A method for rapid detection of common pigment adulteration of congou black tea based on thorn ball-shaped silver nano SERS sensor

Abstract

The present application relates to the technical field of black tea quality rapid detection, and particularly relates to a kind of common pigment adulteration rapid detection method of congou black tea based on thorn ball silver nano SERS sensor, a kind of thorn ball silver nano SERS sensor with high stability and reproducibility and high sensitivity is proposed, which is used for the new method of rapid detection and prediction of common pigment adulteration in congou black tea.The method directly takes adulterated tea soup as the research object, without complex purification treatment, and based on silver nano SERS sensor, corresponding fingerprint spectrum is quickly obtained, quantitative model is established by combining chemical information in spectrum with chemometrics, to realize accurate quantitative detection of four common synthetic pigments in black tea.The method has high detection accuracy, and the detection limit is lower than the limit requirement of food safety regulation, and has good advantages in the application of illegal pigment addition detection in tea, and provides a kind of rapid, simple and sensitive quantitative detection method for the detection of pigment adulteration in tea.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of black tea quality rapid detection, and particularly relates to a common pigment adulteration rapid detection method for congou black tea based on a thorn ball-shaped silver nano SERS sensor. BACKGROUND

[0002] Black tea is the most widely consumed tea in the world, and its bright red tea soup is very suitable for direct drinking or adding milk for drinking, so it is very popular among consumers. However, in order to improve the color of tea and tea soup, some enterprises add artificial synthetic pigments in the processing of black tea. Common artificial synthetic pigments include sunset yellow, carmine, lemon yellow (azo pigment) and erythrosine (non-azo pigment), which are difficult to distinguish from natural pigments in vision, and have the characteristics of stable properties, low cost and strong coloring power, and are often added to food to improve color. Among them, azo dyes with azo groups (-N=N-) as chromophores in the molecular structure are the most common dyes, accounting for more than half of the global dye production. The azo group can decompose to produce carcinogenic aromatic amines, which can pose a potential threat to the health of consumers in the case of excessive intake. The Food and Agriculture Organization and the World Health Organization have strict monitoring of the use of artificial synthetic pigments. At the same time, according to the "Good Practice Standard for Tea Processing" (GB32744-2016), tea shall not be added with pigments and other non-tea substances during production and processing. Therefore, it is necessary to detect the illegal pigment adulteration in black tea. In previous research reports, the artificial pigment adulteration detection technology commonly used in food mainly includes solid extraction-spectrophotometry, thin layer chromatography, high performance liquid chromatography and the like. These analysis technologies have good sensitivity in food quality monitoring, but they have some shortcomings, such as high pretreatment requirement, large amount of solvent, serious sample destruction, long analysis time, and cannot meet the needs of rapid real-time detection in trade flow process. In addition, most of the current detection methods for exogenous adulterants in food require separation and extraction of the target detection object, which cannot meet the needs of rapid and non-destructive detection. Therefore, it is urgent to develop a SERS method with high sensitivity and without pretreatment to realize trace detection of adulterants in the field of food safety control.

[0003] In view of the above defects, the present inventors have finally obtained the present application after long-term research and practice. SUMMARY

[0004] The present application aims to solve the problem of how to develop a SERS method with high sensitivity and without pretreatment to realize trace detection of adulterants, and provides a common pigment adulteration rapid detection method for congou black tea based on a thorn ball-shaped silver nano SERS sensor.

[0005] In order to achieve the above object, the application discloses a kind of common pigment adulteration rapid detection method of congou black tea based on silver nanometer SERS sensor of ball-like shape, comprising the following steps:

[0006] S1, preparation silver nano enhanced substrate as detection black tea pigment adulteration sensor;

[0007] S2, preparation different concentration gradient pigment standard and black tea sample adulterated with different concentration gradient pigment;

[0008] S3, obtain the fingerprint of each pigment standard and adulterated pigment black tea sample, qualitative discrimination black tea pigment adulteration;

[0009] S4, use the chemical information in fingerprint and chemometrics to establish black tea pigment adulteration quantitative model;

[0010] S5, obtain mixed pigment fingerprint, simultaneously identify the adulteration of multiple pigments in black tea.

[0011] The nano enhanced substrate sensor in step S1 includes silver nitrate solution, polyvinylpyrrolidone solution, formaldehyde, ammonia and rhodamine analytical reagent.

[0012] The pigment standard in step S2 includes sunset yellow, cochineal, lemon yellow and erythrosine.

