CN106970041B - Near-infrared determination method for insoluble glutelin macro-polymer content of wheat flour - Google Patents
Near-infrared determination method for insoluble glutelin macro-polymer content of wheat flour Download PDFInfo
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Abstract
The invention belongs to the technical field of agricultural product component detection, and particularly relates to a near-infrared determination method for insoluble gluten macro-polymer content of wheat flour and application thereof. The invention is characterized in that: extracting the wheat flour by using a buffer solution to obtain a liquid sample to be detected containing insoluble glutelin macro-polymers. And (3) scanning the sample to be detected by a reflection type near infrared spectrometer while measuring the real chemical value, and collecting an original spectrogram. And establishing a near-infrared prediction calibration model of the content of the flour insoluble gluten macro-polymers by using chemometric software and a partial least square method. According to model parameters and application verification, the prediction model has the outstanding characteristics of accuracy, rapidness and low cost.
Description
Technical Field
The application relates to the technical field of agricultural product component detection, in particular to a near-infrared determination method for insoluble gluten macro-polymer content of wheat flour.
Background
Near-infrared spectroscopy (NIRS) is based on the non-resonance property of molecular vibration, so that molecular vibration is generated when the molecular vibration transits from a ground state to a high energy level, the wavelength range is usually 800-2500 nm, the frequency doubling and frequency combining absorption of vibration of hydrogen-containing groups C-H, O-H, N-H, S-H, P-H and the like can be recorded, and the correlation between an absorption spectrum and the content of substances is established. Is very suitable for analyzing the water content of the detected object and the content of the hydrocarbon organic substances such as protein, carbohydrate, lipid and the like.
Gluten in wheat grain and flour is usually present in the form of polymers, wherein the fraction with higher degree of polymerization that is not easily extracted in sodium dodecyl sulfate phosphate buffer is called insoluble gluten macro-polymer (UPP). UPP represents only about 50% of the total gluten content of wheat and about 5% of the total storage protein content, but has a very significant positive correlation with gluten strength, the UPP content being mainly influenced by the genotype, which has a decisive effect on gluten quality and food quality (Zhang P, He Z H, Xia X C, et al. Effect of permanent SDS-untracable polymeric protein (% UPP) on end-use quality in Chinese branched cellulose Chemistry,2008,85: 696. 700; Zhu J, Khang K. Effect of growth environment on polymers and branched cellulose. Cereal chem,2001,78: 125. 130; Gupta R B, Khang K, Rice F. biological and biological samples of protein, 18. yield of wheat gluten and wheat gluten, 23. J. Therefore, how to rapidly and accurately quantitatively analyze UPP becomes an important content for the selection of the breeding generation of wheat varieties.
The analysis method of the gluten macro-aggregate commonly used at present comprises the following steps: effect of double Urea colorimetric method (Liu., Wenyang, where Tiger, et al., Glu-1 and Glu-3 allelic variations on insoluble gluten content, Proc. Pal.Miq., 2004,30:1086-, 2008,85: 696-; GuptaR B, Khan K, MacRitchie F. biochemical basis of flow properties induced floors. I. effects of variation in the quality and size distribution of polymeric protein. J. Central Sci,1993,18: 23-41).
Although the biuret colorimetric method and the propanol separation method are simple, the actual measurement is not the content of the large polymer of the gluten but the total amount of the gluten polymer, and the biuret colorimetric method also has the problems of poor repeatability among parallel samples, time waste and labor waste. The multilayer gel electrophoresis optical density scanning method has complex measuring process and technology, strict requirements on dyeing and decoloring of gel, higher cost, time and labor waste. Gel chromatography is the most accurate method at present, but the method has expensive equipment and consumables, needs special technicians, is mostly used for quantitative research with higher requirements, and has less application in breeding auxiliary selection. At present, no report is found on the research of measuring the content of the gluten macro-polymers by using the near infrared spectrum technology.
