Dual-mode aquatic product freshness intelligent indication label and preparation method and application thereof

Abstract

The invention belongs to the technical field of food safety detection, and discloses a dual-mode aquatic product freshness intelligent indication label and a preparation method and application thereof. The preparation method comprises the steps that after gold nanoparticles are dispersed in a reducing agent aqueous solution, a silver salt solution is dropwise added, then vibration treatment is conducted, and gold-core silver-shell nanoparticles are obtained; adjusting the pH value of the anthocyanin concentrated solution to be acidic, and uniformly mixing the anthocyanin concentrated solution with the gold-core silver-shell nanoparticles to obtain a gold-core silver-shell nanoparticle / anthocyanin aggregate solution; and dispersing agar and polyvinyl alcohol in water, heating to form gel, adding the gold-core silver-shell nanoparticle / anthocyanin aggregate solution at 45-50 DEG C, uniformly mixing, and cooling and solidifying to obtain the dual-mode intelligent indication label for freshness of aquatic products. The preparation method provided by the invention is simple and easy to operate, green and environment-friendly, and easy for batch preparation, and the prepared dual-mode aquatic product freshness intelligent indication label can realize sensitive and accurate quantitative analysis of aquatic product freshness indexes.

Description

Technical Field

[0001] The present invention relates to the technical field of food safety detection, and in particular to a dual-mode aquatic product freshness intelligent indicator label and a preparation method and application thereof. Background Art

[0002] Aquatic products are an important part of human diet and can provide essential nutrients such as protein, fatty acids and vitamins. However, aquatic products have a high water content and are prone to spoilage during storage and circulation due to the action of microorganisms and endogenous proteases. Therefore, in order to ensure consumer food safety, it is very necessary to carry out quality and safety monitoring during the circulation of aquatic products.

[0003] The corruption of aquatic products involves various reactions, including lipid and protein oxidation, enzyme reactions, and microbial fermentation. Lipids in food are easily oxidized, resulting in the loss of fat-soluble vitamins and the production of odors and other compounds. Enzymatic hydrolysis reactions caused by endogenous or exogenous enzymes and corruption caused by microbial contamination will produce various metabolites, including biogenic amines, aldehydes, etc. As the storage time of aquatic products increases, the number of bacteria will also increase. Existing methods for detecting the freshness of aquatic products mainly include sensory testing, physical and chemical testing, microbiological testing, electronic noses, near-infrared spectroscopy and other new detection technologies. Among them, sensory testing is fast and simple, but it has the shortcomings of subjectivity and one-sidedness; physical and chemical testing and microbiological testing are highly accurate but complex and time-consuming; although new detection technologies such as electronic noses and near-infrared spectroscopy have good effects, their high costs limit their application. Therefore, a cheap, non-destructive, simple and accurate detection method is needed.

[0004] The food freshness smart indicator label is a means of intuitively reflecting the freshness of food through the color change of the label based on the reaction of some characteristic gases produced during the food spoilage process with specific reagents. However, the existing freshness smart indicator labels are mainly prepared based on chemical synthetic pigments and natural pigments that are sensitive to specific pH. Although the preparation method is simple, the prepared freshness smart indicator labels can only reflect the freshness of the monitored food through the color change of the label, resulting in poor sensitivity of the label for early detection of freshness changes in aquatic products. Often, the label will only undergo obvious color changes in the middle and late stages of food spoilage; the degree of spoilage of aquatic products can only be semi-quantitatively judged through color changes, and more accurate quantitative information cannot be obtained. To this end, the prior art provides some food freshness smart indicator labels based on special materials. For example, the prior art CN116333174A discloses a nanofiber membrane smart label, which is prepared by mixing cellulose with an organic base and an organic solvent, then introducing CO2, and then adding one or more of anhydride, lactide, and polyester as raw materials to mix, and reacting under N2 to obtain cellulose ester; then in a CO2 environment, the cellulose ester is reacted with coumarin 151 to obtain a cellulose-based solid fluorescent material. The cellulose-based solid fluorescent material is dissolved in a mixed solution of N,N-dimethylacetamide and acetone, and a nanofiber membrane smart label is made by electrospinning, and then the nanofiber membrane smart label is sealed together with the aquatic product, and the freshness of the aquatic product is detected according to the fluorescence change of the nanofiber membrane smart label. Although this existing technology can improve the accuracy of detection of aquatic products, the preparation method of the nanofiber membrane smart label is cumbersome, the preparation process requirements are strict, the process operation is difficult, and a large amount of organic bases and organic solvents are required. The preparation cost is high, and the organic waste liquid generated will cause certain environmental pollution. The preparation is green and environmentally friendly, which is not conducive to promotion and large-scale use. Summary of the invention

