includes: a step of measuring reflection spectrum on a wheat sample by using a near-infrared (NIR) spectroscope; and a step of determining an amylose content, an extraction rate, and a falling number (F/N) of the wheat sample by putting a spectrum value deducted from the measured spectrum into an amylose content equation, an extraction rate equation, and an F/N equation. According to the present invention, the amylose content equation can be used for searching a high amylose wheat resource, and the extraction rate equation can confirm a rate of the wheat except testa. The F/N equation indicates a mature sound seed and viviparous germination or a seed in which amylolysis proceeds and thus, can be used for sorting the seed. Accordingly, the quality evaluation method for wheat can rapidly and simply evaluate the quality of the wheat by rapidly and simply evaluating various ingredient items at one time without preprocessing or trituration of raw wheat seed.

Description

Method for evaluating wheat quality using near-infrared spectroscopy {A method for quality evaluation method of wheat using near-infrared spectroscopy}

The present invention comprises the steps of measuring a reflection spectrum for a wheat sample using a near-infrared (NIR) spectrometer; By substituting the spectral values derived from the measured spectrum into the amylose content, milling rate and F / N (Falling Number) calibration equation of wheat, determining the amylose content, milling rate and F / N of the wheat sample It is about how to evaluate quality.

In the world's major wheat producing countries, such as the United States and Canada, grades are stored and distributed according to the quality of wheat.

In order to quickly measure the quality of wheat directly at the site of a wheat purchaser, we have developed, applied, and measured a calibration equation for wheat quality-related factors such as protein and moisture using a near-infrared spectrometer (NIR).

Accordingly, there is an increasing demand to search for high amylose resources for improving various processing usability of domestic wheat by further improving and applying the component measurement items of such NIR technology and to utilize them as processing materials.

Accordingly, the present inventors made intensive research efforts to find a method for quickly and simply evaluating wheat quality. As a result, the reflection spectrum of wheat raw wheat was measured using a near-infrared spectrometer, and the amylose content, milling rate and F/N (Falling Number) of wheat were measured from this. It was confirmed that it can be determined at the same time, and the present invention was completed.

An object of the present invention is to measure a reflection spectrum for a wheat sample using a near-infrared (NIR) spectrometer; By substituting the spectral value derived from the measured spectrum into the amylose content, milling rate and F/N (Falling Number) calibration equation of wheat, determining the amylose content, milling rate and F/N of the wheat sample It provides a way to evaluate quality.

Hereinafter, the present invention will be described in more detail. Meanwhile, each description and embodiment disclosed in the present invention may be applied to each other description and embodiment. That is, all combinations of the various elements disclosed herein fall within the scope of the present invention. In addition, it cannot be said that the scope of the present invention is limited by the specific descriptions described below. In addition, those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Also, such equivalents are intended to be encompassed by the present invention.

As an aspect for achieving the above object, the present invention comprises the steps of measuring a reflection spectrum for a wheat sample using a near-infrared (NIR) spectrometer; By substituting the spectral value derived from the measured spectrum into the amylose content, milling rate and F/N (Falling Number) calibration equation of wheat, determining the amylose content, milling rate and F/N of the wheat sample It provides a way to evaluate quality.

The method for evaluating the quality of wheat according to the present invention is characterized in that it is a non-destructive method capable of measuring the content of ingredients from a raw wheat state rather than a sample processed into powder. Therefore, if the near-infrared spectrometer is used, the above three analyzes can be performed on-site immediately after harvest, so it can be classified according to quality and/or processing purpose.

In order to use wheat for various processing purposes such as bread, confectionery, and noodles, the quality must be analyzed. In the case of the existing wheat quality analysis method, the quality-related factors of wheat such as amylose content, milling rate and F/N are analyzed. For this purpose, it has been made through separate experiments like the general analysis method. However, in the case of such an analysis method, it is difficult to analyze wheat quality in a timely manner in the field because it takes a lot of effort and time and requires a complicated sample processing process.

Accordingly, the present inventors have tried to develop a wheat quality analysis method that can be analyzed in a timely manner in the field in order to solve this disadvantage, and using the near-infrared spectroscopy of the present invention, it is possible to analyze the raw wheat as it is without grinding it. In addition, it was confirmed that various factors affecting wheat quality, such as amylose content, milling rate, and F/N, could be analyzed simultaneously with just one near-infrared spectroscopy.

