CN112945898A - Method for establishing stevia rebaudiana rebaudioside D rapid detection model - Google Patents
Method for establishing stevia rebaudiana rebaudioside D rapid detection model Download PDFInfo
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- QFVOYBUQQBFCRH-VQSWZGCSSA-N steviol Chemical compound C([C@@]1(O)C(=C)C[C@@]2(C1)CC1)C[C@H]2[C@@]2(C)[C@H]1[C@](C)(C(O)=O)CCC2 QFVOYBUQQBFCRH-VQSWZGCSSA-N 0.000 description 1
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Abstract
The invention discloses a method for establishing a rebaudioside D rapid detection model of stevia rebaudiana, which mainly comprises the following steps: collecting the near infrared spectrum of a stevia rebaudiana dry leaf powder sample by using a near infrared spectrometer; selecting representative stevia rebaudiana dry leaf powder samples as calibration samples and inspection samples according to the spectrum; precisely analyzing the rebaudioside D content of the stevia sample by using a high performance liquid chromatography; preprocessing near-infrared light data; establishing an infrared spectrum calibration equation model of rebaudioside D content in a stevia rebaudiana dry leaf powder sample by using partial least squares regression (PLS); evaluating the prediction performance of the calibration model by applying a test sample set; and establishing a near infrared analysis model and a near infrared analysis method with small errors and high decision coefficients. The method has the advantages of high analysis speed, no need of sample pretreatment, high detection precision, and capability of analyzing the rebaudioside D content of the stevia rebaudiana in time, and provides a convenient, quick and efficient analysis method for quality improvement of the stevia rebaudiana.
Description
Technical Field
The invention belongs to the technical field of biology, and particularly relates to a method for establishing a rebaudioside D rapid detection model of stevia rebaudiana.
Background
The sweet component of stevia rebaudiana sugar belongs to diterpene glycoside substances, has a common steviol aglycone structure, and forms at least 9 different diterpene glycoside substances due to different substituted glycosyl groups on aglycone. The two components with the highest content are Stevioside (St, 2-16%) and rebaudioside A (RA, 0-12%), and the sweetness is 300 times and 350 times of that of cane sugar respectively. The RA component not only has sweetness higher than that of the St component, but also has taste better than that of the St component and is close to that of cane sugar. Therefore, the content and proportion of the RA component in the total stevioside are generally used as main indexes for measuring the variety and quality of stevia rebaudiana. At present, the species planted in large area at home and abroad are mainly Japanese No. 2 and No. 3, and the main components are RA. Recent research shows that Rebaudioside D (RD, less than 0.1%) with lower content exists in stevioside, the sweetness of the stevioside is similar to that of the stevioside (250 times of that of cane sugar), the melting point of the stevioside reaches 280 ℃, and the stevioside is positioned at the first position of various glycosides; the RD taste quality and stability are both superior to those of the former two, the RD content is increased, the St content is reduced, and the stevioside taste quality is obviously improved, so the RD is a novel stevioside with a great application prospect. The Near Infrared (NIR) spectrometry technology is a physical measurement method and technology which is newly found in recent years, has the characteristics of no sample weighing, no sample pretreatment, simple and convenient operation and the like, and has obvious advantages. Foreign scholars apply near infrared spectroscopy technology to analyze St monoglycoside in stevia rebaudiana, and the analysis is primarily successful. The invention develops a rapid determination method of a new component rebaudioside D in stevia rebaudiana leaves by utilizing the near infrared spectrum technology, and establishes a rapid and efficient detection method which can be conveniently used by breeders, production enterprises and the like.
Disclosure of Invention
The invention aims to provide a determination method for rapidly detecting a new component rebaudioside D in stevia rebaudiana leaves by utilizing a near infrared spectrum technology, which is used for rapidly detecting the new component rebaudioside D in the stevia rebaudiana leaves and has important significance for rapid and efficient detection of rebaudioside D by breeders and production enterprises.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for establishing a rebaudioside D rapid detection model of stevia rebaudiana is characterized by comprising the following steps:
(1) preparing an analysis sample, and collecting a stevia rebaudiana sample with diversity in genetic way;
(2) determining a sample set, and collecting the near infrared spectrum of the stevia sample by using a near infrared spectrometer, wherein the spectrum scanning range is 4000-10000cm-1；
(3) Selecting representative stevia rebaudiana dry leaf powder samples as a calibration sample set and an inspection sample set according to the spectrum;
(4) measuring rebaudioside D content of stevia rebaudiana, processing and analyzing the calibration sample set and the test sample set by using high performance liquid chromatography to analyze the rebaudioside D content of the stevia rebaudiana sample;
(5) preprocessing near infrared light data of a calibration sample set, wherein the preprocessing comprises mathematical processing and scattering processing, so that interference variables are eliminated;
(6) establishing a regression equation according to the relationship between the near infrared spectrum of the stevia rebaudiana dry leaves preprocessed by the calibration sample set and the rebaudioside D content of the stevia rebaudiana, and constructing a calibration equation model of the rebaudioside D content in the stevia rebaudiana dry leaf powder sample by using partial least squares regression (PLS);
(7) and evaluating the prediction performance of the calibration equation by using a test sample set, and establishing the near-infrared rapid analysis and detection model.