[0005] In order to achieve more accurate quantification of the freshness of aquatic products by using a label, the present invention provides a dual-mode aquatic product freshness intelligent indicator label and its preparation method and application. The present invention utilizes the principle of anthocyanin structural changes caused by pH in an alkaline environment, and by compounding gold core silver shell nanoparticles and anthocyanins, anthocyanins are adsorbed on the surface of gold core silver shell nanoparticles and aggregated to form gold core silver shell nanoparticles / anthocyanin aggregates. The gold core silver shell nanoparticles / anthocyanin aggregates are then mixed with agar and polyvinyl alcohol to form a solid dual-mode aquatic product freshness intelligent indicator label, so as to achieve sensitive and accurate quantitative analysis of aquatic product freshness indicators through the dual-mode aquatic product freshness intelligent indicator label of the present invention.

[0006] The dual-mode aquatic product freshness intelligent indicator label and the preparation method thereof of the present invention are realized by the following technical solutions:

[0007] The first object of the present invention is to provide a method for preparing a dual-mode aquatic product freshness intelligent indicator label, comprising the following steps:

[0008] Step 1, preparation of gold core-silver shell nanoparticle solution: preparing gold core-silver shell nanoparticle solution by reducing agent reduction method.

[0009] It should be noted that, in order to achieve more accurate quantification of the freshness of aquatic products by the label, the present invention composites gold core-silver shell nanoparticles and anthocyanins, so that the gold core-silver shell nanoparticles serve as the SESR enhancement substrate of anthocyanins, and utilizes the interaction between anthocyanins and the gold core-silver shell nanoparticles to induce the aggregation of the gold core-silver shell nanoparticles, thereby generating a large number of SERS "hot spots", significantly enhancing the Raman signal of anthocyanins in the indicator label, so as to achieve sensitive and accurate quantitative analysis of the freshness index of aquatic products.

[0010] In order to improve the composite effect of gold core-silver shell nanoparticles and anthocyanins, in some preferred embodiments of the present invention, the gold core-silver shell nanoparticle solution is prepared by a reducing agent reduction method, and the particle size of the obtained gold core-silver shell nanoparticles is 40nm to 50nm.

[0011] In some other preferred embodiments of the present invention, the gold core silver shell nanoparticles are prepared by the following steps: colloidal gold nanoparticles are prepared by a reducing agent reduction method. A reducing agent is dispersed in water to form a reducing agent aqueous solution, and colloidal gold nanoparticles are dispersed in the reducing agent aqueous solution to obtain a mixed solution. A silver salt solution is added dropwise to the mixed solution, and the silver ions provided by the silver salt solution are reduced to elemental silver by the reducing agent in the reducing agent aqueous solution, and a silver layer is formed on the surface of the gold nanoparticles to obtain a gold core silver shell nanoparticle solution, which is recorded as Au@AgNPs solution.

[0012] In order to ensure that a layer of silver can be coated on the surface of the gold nanoparticles, the present invention preferably first mixes the colloidal gold nanoparticles with the reducing agent aqueous solution, and then adds the silver salt solution dropwise to ensure that the silver ions in the added silver salt solution can fully contact the reducing agent and the gold nanoparticles, so that the silver ions are reduced to elemental silver by the reducing agent on the surface of the gold nanoparticles, and finally the silver layer is uniformly coated on the surface of the gold nanoparticles to obtain Au@AgNPs. Among them, in some preferred embodiments of the present invention, the reducing agent used is one or more of trisodium citrate and ascorbic acid to ensure that the silver salt is slowly reduced and uniformly coated on the surface of the gold nanoparticles.