[0013] The preparation method of different concentration gradient pigment standard in step S2 is to first prepare 600 μg / mL stock solution, and then dilute to different concentration gradient with pure water.

[0014] The preparation method of black tea sample adulterated with different concentration gradient pigment in step S2 is to prepare different concentration gradient by mixing common adulterated pigment with non-adulterated black tea according to specified proportion.

[0015] In step S3, different concentration pigment standard, adulterated black tea sample and silver nano SERS substrate are dropped on gold-coated glass slides in a ratio of 1:1 to obtain the fingerprint of pure tea soup and adulterated black tea sample, so as to realize rapid qualitative identification of black tea adulteration pigment.

[0016] In step S4, based on the obtained fingerprint, PLS quantitative model is established by using different variable screening methods to realize rapid monitoring and quantitative analysis of black tea adulteration pigment.

[0017] In step S5, four kinds of pigments are mixed with tea soup in equal proportion, SERS spectrum is directly obtained, mixed pigment addition amount is calculated by bringing into the established standard curve, and simultaneous identification of four kinds of pigments in black tea is realized.

[0018] Compared with the prior art, the application has the beneficial effects that:

[0019] 1、The prepared silver nanometer SERS substrate with a thorn ball shape has more SERS "hot spots", high response sensitivity to adulterated pigments in black tea, high reproducibility, the method has the characteristics of fast analysis speed, low cost and convenient online detection;

[0020] 2、The application provides a simple and fast detection method for common adulterated pigments in black tea without pretreatment;

[0021] 3、The application extracts features from original spectral data by using different variable screening methods, and can realize accurate discrimination and quantitative detection of various pigments in black tea. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 Figure a is an EDS spectrum of O, Ag and Si elements in the silver nanostructure, and Figure b is a scanning electron microscope image of the thorn ball-shaped silver nanostructure at 2 μm and 500 nm; Figure a is a stability verification of the AgNPs sensor in 80 days by using R6G as a probe molecule, Figure b is SERS intensity at 1362 cm -1 and 1509 cm -1 of two characteristic peaks under different storage times, and Figure c is a comparison of the enhancement of ordinary Raman and SERS;

[0023] Figure 2 Figure a is a SERS spectrum of four pigment standards based on the AgNPs substrate, and Figure b is a standard curve; Figure a is a SERS spectrum of (A) sunset yellow, (B) lemon yellow, (C) cochineal and (D) erythrosin at 9 concentrations (0.1-600 μg / mL); Figure a1 is a standard curve of (A) sunset yellow (1595 cm -1 ), (B1) lemon yellow (1600 cm -1 ), (C1) cochineal (1360 cm -1 ) and (D1) erythrosin (618 cm -1 );

[0024] Figure 3 Figure a is a SERS spectrum of tea soup with 50 μg / ml (A) sunset yellow, (B) lemon yellow, (C) cochineal and (D) erythrosin; DETAILED DESCRIPTION

[0025] The above and other technical features and advantages of the application will be more fully understood from the following detailed description taken in conjunction with the accompanying drawings.

[0026] Example 1

[0027] I. Experimental method

[0028] 1. Preparation of silver nano SERS substrate:

[0029] Take 5 mL of different concentrations of AgNO3 solution 2mM, add 45 mL of ultrapure water to the beaker, stir at 45°C constant temperature for 10 min, then quickly add 0.1 mL of formaldehyde, and add 0.1 mL of ammonia water, add 20 mL of PVP (5%) solution as a protective agent, the solution quickly changes from colorless to gray. At this time it indicates that the preparation of the thorn ball-shaped silver nano substrate is successful. And centrifuge the solution at 6000 rpm for 15 min, then remove the supernatant, leaving the silver nano structure. Then clean with ethanol and ultrapure water three times respectively, remove the excess unreacted reagents and surfactant molecules, and store the silver nanoparticle substrate at room temperature in the dark.

[0030] 2. Preparation of solution:

[0031] Preparation of R6G standard sample: First, prepare R6G into a 10 -1 concentration mother liquor, and then dilute it with pure water into 10 -2 ~ 10 -8 , for determining the sensitivity and reproducibility of silver nano. To determine the SERS spectrum of each pigment standard, first trace amounts of sunset yellow, lemon yellow, cochineal, and erythrosin were plated on gold-coated glass slides, and then placed under the microscope confocal Raman spectrometer workbench for direct scanning. Then prepare different concentrations of pigment standards, the solution preparation steps are as follows: first, prepare a 600 μg / mL concentration mother liquor of sunset yellow, lemon yellow, cochineal, and erythrosin standards, and then dilute it with Watsons water into 0.1, 1, 5, 10, 20, 50, 100, 200, 300 μg / mL, respectively. Detect the characteristic peaks of different concentrations of pigment standards, and analyze the trend of SERS spectrum with concentration change.