Specifically, the evaluation method of the present invention optimizes a calibration equation, which is a quality measurement baseline, by using 300 sample samples and grouping them into 4 groups based on 4 points and performing statistical processing using the first differential method.

Therefore, the evaluation method of the present invention does not require a pre-treatment process, so it does not require additional experimental equipment such as reagents and glassware, and it is possible to quickly and simply evaluate the amylose, milling rate and F/N of wheat in less than 1 minute in analysis time, and a single measurement It is characterized in that it is a method capable of simultaneously determining amylose content, milling rate and F/N.

In the present invention, "amylose content of wheat" is a characteristic of wheat defined as a percentage of the weight occupied by amylose with respect to the total weight of a wheat sample. The amylose content analysis of wheat can be used to search for high amylose wheat resources.

In the present invention, "milling rate of wheat" may be defined as the ratio of wheat flour that can be prepared from wheat except for the seed coat. The higher the milling rate, the easier it can be processed into flour.

In the present invention, "Wheat F/N (Falling Number)" may be defined as an indicator indicating mature healthy seeds, germination or starch decomposition. The F/N analysis may be used when sorting or selecting seeds.

The wheat amylose content calibration formula used to determine the amylose content of wheat from the near-infrared spectral value according to the present invention is a value derived by applying the first differential to the NIR spectrum of a standard wheat sample, and a standard wheat sample by a wet analysis method It may be derived by optimizing it compared with the measured amylose content, and specifically, it may be derived by using 300 sample samples, grouping 4 around 4 points, and statistical processing applying the first differentiation. The amylose analysis method for measuring the amylose content of the standard wheat sample is not limited to the methods listed above, and amylose analysis methods known in the art may be used without limitation.

The calibration formula for the amylose content of wheat may be y = 1.0025x - 0.0574.

Here, when x is the spectral value of the wheat sample, the measured value y (%) of the amylose content of the wheat sample may be determined, and the utilized wavelength range may be 900 to 1,050.

As a result of statistical processing by substituting 359 wheat resources and wet analysis values (average amylose content of 24.93%) in the amylose calibration formula, the data correlation coefficient of the calibration formula is 0.9215, the NIR predicted minimum value is 17.39%, and the maximum value is 32.50%, The standard error was ±0.7%.

The milling rate calibration equation used to determine the milling rate of wheat from the near-infrared spectral value according to the present invention is a value derived by applying the first differential to the NIR spectrum of a standard wheat sample, and a standard wheat sample is measured by a wet milling rate analysis method It may be derived by optimizing it compared with one milling rate, and specifically, it may be derived by using 300 sample samples, grouping four around four points, and performing statistical processing of the first differential application. As the reference value, a milling rate analysis method for measuring a milling rate for a standard wheat sample is not limited to the methods listed above, and milling rate analysis methods known in the art may be used without limitation.

The calibration formula for the milling rate of wheat may be y' = 0.9990x' + 0.0458.

Here, when x is the spectral value of the wheat sample, the milling rate y' (%) of the wheat sample may be determined, and the utilized wavelength range may be 850 to 1,000.

As a result of statistical processing by substituting 491 wheat resources and wet analysis values (average milling rate 56.42%) in the calibration formula for the milling rate, the data correlation coefficient of the calibration formula is 0.9682, the NIR measurement prediction minimum value is 23.92%, the maximum value is 88.92%, The standard error was ±1.9%.

The F/N calibration equation of wheat used to determine the F/N of wheat from the near-infrared spectrum value according to the present invention is a value derived by applying the first differential to the NIR spectrum of a standard wheat sample, and the standard wheat sample is wet F/N It may be derived by optimizing it by comparing it with F/N measured by the N (Falling Number) analysis method. Specifically, using 300 sample samples, 4 groups are grouped around 4 points, and statistical processing is applied to the first differentiation. may have been derived. The F/N analysis method for measuring the F/N for the standard wheat sample is not limited to the methods listed above, and F/N analysis methods known in the art may be used without limitation.