[0013] In some preferred embodiments of the present invention, the molar ratio of the reducing agent to the silver salt in the silver salt solution is 1:0.8-1, so as to ensure that the reducing agent can fully reduce the silver ions provided by the silver salt solution to elemental silver. In some preferred embodiments of the present invention, the silver salt solution is added dropwise to the mixed solution at a dropping rate of 10 μL / 30s-15 μL / 30s, so as to ensure that each addition of the silver salt solution is in full contact with the mixed solution.

[0014] In some preferred embodiments of the present invention, after the silver salt solution is added dropwise, the solution obtained after the addition is subjected to an oscillation treatment, so as to ensure that the silver ions in the silver salt solution can fully contact with the reducing agent and the gold nanoparticles through the oscillation treatment, thereby achieving the silver ions being reduced to elemental silver by the reducing agent on the surface of the gold nanoparticles and uniformly coated on the surface of the gold nanoparticles. In order to ensure that the above effects can be achieved, in other preferred embodiments of the present invention, the oscillation rate of the oscillation treatment is 800rpm to 1000rpm, and the oscillation time is 30min to 45min.

[0015] In some preferred embodiments of the present invention, the silver salt in the silver salt solution is silver nitrate. In some preferred embodiments of the present invention, the volume ratio of the colloidal gold nanoparticles to the silver salt in the silver salt solution is 3mL:60μL-180μL; and the concentration of the silver salt in the silver salt solution is 8mM-12mM.

[0016] In some preferred embodiments of the present invention, when preparing colloidal gold nanoparticles by sodium citrate reduction method, colloidal AuNPs are specifically prepared by the following preparation method: HAuCl4·4H2O solution and water are mixed in a volume ratio of 1 to 1.5:100, heated to boiling, and then 1.0 mL to 1.5 mL of trisodium citrate aqueous solution is added to the boiling solution while stirring, and when the color of the solution changes to purple-red, heating and stirring are continued for 3 min to 7 min, and the reaction is terminated and cooled to room temperature to obtain colloidal AuNPs. Wherein, the mass concentration of HAuCl4·4H2O solution is 0.8% to 1.2%, and the mass concentration of trisodium citrate aqueous solution is 0.8% to 1.2%.

[0017] Step 2, preparation of Au@AgNPs / anthocyanin aggregate solution: using alcohol solution as extraction solvent, extracting anthocyanins from anthocyanin-rich plant materials by alcohol method to obtain anthocyanin extract, and then concentrating to 1 / 11 to 1 / 9 of the original volume of the anthocyanin extract to obtain anthocyanin concentrate. Adjust the pH of the anthocyanin concentrate to an acidic pH, such as pH 5 to 7, and then mix the anthocyanin concentrate with Au@AgNPs to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0018] It should be noted that, in some preferred embodiments of the present invention, the plant material rich in anthocyanins is one or more of purple cabbage, black carrot, mulberry, rose, black grape skin and purple sweet potato.

[0019] In some preferred embodiments of the present invention, when anthocyanins are extracted from anthocyanin-rich plant materials by alcohol method, the solid-liquid ratio is 50g-80g:500mL; the alcohol solution is an ethanol aqueous solution with a volume fraction of 55%-65%.

[0020] In some more preferred embodiments of the present invention, the anthocyanin-rich plant material is obtained by the following steps: taking anthocyanin-rich plant material, chopping, drying and crushing to obtain anthocyanin source powder; dispersing the anthocyanin source powder in an alcohol solution, stirring to fully dissolve the anthocyanin in the dried product in the alcohol solution, and then filtering with Whatman filter paper to remove the filter residue to obtain anthocyanin extract; concentrating the obtained anthocyanin extract to 1 / 11 to 1 / 9 of the original volume of the anthocyanin extract to obtain anthocyanin concentrate. Among them, in some preferred embodiments of the present invention, the anthocyanin-rich plant material is chopped to about 8 cm 2 ~12cm 2 In some preferred embodiments of the present invention, the stirring temperature of the stirring treatment is 25°C to 40°C, and the stirring time is 2h to 4h. In some preferred embodiments of the present invention, the drying temperature is 40°C to 50°C. In some preferred embodiments of the present invention, during concentration, the concentration is carried out by rotary evaporation using a rotary evaporator.