Disclosure of Invention
Aiming at the problems, the invention establishes a near infrared spectrum measuring method (model) capable of measuring the insoluble glutelin macro-polymer content of the wheat flour, and the method has the advantages of simple sample preparation, low cost and high measuring precision. The invention is realized by the following steps:
a near-infrared determination method for insoluble gluten macro-polymer content of wheat flour comprises the following specific steps:
1) preparation of insoluble gluten macro-polymer samples: preparing an insoluble glutelin macro-polymer liquid sample by using an SDS-phosphate buffer solution extracting solution for later use;
the specific extraction method comprises weighing 20mg flour sample in 2.0mL centrifuge tube, adding 1.6mL SDS-phosphate buffer solution extract, shaking for 10min, centrifuging 17000g for 5min, and discarding supernatant; adding 1.6mL of SDS-phosphate buffer solution extracting solution into the precipitate again, extracting for 20s by using an ultrasonic cell disruptor, and then centrifuging for 5min by 17000g to obtain supernate, namely an insoluble glutelin macro-polymer liquid sample;
2) respectively taking 200uL of the insoluble glutelin macro-polymer liquid sample obtained in the step 1) by using a 0.45-micron nylon membrane (water system) needle filter for chromatographic analysis to obtain a chemical measurement result;
3) respectively taking 1.0-1.2 mL of the insoluble glutelin macro-polymer liquid sample to be detected obtained in the step 1), and collecting spectral data; the spectrum scanning interval is 950-1650nm, the scanning times are 10 times, the temperature is room temperature, and the resolution is 5 nm;
4) calculating and analyzing the chemical measurement result obtained in the step 2) and the spectral data obtained in the step 3) by adopting a partial least square method, and establishing a prediction model; the coefficient of determination of the model is R20.89, the standard deviation for the model is RMSECV 36.40;
5) establishing a predicted calibration model by adopting Unscamblebler chemometrics software and combining a partial least square method;
eliminating the influence of spectrum baseline drift on the establishment of a predicted calibration model in the measurement process by adopting a spectrum preprocessing mode of first derivative plus S-G smoothing, and determining a coefficient R of the established model according to the standard deviation of interactive verification2To evaluate the predicted primary parameters of the calibration model effect;
6) preparing an insoluble glutelin macro-polymer liquid sample of the sample to be detected by adopting the method same as the step 1), utilizing the predicted calibration model obtained in the step 5), and carrying out near infrared spectrum analysis on the sample to be detected according to the method in the step 3), namely obtaining the content of the insoluble glutelin macro-polymer of the sample to be detected.
Further, in the near-infrared determination method of the content of the insoluble gluten polymers of the wheat flour, the SDS-phosphate buffer solution extracting solution in the step 1) is 0.5M phosphate buffer solution containing SDS with the mass volume ratio of 0.5%, and the pH value is 6.90.
Further, in the near-infrared determination method of the content of insoluble gluten polymers in wheat flour, the extraction parameters of the ultrasonic cell disruptor in the step 1) are
The probe outputs 10W of work.
Further, in the near-infrared determination method for the content of the insoluble gluten polymers in the wheat flour, the chromatographic analysis in the step 2) is that a high performance liquid chromatograph and a Biosep S4000 gel chromatographic column are adopted, a mobile phase is a 50% acetonitrile water solution (v/v) containing trifluoroacetic acid with the volume ratio of 0.05%, and the flow rate is 0.5 mL/min.
Further, in the near-infrared determination method for the content of the insoluble gluten polymers of the wheat flour, in the step 3), when spectrum data are collected, determination equipment is a Perten DA7200 diode array near-infrared spectrometer, sample loading hardware is a liquid quartz sample cell, and the thickness is 1 mm.
Compared with the existing measurement method, the method for determining the flour insoluble gluten macro-aggregate by using the prediction model provided by the application has the outstanding characteristics of accuracy, rapidness and low cost, and is easy to popularize and apply.
Drawings
FIG. 1 is a graph of correlation analysis of chemical values and spectral predicted values in a near infrared prediction calibration model of insoluble gluten macro-polymers.
FIG. 2 is a near infrared spectrum of a liquid sample (extract) to be tested of insoluble gluten macro-polymers.
Detailed Description
The following examples describe the technical solutions of the present invention in detail, which are for illustrative purposes and are not intended to limit the scope of the present invention.
Material source/configuration method/equipment and operating parameters referred to in the examples:
1. the near-infrared prediction model and the flour sample source used by the model are as follows: the applicant collects 120 parts of wheat varieties (lines) in Jiangsu, Anhui, Shandong, Henan, Shaanxi, Sichuan provinces and the like, and plants the wheat varieties in the test base of agricultural academy of sciences in Jiangsu province in 2014 plus 2015.
The field test adopts random block design, 3 rows of blocks, 1.5m of row length, 2 times of repetition, and about 225kg of nitrogen application amount in the whole growth period-1And harvesting a grain sample after maturation. After mixing the duplicate seed samples in equal amounts, the powder was milled using a brabender quadrumat Junior Laboratory according to standard procedures, yielding approximately 60% powder.
These samples were rich in variations in protein content and insoluble gluten macro-polymers content (see table 1), and 100 of these samples were randomly selected for modeling (example 1) and 20 for model validation (example 2) in the following examples.
TABLE 1 basic statistical analysis of gel chromatography chemical values and spectral predictions for a modeled sample set
| Parameter(s) | Mean value of | Maximum value | Minimum value |
| Protein content (%, dry basis) | 11.25 | 15.03 | 8.54 |
| Insoluble gluten macro-polymer content chemical value (AU/mg) | 1108.37 | 1805.57 | 854.55 |
2. In the following examples, the near infrared spectrum collection or measurement was performed by a PertenDA7200 diode array near infrared spectrometer (Sweden Boston instruments Co.), and the hardware for the measurement was a liquid quartz sample cell with a thickness of 1 mm.