The F/N content calibration formula of wheat may be y'' = 0.9942x'' + 1.7255.

Here, when x is the spectral value of the wheat sample, the F/N value y'' (sec) of the wheat sample may be determined, and the utilized wavelength range may be 900 to 1,050.

As a result of statistical processing by substituting 479 wheat resources and wet analysis values (F/N value average of 266.1 sec) in the F/N calibration formula, the data correlation coefficient of the calibration formula is 0.9658, the NIR measurement prediction minimum value is 0.0 sec, and the maximum value was 565.1 sec, and the standard error was ±18.3%.

In the present invention, wheat, preferably raw wheat that has not been pre-treated or ground, is analyzed by near-infrared spectroscopy to determine the amylose content, milling rate, and F/N at the same time, thereby evaluating the quality of wheat.

In one embodiment of the present invention, the amylose content, milling rate, and F/N obtained by substituting the spectrum for wheat raw wheat measured by NIR spectroscopy into the optimized calibration equation were compared with wet analysis values for the same sample, and the present invention It was confirmed that the values measured using NIR from wheat raw wheat according to

The present invention is a method for evaluating the quality of wheat by measuring the reflection spectrum of wheat raw wheat using a near-infrared spectrometer and simultaneously determining the amylose content, milling rate, and F/N (Falling Number) therefrom. The milling rate calibration formula can check the ratio of flour excluding the seed coat, and the F/N calibration formula represents mature healthy seeds and seeds that have undergone germination or starch decomposition, so it can be used to classify seeds. It is possible to quickly and simply evaluate the quality of wheat for several ingredients in one measurement without pre-treatment or grinding.

1 is a view showing wheat quality analysis by near-infrared spectroscopy. (A) Near-infrared spectroscopy, (B) Calibration of wheat quality factor by near-infrared spectroscopy.
2 is a diagram showing (A) amylose content 20.59 to 31.99%, (B) wheat flour yield 33.27 to 81.88%, and (C) F/N (Falling Number) 69.50 to 538.50 sec collected from wheat germplasm.
3 is a diagram showing the correction of wheat quality factor by near-infrared spectroscopy. (A) amylose, (B) wheat yield, and (C) F/N.

Hereinafter, the present invention will be described in more detail through examples. These Examples are for explaining the present invention in more detail, and the scope of the present invention is not limited to these Examples.

Example 1: Conventional wheat quality analysis method

For comparison with the results of non-destructive quality analysis using near-infrared spectroscopy according to the present invention, amylose content, milling rate, and F/N were measured by a conventional wet method. The general analysis methods used a powder sample obtained by pulverizing wheat.

1.1. Amylose content analysis

The content of amylose in wheat was measured by a colorimetric method (BO Juliano BO 1971. A simplified assay for milled rice amylose. Cereal Sci. Today, 16 (1971), p. 340). Specifically, whole wheat was made of 100 mesh flour, dried at 105° C. for 2-3 hours (or one day at 50° C.), and stored in a desiccator. 100 mg of the prepared 100 mesh flour was weighed and placed in a 100 ml mass flask. 1 ml of 95% ethanol and 9 ml of NaOH were put in a flask, left for about 20 minutes, and then placed in a 95-100° C. water bath and gelatinized for 5-10 minutes. After cooling the gelatinized sample, it was filled to 100 ml with distilled water and shaken well. 5 ml of the mixture was taken with a pipette, transferred to a 100 ml mass flask containing 50 ml of distilled water, 1 ml of 1N CH ₃ COOH and 2 ml of I2-KI solution were added, filled with distilled water to make 100 ml, and shaken well and left for at least 30 minutes. .