Further, the stevia sample collection basis and the pretreatment method in the step (1) are as follows: collecting plants with multiple branches, multiple and thick leaves, no withered leaves, dark leaves and no serious diseases and insect pests, collecting the plants with various leaf shapes and leaf colors, harvesting 5-8 branches in the bud stage of a single plant, airing for 24 hours in the shade, drying, manually removing leaves, crushing the leaves, and sieving with a 60-mesh sieve.
Further, in the near infrared spectrum in the step (2), the repeated scanning times of the sample are 64 times, and the resolution is 8cm-1Near infrared scanning is carried out for 30 seconds before each sample spectrum is collected, and the near infrared scanning is used as a built-in reference of a background spectrum.
Further, the rebaudioside D content ranges in the calibration sample set in step (4) comprise the rebaudioside D content ranges in the test sample set.
Further, the processing and analyzing method of the high performance liquid chromatography in the step (4) comprises the following steps: baking stevia rebaudiana powder in an oven at 50 ℃ for 24 hours until the weight is constant, weighing 0.5g of dried stevia rebaudiana powder, putting the dried stevia rebaudiana powder into a 15mL centrifuge tube, adding 5mL of an extracting agent, uniformly mixing the stevia rebaudiana powder and the extracting agent in a mixing instrument, performing ultrasonic treatment in an ultrasonic instrument for 30min, performing centrifugation at 6000r/min for 5min at room temperature, pouring a supernatant into another 15mL centrifuge tube, adding 5mL of the extracting agent into residues again, uniformly mixing the extracting agent in the mixing instrument, performing ultrasonic treatment for 30min, performing centrifugation at 6000r/min for 5min at room temperature, combining 2 times of supernatants, uniformly mixing the stevia rebaudiana powder and the supernatant in the mixing instrument, performing centrifugation at 6000r/min at room temperature for 5 min.
Further, the mathematical processing in step (5) is to perform operation calculation on the initial spectrum of the stevia powder sample by sequentially using a first derivative and a second derivative in the pathlength type, and the scattering processing is a scattering correction Method (MSC).
Further, the calibration equation in step (6) has a corrected standard deviation (RMSEC) of 0.174, a verified standard deviation (RMSEP) of 0.118, a corrected correlation coefficient (RSQ) of 0.898, a verified correlation coefficient (R2) of 0.872, and a relative analysis error RPD (SD/SEP) value of 3.170.
Further, in the step (7), a representative stevia sample is continuously added to the near-infrared rapid analysis and detection model in the later work, so as to ensure the stability and reliability of the model.
Furthermore, after the initial spectrum operation calculation of the stevia rebaudiana powder sample is carried out by adopting the first derivative, the wave band fluctuation of the spectrum image is more obvious, the peak change display is steeper and clearer, and the spectrum baseline translation background information is removed.
A method for establishing a stevia rebaudiana D rapid detection model is applied to rapid analysis and detection of the rebaudiana rebaudi.
Compared with the conventional rebaudioside D detection method of stevia rebaudiana, the detection method disclosed by the invention has the advantages of high analysis speed, no need of sample pretreatment and high detection precision, can be used for analyzing the rebaudioside D content of stevia rebaudiana in time, provides a convenient, rapid and efficient analysis method for quality improvement of stevia rebaudiana, and has important significance for rapid and efficient detection of rebaudioside D for breeders and production enterprises.