[0021] In some preferred embodiments of the present invention, the volume ratio of anthocyanin concentrate to Au@AgNPs solution is 0.2-0.5:3-12. In some preferred embodiments of the present invention, before mixing anthocyanin concentrate with Au@AgNPs, the anthocyanin concentrate is adjusted to a pH of 5-7 to achieve the purpose of sensitive response of anthocyanin color information and Raman signal. In some preferred embodiments of the present invention, when mixing anthocyanin concentrate with Au@AgNPs, vortex incubation is used to mix to ensure that anthocyanin is adsorbed on the surface of Au@AgNPs and induce aggregation between Au@AgNPs to form Au@AgNPs / anthocyanin aggregates.

[0022] Step three, compounding with agar and polyvinyl alcohol: disperse agar and polyvinyl alcohol in water, heat to boiling and stir, then cool to 45°C~50°C to obtain agar / polyvinyl alcohol gel; add Au@AgNPs / anthocyanidin aggregate solution to the agar / polyvinyl alcohol gel and mix well, and after cooling and solidifying, a dual-mode aquatic product freshness intelligent indicator label is obtained.

[0023] It should be noted that, in the present invention, agar and polyvinyl alcohol are first mixed in water, and then heated to boiling and stirred to allow agar and polyvinyl alcohol to fully react to form an agar / polyvinyl alcohol gel, wherein the stirring time of the stirring treatment is 1 to 2 hours.

[0024] In some preferred embodiments of the present invention, the mass ratio of agar to polyvinyl alcohol is 4:1-3, so as to ensure that agar and polyvinyl alcohol can fully react and form agar / polyvinyl alcohol gel. Wherein, the molecular weight of polyvinyl alcohol is 27000. In some preferred embodiments of the present invention, the amount ratio of water to agar is 45mL-55mL:0.8g.

[0025] In some preferred embodiments of the present invention, after the stirring treatment is completed, the solution system is cooled to 45°C to 50°C, and then the Au@AgNPs / anthocyanidin aggregate solution is added to prevent the anthocyanin structure from being destroyed at high temperature. In some preferred embodiments of the present invention, the dosage ratio of the Au@AgNPs / anthocyanidin aggregate solution to agar is 3.4mL to 12.4mL:0.8g.

[0026] The second object of the present invention is to provide a dual-mode aquatic product freshness intelligent indicator label prepared by the above preparation method.

[0027] The third object of the present invention is to provide an application of the dual-mode aquatic product freshness intelligent indicator label for reflecting the freshness of food.

[0028] In some preferred embodiments of the present invention, the evaluation of food freshness is achieved by the following steps:

[0029] 1) Establish an evaluation model

[0030] Collection intelligent indicator label 800cm -1 ~1800cm -1 The SERS signals in the range were collected by averaging 5 points for each tag and the Raman shift of 840 cm -1 The overall SERS spectrum of the label is normalized by the Raman characteristic peak at , and a partial least squares regression model, namely the PLSR prediction model, is established between the SERS signal of the indicator label and TVB-N. The PLSR prediction model is a regression model of multiple dependent variables to multiple independent variables. The high-dimensional data space of the independent variables and the dependent variables is projected into the corresponding low-dimensional space, and mutually orthogonal eigenvectors of the independent variables and the dependent variables are obtained respectively. Then, a univariate linear regression relationship is established between the eigenvectors of the independent variables and the dependent variables, and then a quantitative model with TVB-N value as the independent variable and Raman spectrum signal as the dependent variable is obtained. When the SERS signal response value of the Raman spectrum is input into the model, the corresponding TVB-N value will be output. Through the determination coefficient R of the model 2, root mean square error RMSE to evaluate and verify the model, where R 2 The closer it is to 1, the smaller the RMSE is, indicating that the prediction performance of the model is better.