40 mg of pure amylose (Waco) (dried) was weighed into a 100 ml mass flask. 1 ml of 95% ethanol and 9 ml of 1N NaOH were added to the weighed pure amylose, heated in a water bath at 95-100° C. for 5-10 minutes, gelatinized, and then cooled to 100 ml with distilled water. Pipet 0.5 ml, 1 ml, 1.5 ml, 2 ml, 2.5 ml, 3 ml, 3.5 ml, 4 ml, 4.5 ml, and 5 ml of the amylose solution into a 100 ml beaker containing 50 ml of distilled water. After transfer, the pH was adjusted to 10.5 with 0.05N-HCl. The pH-adjusted amylose solution was transferred to a 100 ml mass flask, then 2 ml of I2-KI solution and 1 ml of 1N CH ₃ COOH were added, filled with distilled water to make 100 ml, and shaken well and left for about 20 minutes. The absorbance was measured at a colorimetric wavelength of 620 nm, and the absorbance was again obtained from the conversion table to obtain a linear regression equation between the amylose content and the absorbance, and a standard conversion table was prepared. The contents of each amylose in 0.5 to 5 ml of amylose solution measured accordingly are shown in Table 1 below.

Collection sample volume (ml) 0.5 One 1.5 2 2.5 3 3.5 4 4.5 5 amylose (ppm) 2 4 6 8 10 12 14 16 18 20 Converted amylose of wheat amylose (%) 4 8 12 16 20 24 28 32 36 40 megazyme 70% high amylose
conversion table used 2.8 5.6 8.4 11.2 14 16.8 19.6 22.4 25.2 28

However, in this case, the moisture content of wheat flour and pure amylose is the same.

※ Blank uses all reagents except for the sample added.

※ After standard curve preparation, formula: Y= 0.0763X + 0.0046 (R2 = 0.9987)

1.2. Milling rate analysis

Grinding is the production of flour by separating only the pure endosperm from the wheat seeds except for the bran and pear parts. For laboratory-level milling, a Buhler laboratory mill (Buhler Bros., Inc., Switzerland) is used, and the mill should maintain a temperature of 23°C and a humidity of 70%. Milling rate was specifically determined according to the previous method (American Association of Cereal Chemists. 2000. Approved Methods 26-10, 26-20. 10th ed. The Association: St. Paul, MN.). Foreign matter was removed from the pure wheat seeds and tempering was performed. The tempering is an operation to make the endosperm part easily separated from the bran. Generally, 15~16% for hard wheat and 14% for soft wheat, so that moisture can be evenly distributed at room temperature for about 18 hours. Thereafter, a sieve suitable for mill seed hardness was installed, and the gap between break rolls was adjusted. In general, when milling, the amount of the first fraction of the brake roll was maintained at 4 to 6% for hard wheat and 9 to 13% for soft wheat. The seed feed rate was 2 kg per hour for soft wheat and 3 kg per hour for hard wheat. After milling, the weights of wheat flour, bran and short flour received from 3 batches of each roll were recorded. The milling rate was calculated according to the following formula.

in the above formula B1, B2, and B3 are the weight (g) of flour received from the brake roll, and R1, R2, and R3 are the weight (g) of flour received from the reduction roll.

1.3. F/N analysis

F/N is an instrument for measuring α-amylase activity of cereals, and it measures the time it takes for a metal ball to pass through a gelatinized grain meal and fall. Although it shows a high value, in the case of seeds with water germination, starch is decomposed by α-amylase and the level is lowered. F/N was analyzed using Falling Number 1900 (Perten Instruments, Sweden). Specifically, the coarser the sample particles, the more errors occur during measurement, so the sample was sieved through a sieve of 0.8 mm or less, and then a 7.0 ± 0.05 g sample was measured and transferred to a test tube for measurement. 25.0 ± 0.2 ml of distilled water was put into the test tube. Close the stopper and shake to spread the sample evenly. When the temperature of the instrument rose to 98° C. or higher, a test tube was attached to the instrument, and the sample was gelatinized while stirring for 5 seconds. After 5 seconds, the stroke with the weight went up and down twice per second for 60 seconds, and the weight dropped by gravity, and the time it took to fall was measured. Based on the moisture content of 14%, F/N was calculated according to the following formula.