Drawings
FIG. 1: all samples are in NIR spectrum;
FIG. 2 is a schematic representation of a near infrared spectrum after first derivative treatment;
FIG. 3: a near infrared spectrum schematic diagram after second derivative processing;
FIG. 4: the PRESS values of different factors of RD are shown in a graph;
FIG. 5: a schematic diagram of a near-infrared calibration model of a stevia RD component;
FIG. 6: distribution of sample frequency for different amounts of RD.
Detailed Description
The technical scheme of the patent is further explained by combining the attached drawings and the embodiment.
Example 1
The selection basis and the processing method of the single stevia rebaudiana plant are as follows: (1) the number of branches is large, and the number of blades is large and thick; (2) no withered leaves and dark leaves, and no serious pest and disease damage; (3) large and small leaves, light leaf color, and various leaf shapes (round, oval and strip shapes) are all contracted; (4) harvesting 5-8 branches in the bud stage of a single plant, placing the branches in a shade or under a tree, airing for 24 hours, and then moving the branches to the sun for airing; (5) manually removing leaves, grinding the leaves into powder with a traditional Chinese medicine grinder, sieving with a 60-mesh sieve, storing in a self-sealing plastic bag, and storing in a constant-temperature storage room at 15 deg.C until being taken out before analysis.
Example 2
Collecting a near infrared spectrum of a sample: taking out the dried stevia rebaudiana sample powder in the dryer, and filling the dried stevia rebaudiana sample powder into a 5cm sample containing cup matched with the near infrared instrument by using a spoon, wherein the sample containing cup is cleaned to be clean without residue of the previous powder sample. During filling, the sample powder in the sample containing cup is required to be uniform, have no gap and have a smooth mouth surface, the cup cover is slightly screwed after the sample containing cup is filled and compacted, and the sample powder is not easy to loose or tighten and then placed in a rotation detector. Stevia powder samples were scanned using an Antaris II Fourier transform near infrared (FT-NIR) spectrometer. Before the spectrum of the stevia rebaudiana powder sample is collected, a new workflow is added into RESULT-Operation software and named. The spectral powder sample collected in the test is a stevia rebaudiana leaf, belongs to a solid sample, and adopts a diffuse reflection working mode in a long-wave near-infrared region, namely, an integrating sphere diffuse reflection collection system is adopted in a sample specification selection sampling mode (the sample spectrum measured by an integrating sphere is high in signal-to-noise ratio and good in repeatability), and the spectral scanning wavelength range is set to be 4000-10000 cm--1And sets the corresponding scanning times and resolution. The default number of repeated scans of the sample was 64, with a resolution of 8cm-1. Near infrared scanning for 30 seconds of background spectra was used as a built-in reference before each sample spectrum acquisition. And (3) loading and scanning twice for each bag of stevia rebaudiana powder sample, respectively recording as variety a and variety b, correctly naming the scanned sample powder by spectrum, and storing.
Example 3
Determination of sample set: according to the results of infrared spectrum collection of example 2, 139 stevia powder samples having representative spectra were selected and then uniformly divided into a calibration sample set and an inspection sample set according to the spectral characteristics, wherein the calibration sample set contains 117 stevia powder samples and the inspection sample set contains 22 stevia powder samples.
High performance liquid chromatography determination of rebaudioside D of stevia rebaudiana bertoni:
sample preparation: pulverizing dried stevia leaf sample with pulverizer, sieving with 60 mesh sieve, sealing and storing.
And (3) sample liquid determination: baking stevia rebaudiana powder in an oven at 50 ℃ for 24h to constant weight; accurately weighing 0.5g of dried stevia rebaudiana powder, and placing the powder into a 15mL centrifuge tube; precisely adding 5mL of an extracting agent, and uniformly mixing by using a uniformly mixing instrument; performing ultrasonic treatment in an ultrasonic instrument for 30 min; centrifuging at 6000r/min for 5 min; pouring the supernatant into another 15ml centrifuge tube; precisely adding 5mL of the extractant into the residue again, and uniformly mixing by using a uniformly mixing instrument; performing ultrasonic treatment for 30 min; centrifuging at 6000r/min for 5 min; mixing the supernatants for 2 times, and mixing; centrifuging at 6000r/min for 5 min; 1.5mL of sample supernatant was aspirated, filtered through a 0.45 μm needle-type microporous filter membrane, and then injected. Each variety is repeated for 2 times, and if the error of the results of the two times exceeds 0.5 percent, the two times are repeated again.