[0032] The red tea sample without any added pigment was self-made Qimen black tea according to the processing technology of Gongfu black tea. Since it is prohibited to add any food additives during tea processing, the concentration of the four pigments was determined according to the Food Safety National Standard Food Additive Use Standard (GB 2760-2014), which is within and lower than the food additive range. The concentration range of the test sample can cover the possible range of sunset yellow, lemon yellow, carmine, and erythrosin in the market. Since the tea soup will show an unpleasant color when the concentration of the adulterated pigment exceeds 600 μg / mL, 600 μg / mL is set as the maximum value. The tea water ratio is 1:50, and the tea is brewed for 5 min. The tea soup and different concentrations of each pigment are mixed at a ratio of 1:1, and 10, 20, 50, 100, 200, 300, and 600 μg / mL are prepared. The mixed solution is shaken and not purified. The tea soup without adulterated pigment is used as a blank control. Mixed pigment detection: the four pigment solutions are mixed to 50 μg / mL, and then directly detected based on the SERS substrate to verify the specificity and sensitivity of the silver nano substrate. All test samples and silver nano solutions are mixed at a ratio of 1:1, and the mixture is vortexed for 6 s to ensure sufficient interaction between the pigment and the silver nano surface. Finally, 4 μL of the mixture is placed on a microscope slide and air-dried before being placed under the microscope confocal Raman spectrometer workstation for scanning. To reduce experimental error, the same parameters are used each time, and the detection is carried out in a constant temperature and humidity environment. Each test sample is subjected to SERS detection on the same day to test the sensitivity and repeatability of the method.

[0033] 3. Characterization of silver nano substrate

[0034] The scanning electron microscope results of the prepared silver nano are shown in Figure 1 Figure a(A) is an EDS elemental analysis diagram of AgNPs particles, which shows that the prepared SERS substrate is mainly composed of silver nano with high purity. Figures a(B, C) show the silver nano electron microscope characterization results under different magnifications. From the 2 μm electron microscope image, it can be seen that the prepared silver nano is uniformly distributed, and the morphology and size are consistent. From the 500 nm field of view, it can be clearly seen that small protrusions are distributed on the surface of the thorn ball-shaped nanoballs. The surface rough AgNPs sensor provides more SERS binding "hot spots" due to the increase in surface area, which is beneficial to the adsorption of analytes and thus improves the sensitivity of the signal to the analyte. In summary, thorn ball-shaped silver nano particles with high purity and large surface area are successfully synthesized through a simple silver mirror reaction.

[0035] The sensitivity and stability of the prepared AgNPs substrate were further evaluated. Figure 1b(A) is the change of peak intensity from storage time within 80 days using R6G as a probe molecule. The results show that the signal intensity obtained within 80 days does not show significant increase or decrease, indicating that the prepared substrate has good stability. Figure 1 b(B) shows the change of peak intensity at 1362 cm -1 and 1509 cm -1 over time. As can be seen from the figure, there is no significant difference (p>0.05) within the first 80 days. Figure 1 b(C) is a comparison chart based on ordinary Raman and SERS signal response. The EF calculation results are shown in Table 1. The AgNPs have strong enhancement performance, and the enhancement coefficients are 6.9x10 8 and 6.6x10 8 , respectively. In summary, we successfully prepared a silver nano substrate with long-term stability and high sensitivity, which can be applied to rapid detection of pigments.

[0036] 4. Detection method:

[0037] The SERS spectrum was obtained using a HORIBA LabRAM HR Evolution Raman spectrometer system (Horiba Jobin Yvon). A 785 nm laser was selected, and the detection range was set to 400 cm -1 -1700 cm -1 . Before each detection, a silicon chip (520.7 cm -1 ) was used to calibrate the spectrometer. During the SERS experiment, a 50x objective lens, 50% laser power, and a collection time of 5 s were used, and the cumulative collection number was 5. The ratio of R6G probe molecules, each pigment standard, and adulterated black tea soup to silver nano SERS substrate for detection was 1:1. The mixed detection sample was placed directly under the microscope confocal Raman spectrometer workbench for scanning. Different concentration gradients were tested in two parallel controls (10 repeated parallel controls for each group). When collecting SERS spectra of 4 pigment samples, 20 points were randomly selected for each sample, and 9 concentrations were set for each pigment standard, and 180 SERS spectrum data were collected. For each pigment adulterated tea, 7 concentrations were set, and 140 adulterated SERS spectrum data were collected. To reduce experimental errors, the same parameters and constant temperature and humidity were used for detection.