Example 2: Method for evaluating wheat quality using near-infrared spectroscopy

After selecting the wheat raw wheat sample, 50 healthy grains (or 3 g) were taken and put in a measuring bottle. The measuring bottle was placed on the light measuring position of a near-infrared (NIR) spectrometer, and a spectrum was obtained by irradiating near-infrared rays and receiving the reflected light ( FIG. 1 ). The intensity of the reflected light corresponds to a value obtained by subtracting the intensity of the transmitted light from the intensity of the irradiated light. The measured spectrum was repeated three times, and the above process was repeated for each sample after replacing the sample. In order to establish a calibration formula for amylose content, milling rate, and F/N by quantifying the content based on the peak of the graph formed according to the spectrum for all samples, statistical analysis was performed using the first differential method, etc. and optimized. The data obtained from the NIR spectrum was optimized in the direction of minimizing the error range by examining the accuracy of content measurement for each component. The calibration formula for the content of each component thus obtained is as follows:

Amylose calibration formula: y = 1.0025x - 0.0574

(Used wavelength range 900~1,050)

Milling rate calibration formula: y' = 0.9990x' + 0.0458

(Used wavelength range 850~1,000)

F/N : y'' = 0.9942x'' + 1.7255

(Used wavelength range 900~1,050)

In each of the above formulas, x to x'' are spectral values for amylose content, milling rate, and F/N, respectively. After measuring the spectrum for individual samples, quantifying the spectrum in the wavelength range using the least squares method and applying it to the formula, the predicted value (NIR measurement) content) of y to y'' can be digitized and obtained as a content. The calibration of the wheat quality factor by the NIR is shown in FIG. 3 .

The amylose content, milling rate and F/N (Falling Number) obtained by substituting the spectrum for raw wheat measured by NIR spectroscopy into the optimized calibration equation, and general analysis values for the same sample (FIG. 2) are shown in Table 1 below. compared. It was confirmed that the value measured using NIR from wheat raw wheat according to the present invention can be measured at a level of error within ±0.5 (% or ml) for all components compared to the existing general analysis value.

Factor Number Mean SD Est.Min Est. Max SEC RSQ SECV Amylose
(%) 359 24.93 2.52 17.37 32.50 0.7064 0.9215 0.7470 FlourYield
(%) 491 56.42 10.84 29.92 88.92 1.9314 0.9682 2.0005 Falling Number
(sec) 479 266.07 99.0 0.00 565.08 18.30 0.9658 19.7290

Number: number of samples, SD: standard deviation, Est. Min: predicted minimum, Est. Max: predicted maximum value, SEC: standard calibration error, RSQ: data correlation coefficient, SECV: cross-validation error in the table.

From the above description, those skilled in the art to which the present invention pertains will understand that the present invention may be embodied in other specific forms without changing the technical spirit or essential characteristics thereof. In this regard, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. The scope of the present invention should be construed as being included in the scope of the present invention, rather than the above detailed description, all changes or modifications derived from the meaning and scope of the claims to be described later and their equivalents.

Claims (4)

Measuring a reflection spectrum for a domestic wheat sample using a near-infrared (NIR) spectrometer; and
A spectral value derived from the measured spectrum,
a) Wheat amylose content calibration formula derived by optimizing the value derived by applying the first powder to the NIR spectrum of the standard wheat sample with the amylose content measured by the wet analysis method for the standard wheat sample;
b) a milling rate calibration formula derived by optimizing a value derived by applying the first differential to the NIR spectrum of a standard wheat sample with a milling ratio measured by a wet milling rate analysis method for a standard wheat sample, and
c) F/N derived by comparing the value derived by applying the first differential to the NIR spectrum of the standard wheat sample with the F/N measured by the wet F/N (Falling Number) analysis method of the standard wheat sample N calibration,
By substituting it, the method for evaluating the quality of domestic wheat, comprising the step of determining the amylose content, milling rate and F / N (Falling Number) of the wheat sample.
The method according to claim 1, wherein the calibration formula for the amylose content of wheat is y = 1.0025x - 0.0574, and when x is the spectral value of the wheat sample, the measured value y (%) of the amylose content of the wheat sample is determined.
The method according to claim 1, wherein the milling rate calibration equation of the wheat is y' = 0.9990x' + 0.0458, and when x' is a spectral value of the wheat sample, the measured milling rate y' (%) of the wheat sample is determined.
The method according to claim 1, wherein the F/N calibration equation of the optimized wheat sample is y'' = 0.9942x'' + 1.7255, and when x'' is the spectral value of the wheat sample, the F/N measurement value of the wheat sample y'' and (sec) is determined.

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