Preparation of a steviol glycoside standard solution: placing a standard sample stevioside in a 50 ℃ oven to be baked for 24h to constant weight; accurately weighing 0.3g of RA standard sample and 0.04g of RD standard sample, adding into a 50mL measuring flask, and dissolving with 70% (g/g) ethanol/water solution; performing ultrasonic treatment for 1 h; fixing the volume to a scale, and taking the volume as standard stock solution, wherein the mass concentration of the standard stock solution is RA 6mg/mL and RD 0.8 mg/mL; accurately sucking 0.5, 1.0, 2.0 and 4.0mL respectively into a 10mL volumetric flask for constant volume to obtain RA 0.6, 1.2, 2.4, 4.8, 6mg/mL, RD 0.08, 0.16, 0.32, 0.64, 0.8mg/mL and 5 gradient standard solutions.
And (3) calculating the stevioside content: referring to the national standard GB 8270-2014 food additive stevioside published by 2015-01-28, the mass fraction w of the RD content (on a dry basis) is calculated according to the following formula:
mS-the mass of RA in a standard solution of stevioside (on a dry basis) in milligrams (mg);
m-mass of sample in sample solution (on a dry basis), 500 mg;
f-formula weight ratio of RD to RA: 1.17
A-peak area value of RD in chromatogram of sample solution;
AS-peak area value of RA in standard solution chromatogram.
As shown in table 1, the predicted stevia rebaudiana glycoside content of the calibration sample set is 117, RD ranges between 0.034 and 2.024%, the number of the test sample set is 22, RD ranges between 0.106 and 0.960%, and the test sample set sample content ranges are included in the calibration sample set sample content range. The mean and Standard Deviation (SD) of the RD (rebaudioside D) content of the calibration sample set and the test sample set were 0.368, 0.396 and 0.382, 0.225, respectively, which are similar values. The results show that the selection of the samples is representative, the differences of the maximum value, the minimum value, the average value and the standard deviation between the samples of the calibration sample set and the samples of the test sample set are small, and the selection of the calibration sample set and the test sample set is reasonable and can be used for creating and applying a near infrared spectrum model.
TABLE 1 statistical results of distribution of RD content measurements (%)
Example 4
Optimizing a near infrared scaling equation: and establishing a regression equation according to the relationship between the preprocessed stevia rebaudiana dry leaf near infrared spectrum and the target character content, and setting 4-fold cross validation in the training process to prevent the overfitting phenomenon. According to the research, a TQ Analyst V9.4.45 software (Thermo Fisher Scientific Inc.) is adopted to collect stevia rebaudiana near infrared spectrum and establish a calibration equation, spectrum pretreatment is performed in a full wavelength range, the model is constructed by adopting two spectrum pretreatment methods of first derivation (1st D) and second derivation (2nd D) and matching three optical path correction methods of Constant optical path (Constant), multiple scattering correction Method (MSC) and standard normal variable transformation (SNV) and three quantitative analysis methods of Partial Least Squares (PLS), Principal Component Regression (PCR) and Multiple Linear Regression (MLR), a plurality of near infrared calibration equation models are respectively constructed for optimization, and an optimal calibration equation model is screened out according to parameters obtained by the model.
Example 5
Preprocessing a near-infrared spectrogram: the acquired near-infrared scanning original spectrum is shown in fig. 1, the initial spectrum of the stevia rebaudiana powder sample is calculated by sequentially adopting a first derivative and a second derivative in the pathlength type, as shown in fig. 2 and 3, the wave band fluctuation of the spectrum image of the initial spectrum after the first derivative processing is carried out is more remarkable, the peak change is displayed more steeply and clearly, the originally flat spectrum curve is divided into a plurality of peaks, and background information such as spectrum baseline translation and the like is obviously removed.
Example 6
Rebaudioside D near infrared calibration equation creation:
PRESS test: the PRESS test may show that each component in the method selects the best number of factors. The PRESS value is an indicator of the PLS or ACLS method calibration error. Each time a factor representing useful information is added to the calibration model, it reduces the error and lowers the depression value. At some point, the PRESS value may reach a minimum, tend to plateau, or begin to increase. If a factor is added after this point, the performance of the method is not improved and may be degraded if the calibration model is over-fitted.
Fig. 4 illustrates the change law of the PRESS value of the selected component when the software increases the number of factors used for the calibration method, as the second point in the graph represents the first number of factors and their PRESS values. As can be seen from the figure, the PRESS value is lowest when 2 factors are used, so 2 factors are selected for modeling.