[0031] 2) The dual-mode intelligent indicator label prepared in the present invention is placed inside the packaging of the aquatic product to be tested and stored at a temperature of 0° C. to 37° C.

[0032] 3) Detect the colorimetric and SERS signals of the intelligent indicator tag, so as to qualitatively judge the freshness of the aquatic product to be tested through the change of the tag color response; and quantitatively judge the TVB-N value of the aquatic product to be tested through the change of the SERS signal response.

[0033] Among them, according to the change of label color response, the freshness of the aquatic product to be tested is qualitatively judged according to the following standards:

[0034] When the label color is purple or dark purple, the aquatic product to be tested is in the first-level freshness state.

[0035] When the label color turns dark blue, the aquatic product to be tested is in the second level of freshness.

[0036] When the label turns light blue, the aquatic product to be tested is completely spoiled.

[0037] According to the response value of the SERS signal, the corresponding TVB-N content is obtained by bringing it into the PLSR prediction model. The freshness grade of aquatic products is evaluated based on the obtained TVB-N content:

[0038] When TVB-N < 20mgN / 100g, it is the first-level freshness;

[0039] When TVB-N is 20mgN / 100g~30mgN / 100g, it is the second level of freshness;

[0040] When TVB-N>30mgN / 100g, it is corrupt.

[0041] In some other preferred embodiments of the present invention, the test conditions of Raman spectroscopy are as follows: the Raman spectrometer model is RMS1000 of Ruhai Optoelectronics, the laser excitation wavelength is 785nm, and the collection range is 800cm -1 ~1800cm -1 , 5 points of the freshness intelligent indicator label were randomly collected, and the average value was taken as the response value of the SERS signal.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention adopts a reducing agent reduction method to prepare an Au@AgNPs solution containing gold nanoparticles uniformly coated with elemental silver on the surface. Anthocyanins in anthocyanin-rich plant materials are extracted by an alcohol method to obtain anthocyanin extract. The anthocyanin extract is used as a matrix to realize the sensitive response of anthocyanin color information and SESR signals, and Au@AgNPs are used as an SESR enhancement substrate for anthocyanins. The anthocyanin extract is concentrated and the pH is adjusted to acidic, and then mixed with the Au@AgNPs solution, so that anthocyanins can be uniformly adsorbed on the surface of Au@AgNPs in a solution environment, and then under the interaction between anthocyanins and Au@AgNPs, Au@AgNPs are further induced to aggregate, thereby generating a large number of SERS "hot spots" to significantly enhance the SERS signal of anthocyanins in the indicator label. The aggregated product is then cooled and solidified after being gelled with agar / polyvinyl alcohol, so as to obtain a dual-mode aquatic product freshness intelligent indicator label that can realize sensitive and accurate quantitative analysis of aquatic product freshness indicators. The preparation method of the invention is simple and easy to operate, does not require the use of complex instruments and equipment, has low material cost, does not require the use of a large amount of organic bases and organic solvents, is green and environmentally friendly, and is easy to prepare in large quantities.

[0044] The present invention introduces Au@AgNPs into the smart indicator label, which can not only enhance the Raman signal of anthocyanin, but also Au@AgNPs has a good antibacterial effect. Therefore, the smart indicator label prepared by the present invention has good antibacterial properties.