3. Examples chemical value measurement in the following examples the main apparatus was a Dionex UlltiMate 3000 high performance liquid chromatograph, and the column was a Biosep S4000 gel column. The necessary parameters for the measurement are: the mobile phase was 50% acetonitrile in water (v/v) containing 0.05% (v/v) trifluoroacetic acid at a flow rate of 0.5 mL/min. The chemical value units are converted to AU/mg and represent the Absorbance (AU) of the large gluten polymers per mg of flour.
4. SDS-phosphate buffer extract: 0.5M phosphate buffer, pH6.90, containing 0.5% SDS (w/v, sodium dodecyl sulfate).
Example 1 establishment of near-infrared model for measuring insoluble glutelin macro-polymer content
1. Preparing insoluble glutelin macro-polymer samples to be tested: randomly selecting 100 parts of flour samples, accurately weighing 20mg of flour samples in each part into a 2.0mL centrifuge tube, adding 1.6mL of SDS-phosphate buffer solution extracting solution, and oscillating at room temperature
Centrifuging for 5min, and discarding the supernatant; adding 1.6mL of SDS-phosphate buffer solution into the precipitate again, and using an ultrasonic cell disruptor (
Probe, 10W) for 20s, then centrifuging for 5min at 17000g, and obtaining supernate which is the insoluble glutelin macro-polymer liquid sample to be detected.
2. Chromatographic assay determination of chemical values: and (3) performing chromatographic analysis on 200uL of the liquid sample to be tested obtained in the step (1) by using a 0.45-micron nylon membrane (water system) needle filter, wherein the variation range of the chemical value is wide and is 854.55 AU/mg-1805.57 AU/mg. (see Gupta R B, Khan K, MacRitchie F. biological basis of flowing properties in branched intermediates I. effects of variation in the quality and distribution of polymeric protein J Central Sci,1993,18: 23-41; Larroque O R, Bekes F. Rapid size-exclusion chromatography analysis of molecular size distribution for flowing end properties Central Chem,2000,77:451 453.) the results of the chemical assays for 100 samples of this example are shown in Table 2.
3. Modeling and spectrum collection: and (3) directly and respectively taking 1.0-1.2 mL of insoluble glutelin macro-polymer liquid sample to be detected while measuring the chemical value in the step (2), and collecting the spectral data of the sample by using a Perten DA7200 liquid quartz sample cell. The spectrum scanning interval 950-1650nm, the scanning times 10 times, the temperature room temperature and the resolution 5 nm. The near infrared spectrum data obtained from 100 parts of the insoluble gluten macro-polymer liquid sample (extract) to be tested are shown in fig. 2.
4. Establishing a near-infrared determination model of insoluble gluten macro-polymers: modeling was performed by computational analysis of step 2 chemical values (table 2) and step 3 spectral data.
The modeling software used in this example was The Unscrambler X (v10.3, CAMO), The spectral data are shown in FIG. 2, The modeling method used was The Partial Least Squares (PLS) method, and The modeling wavelength band was 950-.
When the PLS is used for operation, principal component decomposition is carried out on the spectral information X and the concentration information Y matrix at the same time, and regression is carried out by adopting a principal factor, wherein the model comprises the spectral information and the concentration information of the sample related index; the PLS comprises the following specific steps:
firstly, decomposing the X and Y matrixes, wherein the model is as follows:
Y＝UQT+EY(1)
X＝TPT+EX(2)
in the formulas (1) and (2), T and P are respectively the score and the load matrix of the X matrix, U and Q are respectively the score load matrix of Y, EXAnd EYResidual matrixes left when the PLS model is used for fitting X and Y are respectively used;
then, linear regression was performed on T and U:
U＝TB (3)
B＝(TTT)-1TTY (4)
in prediction, firstly, an unknown sample matrix X is obtained according to a load matrix PIs unknownScoring matrix TIs unknownThen, a predicted concentration value is obtained from equation (5):
Yis unknown＝TIs unknownBQ (5)
5. And obtaining a corresponding prediction model, and reversely predicting the spectral data by using the prediction model to obtain a predicted value (Table 2).
TABLE 2100 chromatographic chemical values and model predictive values (AU/mg) of flour samples for modeling
The coefficient of certainty for this model is R2 ═ 0.89, and the cross validation standard deviation for the model is RMSECV ═ 36.40, which is only 3.28% of the mean of the modeled samples.