The effect of different chemometric analyses on the scaling equation: the combination method of calculation and pretreatment for constructing the stevia rebaudiana RD component content model is various, and parameter results of calibration equations obtained by different collocation combinations are often quite different. The purpose of the experiment is to select a collocation method which finds out the most excellent model calibration prediction result as a stevia model. Therefore, the scanned stevia rebaudiana powder sample spectrum is prepared by various methods and continuously selected from various schemes. The main modeling modes in the TQ software are Partial Least Squares (PLS), Principal Component Regression (PCR) and stepwise Multiple Linear Regression (MLR); the optical path correction measures include uncorrecting, namely, optical path constancy (Constant), standard canonical transformation (SNV), and additional scatter correction (MSC).
The different methods are respectively combined with a first derivative (first derivative) and a second derivative (second derivative) for modeling, and the obtained parameters are shown in table 2. And comparing the correction decision coefficient, the test set decision coefficient, the correction standard deviation, the prediction standard deviation and the like of each collocation method, and selecting the optimal modeling scheme. By looking up documents, the larger the value of the correlation coefficient of the calibration equation model is, the best the fitting effect and accurate value of the simulation are; the larger the RPD value, the higher the model accuracy.
Compared with other modeling methods, the accuracy of the stevia rebaudiana RD scaling equation obtained by selecting a partial least squares regression (PLS) construction model is higher; under the same modeling condition, a calibration equation obtained by not correcting the spectrum (constant) is better; in the same modeling method, when the optical path correction condition is unchanged, the spectrum preprocessing data operated by the second derivative formula is better than the calibration effect obtained by adopting the first derivative calculation method. The data show that partial least squares regression (PLS) is preferably adopted for constructing the stevia rebaudiana RD model, the optical path correction method adopts uncorrected, namely Constant optical path (Constant), and the spectrum preprocessing method runs through a second derivative method, the effect is optimal, the corrected standard deviation (RMSEC) is 0.174, the verified standard deviation (RMSEP) is 0.118, the corrected correlation coefficient (RSQ) is 0.898, and the verified correlation coefficient (R) is 02) 0.872 and an RPD (SD/SEP) value of 3.170.
TABLE 2 comparison of the effects of different treatment combinations on parameters of the calibration equation for the content of stevia RD components
Note: SEC is the correction standard deviation, RSQ is the correction determining coefficient, SEP is the prediction standard deviation, R2To predict the coefficient of determination for the samples, RPD-SD/SEP is the relative analytical error.
Creation of near-infrared scaling equation: the absolute error distribution diagram of the near infrared calibration model of the RD component constructed by using the optimal modeling method is shown in fig. 5, which visually shows the absolute deviation (absolute deviation) between the predicted value and the actual value of the stevia calibration model, and the 139 correction sets (indicated by circles in fig. 5) and the detection sets (indicated by plus signs in fig. 5) of the stevia sample powder selected by the experiment are observed in the diagram to be uniformly staggered, not regularly and disorderly scattered on two sides of the oblique line, not excessively deformed and stretched into other shapes, and not showing any abnormal condition.
The method shows that the model of the rebaudioside D component of the stevia rebaudiana constructed by the PLS method in the experiment has high accuracy, and the model can be used for predicting the content of the rebaudioside D component in other stevia rebaudiana samples.
Example 7
Using the established model, RD values of 474 laboratory-stored and collected stevia rebaudiana and high RD offspring of the variety sown in 2018 were predicted. The variation range of the content of the RD of the obtained sample to be detected is 0.002% -2.073%. The histogram of the number distribution of the RD samples at different contents is shown in fig. 6. The number of the RD content samples is distributed in a skewed manner, and the RD content samples are mainly concentrated in three sections of 0.000% -0.200%, 0.201% -0.400% and 0.401% -0.600%.
The present invention is further illustrated and described in the above embodiments, which are only used to help understand the method and the core idea of the present application, and the content of the present specification should not be construed as limiting the present application since the skilled person can change the specific implementation and application scope according to the idea of the present application.