[0045] The dual-mode aquatic product freshness intelligent indicator label prepared by the present invention can, on the one hand, quickly and visually identify the freshness level of aquatic products according to the color change of the indicator label; on the other hand, by using the more sensitive SERS technology to detect the change of the Raman signal of the indicator label, it can identify the change of the early freshness of aquatic products and establish a connection with TVB-N to achieve sensitive and accurate quantitative analysis of the freshness index of aquatic products. Therefore, the present invention solves the problem that the traditional freshness intelligent indicator label has poor sensitivity and is difficult to accurately and quantitatively detect. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 SEM images of Au@AgNPs, Au@AgNPs / anthocyanidin aggregates, agar / polyvinyl alcohol gel, the label of Comparative Example 1, and the label of Example 1 in Example 1; Figure 1 In the figure, Figure A is a SEM image of Au@AgNPs, Figure B is a SEM image of Au@AgNPs / anthocyanin aggregates, Figure C is a SEM image of agar / polyvinyl alcohol gel, Figure D is a SEM image of the label of Comparative Example 1, Figure E is a SEM image of the label of Example 1 at a scale of 200 μm, and Figure F is a SEM image of the label of Example 1 at a scale of 2 μm.

[0047] Figure 2 The SERS signal response results of the tag in Example 1 to different pH buffers are shown in FIG. Figure 2 The illustration in FIG. 1 is the colorimetric response result of the label of Example 1 to buffer solutions of different pH values.

[0048] Figure 3 The colorimetric and SERS signal response results of the tag of Example 1 to different volatile gases are shown in FIG. Figure 3 In the figure, Figure A shows the SERS signal response result to ammonia, wherein the inset is the colorimetric response result to ammonia; Figure B shows the SERS signal response result to dimethylamine, wherein the inset is the colorimetric response result to dimethylamine; Figure C shows the SERS signal response result to trimethylamine, wherein the inset is the colorimetric response result to trimethylamine; Figure D shows the SERS signal response result to alcohols, hydrocarbons, aldehydes, and ester gases, wherein the inset is the colorimetric response result to alcohols, hydrocarbons, aldehydes, and ester gases.

[0049] Figure 4 The color changes of 20 random points on the label.

[0050] Figure 5 The SERS signal response changes of 20 random points on the tag.

[0051] Figure 6 The color change of the label of Example 1 after storage at 4°C for 18 days.

[0052] Figure 7 The SERS signal response change of the tag of Example 1 after being stored at 4° C. for 18 days.

[0053] Figure 8 The inhibitory effects of the label of Example 1 and the label of Comparative Example 1 on Escherichia coli and Salmonella are shown in FIG. Figure 8 In the figure, Figure A shows the inhibitory effect of the label on Escherichia coli, and Figure B shows the inhibitory effect of the label on Salmonella. In Figures A and B, 1 is the label with added Au@AgNPs / anthocyanin aggregates, and 2 is the label with only added anthocyanin.

[0054] Fig. 9 The color change of the label of Example 1 placed inside the package of Penaeus vannamei during storage at 4°C.

[0055] Fig.10 The TVB-N value changes inside the packaging of Penaeus vannamei during storage at 4°C.

[0056] Fig.11 The SERS signal response changes of the tag of Example 1 placed inside the package of Penaeus vannamei during storage at 4°C.

[0057] Fig.12 A partial least squares regression (PLSR) model was established between the SERS signal of the tag and TVB-N.

[0058] Fig.13 The test results of the effect of the pH value of anthocyanin concentrate on the detection performance of the smart indicator label are as follows; Fig.13 In the figure, Figure A is the SERS signal response result of Example 2, wherein the inset is the colorimetric response result of Example 2; Figure B is the SERS signal response result of Example 1, wherein the inset is the colorimetric response result of Example 1; Figure C is the SERS signal response result of Example 3, wherein the inset is the colorimetric response result of Example 3.

[0059] Fig.14 The test results show the effect of the amount of anthocyanin concentrate on the detection performance of the smart indicator label; Fig.14 In the figure, Figure A is the SERS signal response result of Example 4, wherein the inset is the colorimetric response result of Example 4; Figure B is the SERS signal response result of Example 5, wherein the inset is the colorimetric response result of Example 5; Figure C is the SERS signal response result of Example 1, wherein the inset is the colorimetric response result of Example 1; Figure D is the SERS signal response result of Example 6, wherein the inset is the colorimetric response result of Example 6.