[0038] 5. Data processing method:

[0039] The SERS spectrum data obtained were first processed by LabSpec 6 to remove the noise at both ends. Finally, 430-1650 cm -1The spectral information within the specified band was used, and baseline and smoothing processes were applied to reduce the influence of fluorescence on the SERS spectral signal. A hypothetical model of black tea adulteration was established using MATLAB R2014a software.

[0040] 6. Qualitative identification of pigments in adulterated black tea:

[0041] Based on the obtained pigment samples, unadulterated black tea infusion, and SERS fingerprints of adulterated black tea, such as... Figure 3 The main characteristic peaks of the four pigments, sunset yellow, lemon yellow, carmine, and erythrosine, are at 1595 cm⁻¹. -1 1600cm -1 1360cm -1 and 618cm -1 If the SERS fingerprint spectrum of adulterated black tea matches the main characteristic peaks of the SERS fingerprint spectrum of the pigment standard, it can be preliminarily determined that the target black tea sample contains Sunset Yellow, Tartrazine, Carmine, and Erythrosine pigments, and the method can be deemed to have good specificity. SERS spectra of each pigment at different concentration gradients are obtained, such as... Figure 2 (AD, A1-D1) SERS spectra and standard curves corresponding to pigment standard solution concentrations ranging from 0.1 to 600 μg / mL. Overall, the intensity of characteristic peaks in the SERS spectra is directly proportional to the concentration. Furthermore, signals can be observed even at pigment concentrations as low as 0.1 μg / mL, indicating high sensitivity of the method. Standard curves were established using the main characteristic peaks of each pigment, as shown in Figures (A1-D1). The standard curves for each pigment exhibit good linearity, with R² values ​​all greater than 0.9400, specifically 0.9998, 0.9996, 0.9403, and 0.9839. Figure 3 The SERS spectra of adulterated black tea with safflower, lemon yellow, carmine, and erythrosine were analyzed. The main characteristic peaks of each adulterant pigment were clearly visible in the results, and their intensity increased with increasing adulterant concentration. Since the tea infusion was not purified before rapid detection, other components in the tea infusion were also detected, such as those at 732 cm⁻¹. -1 The response intensity is a characteristic peak caused by catechins, and its intensity increases as the content of adulterated pigments in the tea infusion decreases. To further verify the feasibility of this method for detecting multiple mixed pigments adulterated in black tea, the four pigment solutions were mixed to a concentration of 50 μg / mL before detection, and the main characteristic peaks of each pigment could still be detected.

[0042] 7. Construction and optimization of a quantitative prediction model for adulterated pigments in black tea:

[0043] The content of the adulterated pigment in black tea is proportional to the relative characteristic peak. In the construction of the quantitative model of the adulterated pigment in black tea and optimization, the SERS spectra of the adulterated sunset yellow, lemon yellow, carmine (azo) and erythrosine (non-azo) in black tea are screened based on GA, SPA and CARS, and the GA-PLS, SPA-PLS and CARS-PLS models are constructed, and the results are shown in Table 1. By comparing the correlation coefficients of the prediction set of the constructed models, the best quantitative prediction model is the CARS-PLS model. In the established quantitative model, the RPD of the azo pigment is the lowest, which is 3, and the highest can reach 9.8, and the Rp is greater than 0.90. The performance of the non-azo pigment combined with the SERS sensor is weaker than that of the azo pigment, the RPD is 2.69, the Rc is equal to 0.91, and the Rp is equal to 0.88.

[0044] Table 1 The enhancement factor of two characteristic peaks at 1362 cm -1 and 1509 cm -1 of R6G as a probe molecule

[0045] Raman shift (cm -1 )]]> I RS ]] C RS (mg / L)]]> I SERS ]] C SRES (mg / L)]]> EF = (I SERS / C SERS ) / (I RS / C RS )]]> 1362 108.62 479.01 75481.7 0.000479 6.9 x 10 8 ]]> 1509 152.13 479.01 87756.2 0.000479 6.6 x 10 8 ]]>

[0046] Note: I RS = the intensity of R6G, C RS = the concentration of R6G; on the SERS substrate, I SERS = the intensity of R6G, C SERS = the concentration of R6G; SD = standard deviation (n = 10)

[0047] Table 2 PLS modeling results of different variable screening methods

[0048]

[0049] Note: NVs: variable number; LVs: latent variable number; Rc: correlation coefficient of calibration set; RMSECV: root mean square error of calibration; Rp: correlation coefficient of prediction set; RMSEP: root mean square error of prediction; RPD: residual prediction deviation.