As can be seen from Table 2, this model accurately measures the content of insoluble gluten macro-aggregates in SDS phosphate buffered extract. The main absorption peak of the sample to be tested is located in the range of 1400-1600 nm (as shown in figure 2), and mainly comprises N-H first frequency multiplication, C-H combined frequency and O-H first frequency multiplication absorption. Meanwhile, as can be seen from fig. 2, absorption peaks of each component in the near-infrared spectral region overlap each other, so that an Unscrambler chemometrics software is used in combination with a partial least squares method to establish a predicted calibration model.
Before modeling, a spectrum preprocessing mode of first derivative + S-G smoothing (the number of smoothing points is 7) is adopted to eliminate the influence of spectrum baseline drift on modeling in the measurement process. Using Standard Error of Cross Validation (SECV) and coefficient of determination (R) of the built model2) Is the main parameter for evaluating the modeling effect.
Example 2 application of near-infrared model for determining insoluble gluten macro-polymer content
And (3) selecting 20 samples which do not participate in the modeling of the example 1, and obtaining the insoluble glutelin macro-polymer liquid sample to be tested by adopting the same sample preparation method as the step 1 of the example 1.
The same DA7200 near-infrared analyzer and liquid quartz sample cell in example 1 were used, the insoluble glutelin macro-aggregate content prediction calibration model (absorbance of substance in the range of 950-.
Chemical values of 20 samples were measured using the same chromatographic conditions as in step 2 of example 1, and the results are shown in Table 3.
The results of the near infrared prediction calibration model were compared with the chemical values and are also shown in table 3.
TABLE 320 chromatographic chemical values and model test values (AU/mg) of flour samples for validation of models
Note: the prediction standard deviation is 43.66AU/mg, and the prediction correlation coefficient is 0.93.
As can be seen from Table 3, the insoluble gluten macro-polymer content determined using the established near-infrared detection model
The detection range is wide, the prediction correlation coefficient reaches 0.93, the prediction standard deviation is 43.66AU/mg, and the model has a good application prospect in the determination of flour insoluble gluten.
Claims (3)
1. A near-infrared determination method for insoluble gluten macro-polymer content of wheat flour is characterized by comprising the following specific steps:
1) preparation of insoluble gluten macro-polymer samples:
weighing 20mg of flour sample, adding 1.6mL of SDS-phosphate buffer solution extract, shaking for 10min, centrifuging for 5min at 17000g, and removing supernatant; adding 1.6mL of SDS-phosphate buffer solution extracting solution into the precipitate again, extracting for 20s by using an ultrasonic cell disruptor, and then centrifuging for 5min by 17000g to obtain supernate, namely an insoluble glutelin macro-polymer liquid sample for later use;
the SDS-phosphate buffer solution extracting solution refers to: 0.5M phosphate buffer containing 0.5% SDS by mass/volume, pH 6.90;
2) taking the insoluble glutelin macro-polymer liquid sample obtained in the step 1) by using a nylon membrane needle filter for chromatographic analysis to obtain a chemical determination result;
the chromatographic analysis is that a high performance liquid chromatograph is adopted, a mobile phase is a 50% acetonitrile water solution containing trifluoroacetic acid with the volume ratio of 0.05%, and the flow rate is 0.5 mL/min;
3) taking 1.0-1.2 mL of the insoluble glutelin macro-polymer liquid sample to be detected obtained in the step 1), and collecting spectral data; the spectrum scanning interval is 950-1650nm, the scanning times are 10 times, the temperature is room temperature, and the resolution is 5 nm;
4) calculating and analyzing the chemical measurement result obtained in the step 2) and the spectral data obtained in the step 3) by adopting a partial least square method, and establishing a prediction model; the coefficient of determination of the model is R2=0.89, the standard deviation of the model scaled is SECV = 36.40;
establishing a predicted calibration model by adopting Unscamblebler chemometrics software and combining a partial least square method;
5) eliminating the influence of spectrum baseline drift on the establishment of a predicted calibration model in the measurement process by adopting a spectrum preprocessing mode of first derivative plus S-G smoothing, and carrying out cross validation on the calibration standard deviation and the decision coefficient R of the established model2As a primary parameter in evaluating the predicted calibration model effect;
6) preparing an insoluble glutelin macro-polymer liquid sample of the sample to be detected by adopting the method same as the step 1), utilizing the predicted calibration model obtained in the step 5), and carrying out near infrared spectrum analysis on the sample to be detected according to the method in the step 3), namely obtaining the content of the insoluble glutelin macro-polymer of the sample to be detected.
2. The near-infrared determination method for the content of insoluble gluten polymers of wheat flour according to claim 1, characterized in that the extraction parameter of the ultrasonic cell disruptor in step 1) is ø 3mm probe with 10W of output work.
3. The near-infrared determination method for the content of insoluble gluten polymers of wheat flour according to claim 1 or 2, characterized in that, when the spectral data is collected in the step 3), the sample loading hardware is a liquid quartz sample cell with the thickness of 1 mm.
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