[0060] Fig.15 The test results show the effect of the dosage of Au@AgNPs on the detection performance of the smart indicator label. Fig.15 In the figure, Figure A is the SERS signal response result of Example 7, wherein the inset is the colorimetric response result of Example 7; Figure B is the SERS signal response result of Example 1, wherein the inset is the colorimetric response result of Example 1; Figure C is the SERS signal response result of Example 8, wherein the inset is the colorimetric response result of Example 8; Figure D is the SERS signal response result of Example 9, wherein the inset is the colorimetric response result of Example 9. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present invention are described clearly and completely below. It should be noted that in the following embodiments of the present invention, the freshness of aquatic products is evaluated by the following steps:

[0062] 1) Establish an evaluation model: collect intelligent indicator tags 800~1800cm -1 The SERS signals in the range were collected by averaging 5 points for each tag and the Raman shift of 840 cm -1 The overall SERS spectrum of the tag is normalized by the Raman characteristic peak at , and a partial least squares regression PLSR prediction model is established between the SERS signal of the indicator tag and TVB-N;

[0063] 2) placing the dual-mode intelligent indicator label inside the package of the aquatic product to be tested and storing it at 0-37° C.;

[0064] 3) Detecting the colorimetric and SERS signals of the intelligent indicator tag, so as to qualitatively judge the freshness of the aquatic product to be tested through the change of the tag color response; and quantitatively judge the TVB-N value of the aquatic product to be tested through the change of the SERS signal response;

[0065] Among them, according to the change of label color response, the freshness of the aquatic product to be tested is qualitatively judged according to the following standards:

[0066] When the label color is purple or dark purple, the aquatic product to be tested is in the first-level freshness state;

[0067] When the label color turns dark blue, the aquatic product to be tested is in the second level of freshness;

[0068] When the label turns light blue, the aquatic product to be tested is completely spoiled;

[0069] According to the response value of the SERS signal, it is brought into the PLSR prediction model to obtain the corresponding TVB-N content. The freshness grade of aquatic products is evaluated based on the obtained TVB-N content:

[0070] When TVB-N < 20mgN / 100g, it is the first-level freshness;

[0071] When TVB-N is 20mgN / 100g~30mgN / 100g, it is the second level of freshness;

[0072] When TVB-N>30mgN / 100g, it is corrupt.

[0073] For ease of description, AuNPs is used to describe gold nanoparticles in the following embodiments of the present invention.

[0074] In the following embodiments of the present invention, the AuNPs used are prepared by the following steps: 1 mL of 1% HAuCl4·4H2O solution is mixed with 100 mL of ultrapure water, heated to boiling, and then 1.4 mL of 1% trisodium citrate aqueous solution is added while stirring. When the color of the solution changes to purple-red, heating and stirring are continued for 5 minutes, the reaction is terminated and cooled to room temperature to obtain colloidal AuNPs.

[0075] In the following embodiments of the present invention, the Au@AgNPs used are prepared by the following steps:

[0076] 3 mL of colloidal AuNPs was mixed with 60 μL of 1% sodium citrate trisodium aqueous solution and 125 μL of 10 mM ascorbic acid solution to obtain a mixed solution. 125 μL of 10 mM silver nitrate solution was added dropwise to the mixed solution at a rate of 13 μL / 30 s. After the addition was completed, the mixture was shaken at 1000 rpm for 45 min to obtain an Au@AgNPs solution.

[0077] Example 1

[0078] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0079] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2 After being formed into flakes, it was dried in an oven at 40°C. 60 g of the dried product was placed in 500 mL of 60% ethanol aqueous solution, stirred for 3 hours, and then filtered with Whatman filter paper to obtain anthocyanin extract; the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50 mL to obtain an anthocyanin solution. The obtained anthocyanin solution was adjusted to pH 6.0 with 1M hydrochloric acid, and then 0.4 mL of anthocyanin concentrate was mixed with 6 mL of Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0080] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0081] Example 2

[0082] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0083] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2After being formed into flakes, it was dried in an oven at 40°C. 60 g of the dried product was placed in 500 mL of 60% ethanol aqueous solution, stirred for 3 hours, and then filtered with Whatman filter paper to obtain anthocyanin extract; the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50 mL to obtain an anthocyanin solution. The obtained anthocyanin solution was adjusted to pH 5.0 with 1M hydrochloric acid, and then 0.4 mL of anthocyanin concentrate was mixed with 6 mL of Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0084] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0085] That is, the only difference between this embodiment and embodiment 1 is that the pH value of the anthocyanin concentrate in this embodiment is 5.