[0050] In addition, the present application attempts to detect four kinds of mixed pigments synchronously, and obtains the SERS spectra of the mixed pigment samples, which are respectively substituted into the established standard curves of the four pigments. The results are shown in Table 3, and the results show that the synchronous differentiation of the mixed pigments can be realized based on the AgNPs sensor, the recovery rate is between 94.22-103.01%, the model accuracy (RSD) is less than 0.46%, and the universality is good. The present application can realize synchronous detection and accurate quantification of four kinds of pigment adulteration in black tea without purification treatment of the tea sample.

[0051] Table 3 Determination of the residual level of mixed pigments

[0052]

[0053] The above description is only preferred embodiments of the present application, which is only illustrative, not restrictive. Those skilled in the art understand that many changes, modifications, even equivalent can be made to the present application within the spirit and scope defined by the claims of the present application, but will fall within the protection scope of the present application.

Claims

1. A rapid detection method for common pigment adulteration in Gongfu black tea based on a spiky silver nano-SERS sensor, characterized in that, Includes the following steps: S1, Prepare a silver nano-reinforced substrate as a sensor for detecting adulteration of black tea pigments; S2, Prepare pigment standards with different concentration gradients and black tea samples mixed with pigments with different concentration gradients; S3, Obtain fingerprint spectra of each pigment standard and adulterated black tea sample to qualitatively determine the adulteration of black tea pigment; S4. A hypothetical model of pigment adulteration in black tea was established by combining chemical information in fingerprint spectrum with chemometrics. S5, acquire mixed pigment fingerprint spectrum, and simultaneously identify multiple pigments adulterated in black tea; The silver nano-reinforced substrate is prepared as follows: Take 5 mL of 2 mM AgNO3 solution of different concentrations, add 45 mL of ultrapure water to a beaker, stir at 45°C for 10 min, then quickly add 0.1 mL of formaldehyde and 0.1 mL of ammonia, and add 20 mL of 5% polyvinylpyrrolidone solution as a protective agent. The solution quickly changes from colorless to gray. Centrifuge the solution at 6000 rpm for 15 min, and then remove the supernatant to obtain the silver nano-reinforced substrate.

2. The rapid detection method for common pigment adulteration in Gongfu black tea based on a spiky silver nano-SERS sensor as described in claim 1, characterized in that, The pigment standards in step S2 include Sunset Yellow, Carmine, Tartrazine, and Erythrosine.

3. The rapid detection method for common pigment adulteration in Gongfu black tea based on a spiky silver nano-SERS sensor as described in claim 1, characterized in that, The preparation method for pigment standards with different concentration gradients in step S2 is as follows: first, prepare a 600 μg / mL stock solution, and then dilute it with pure water to different concentration gradients.

4. The rapid detection method for common pigment adulteration in Gongfu black tea based on a spiky silver nano-SERS sensor as described in claim 1, characterized in that, The method for preparing black tea samples with different concentration gradients of pigments in step S2 is to mix common adulterant pigments with unadulterated black tea in a specified ratio to prepare samples with different concentration gradients.

5. The rapid detection method for common pigment adulteration in Gongfu black tea based on a spiky silver nano-SERS sensor as described in claim 1, characterized in that, In step S3, pigment standards of different concentrations, adulterated black tea samples, and silver nano SERS substrates are dropped onto gold-plated glass slides in a 1:1 ratio to obtain fingerprint spectra of pure tea soup and adulterated black tea samples, so as to achieve rapid qualitative identification of adulterated pigments in black tea.

6. The rapid detection method for common pigment adulteration in Gongfu black tea based on a spiky silver nano-SERS sensor as described in claim 1, characterized in that, In step S4, based on the acquired fingerprint spectrum, a PLS quantitative model is established using different variable screening methods to achieve rapid monitoring and quantitative analysis of adulterated pigments in black tea.

7. The rapid detection method for common pigment adulteration in Gongfu black tea based on a spiky silver nano-SERS sensor as described in claim 1, characterized in that, In step S5, the four pigments are mixed with the tea soup in equal proportions, and the SERS spectrum is directly obtained. The amount of mixed pigments is calculated by substituting the spectrum into the established standard curve, so as to achieve simultaneous differentiation of the four pigments in black tea.

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