Claims (10)
1. A method for establishing a rebaudioside D rapid detection model of stevia rebaudiana is characterized by comprising the following steps:
(1) preparing an analysis sample, and collecting a stevia rebaudiana sample with diversity in genetic way;
(2) determining a sample set, and collecting the near infrared spectrum of the stevia sample by using a near infrared spectrometer, wherein the spectrum scanning range is 4000-10000cm-1；
(3) Selecting representative stevia rebaudiana dry leaf powder samples as a calibration sample set and an inspection sample set according to the spectrum;
(4) measuring rebaudioside D content of stevia rebaudiana, processing and analyzing the calibration sample set and the test sample set by using high performance liquid chromatography to analyze the rebaudioside D content of the stevia rebaudiana sample;
(5) preprocessing near infrared light data of a calibration sample set, wherein the preprocessing comprises mathematical processing and scattering processing, so that interference variables are eliminated;
(6) establishing a regression equation according to the relationship between the near infrared spectrum of the stevia rebaudiana dry leaves preprocessed by the calibration sample set and the rebaudioside D content of the stevia rebaudiana, and constructing a calibration equation model of the rebaudioside D content in the stevia rebaudiana dry leaf powder sample by using partial least squares regression (PLS);
(7) and (3) evaluating the prediction performance of the calibration equation by using the test sample set, and establishing a near-infrared rapid analysis detection model.
2. The method for establishing a stevia rebaudiana rebaudioside D rapid detection model according to claim 1, wherein the basis for collecting the stevia rebaudiana sample and the pretreatment method in step (1) are as follows: collecting plants with multiple branches, multiple and thick leaves, no withered leaves, dark leaves and no serious diseases and insect pests, collecting the plants with various leaf shapes and leaf colors, harvesting 5-8 branches in the bud stage of a single plant, airing for 24 hours in the shade, drying, manually removing leaves, crushing the leaves, and sieving with a 60-mesh sieve.
3. The method of claim 1, wherein in the near infrared spectrum of step (2), the number of repeated scans of the sample is 64, and the resolution is 8cm-1Near infrared scanning is carried out for 30 seconds before each sample spectrum is collected, and the near infrared scanning is used as a built-in reference of a background spectrum.
4. The method of claim 1, wherein the rebaudioside D content ranges in the calibration sample set in step (4) comprise the rebaudioside D content ranges in the test sample set.
5. The method for establishing a stevia rebaudiana rebaudioside D rapid detection model according to claim 1, wherein the HPLC analysis method in step (4) comprises: baking stevia rebaudiana powder in an oven at 50 ℃ for 24 hours until the weight is constant, weighing 0.5g of dried stevia rebaudiana powder, putting the dried stevia rebaudiana powder into a 15mL centrifuge tube, adding 5mL of an extracting agent, uniformly mixing the stevia rebaudiana powder and the extracting agent in a mixing instrument, performing ultrasonic treatment in an ultrasonic instrument for 30min, performing centrifugation at 6000r/min for 5min at room temperature, pouring a supernatant into another 15mL centrifuge tube, adding 5mL of the extracting agent into residues again, uniformly mixing the extracting agent in the mixing instrument, performing ultrasonic treatment for 30min, performing centrifugation at 6000r/min for 5min at room temperature, combining 2 times of supernatants, uniformly mixing the stevia rebaudiana powder and the supernatant in the mixing instrument, performing centrifugation at 6000r/min at room temperature for 5 min.
6. The method of claim 1, wherein the mathematical process in step (5) is performed by using a first derivative and a second derivative in sequence in a pathlength type to perform a calculation on the initial spectrum of the stevia rebaudiana powder sample, and the scattering process is a scattering correction Method (MSC).
7. The method of claim 1, wherein the calibration equation in step (6) has a corrected standard deviation (RMSEC) of 0.174, a verified standard deviation (RMSEP) of 0.118, a corrected correlation coefficient (RSQ) of 0.898, and a verified correlation coefficient (R) of 0.8982) 0.872 and a relative analytical error RPD (SD/SEP) value of 3.170.
8. The method for establishing a stevia rebaudiana rebaudioside D rapid detection model according to claim 1, wherein in the step (7), a representative stevia rebaudiana sample is continuously added to the near-infrared rapid analysis detection model in the later work to ensure the stability and reliability of the model.
9. The method for establishing a stevia rebaudiana rebaudioside D rapid detection model according to claim 6, wherein after the initial spectrum of the stevia rebaudiana powder sample is calculated by adopting the first derivative, the wave band fluctuation of the spectrum image is more remarkable, the peak change is more steeply and clearly displayed, and the spectrum baseline shift background information is removed.
10. The method for establishing the stevia rebaudiana rebaudioside D rapid detection model according to any one of claims 1 to 9, which is applied to rapid analysis and detection of the rebaudioside D content of stevia rebaudiana.
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