[0086] Example 3

[0087] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0088] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2 After being formed into flakes, it was dried in an oven at 40°C. 60 g of the dried product was placed in 500 mL of 60% ethanol aqueous solution, stirred for 3 hours, and then filtered with Whatman filter paper to obtain anthocyanin extract; the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50 mL to obtain an anthocyanin solution. The obtained anthocyanin solution was adjusted to pH 7.0 with 1M hydrochloric acid, and then 0.4 mL of anthocyanin concentrate was mixed with 6 mL of Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0089] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0090] That is, the only difference between this embodiment and embodiment 1 is that the pH value of the anthocyanin concentrate in this embodiment is 7.

[0091] Example 4

[0092] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0093] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2 After being formed into flakes, it was dried in an oven at 40°C. 60 g of the dried product was placed in 500 mL of 60% ethanol aqueous solution, stirred for 3 hours, and then filtered with Whatman filter paper to obtain anthocyanin extract; the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50 mL to obtain an anthocyanin solution. The obtained anthocyanin solution was adjusted to pH 6.0 with 1M hydrochloric acid, and then 0.2 mL of the anthocyanin concentrate was mixed with 6 mL of the Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0094] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0095] That is, the only difference between this embodiment and embodiment 1 is that the amount of anthocyanin concentrate used in this embodiment is 0.2 mL.

[0096] Example 5

[0097] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0098] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2 After being formed into flakes, it was dried in an oven at 40°C. 60g of the dried product was placed in 500mL of 60% ethanol aqueous solution to obtain anthocyanin extract; the anthocyanin extract was stirred for 3h, then filtered with Whatman filter paper to remove the filter residue, and the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50mL to obtain anthocyanin concentrate. The obtained anthocyanin concentrate was adjusted to pH 6.0 with 1M hydrochloric acid, and then 0.3mL of the anthocyanin concentrate was mixed with 6mL of Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0099] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0100] That is, the only difference between this embodiment and embodiment 1 is that the amount of anthocyanin concentrate used in this embodiment is 0.3 mL.

[0101] Example 6

[0102] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0103] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2 After being formed into flakes, it was dried in an oven at 40°C. 60g of the dried product was placed in 500mL of 60% ethanol aqueous solution to obtain anthocyanin extract; the anthocyanin extract was stirred for 3h, then filtered with Whatman filter paper to remove the filter residue, and the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50mL to obtain anthocyanin concentrate. The obtained anthocyanin concentrate was adjusted to pH 6.0 with 1M hydrochloric acid, and then 0.5mL of the anthocyanin concentrate was mixed with 6mL of Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0104] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0105] That is, the only difference between this embodiment and embodiment 1 is that the amount of anthocyanin concentrate used in this embodiment is 0.5 mL.

[0106] Example 7

[0107] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0108] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2 After being formed into flakes, it was dried in an oven at 40°C. 60g of the dried product was placed in 500mL of 60% ethanol aqueous solution to obtain anthocyanin extract; the anthocyanin extract was stirred for 3h, then filtered with Whatman filter paper to remove the filter residue, and the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50mL to obtain anthocyanin concentrate. The obtained anthocyanin concentrate was adjusted to pH 6.0 with 1M hydrochloric acid, and then 0.4mL of the anthocyanin concentrate was mixed with 3mL of Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0109] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0110] That is, the only difference between this embodiment and embodiment 1 is that the amount of Au@AgNPs solution used in this embodiment is 3 mL.

[0111] Example 8

[0112] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0113] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2 After being formed into flakes, it was dried in an oven at 40°C. 60 g of the dried product was placed in 500 mL of 60% ethanol aqueous solution to obtain anthocyanin extract; the anthocyanin extract was stirred for 3 hours, then filtered with Whatman filter paper to remove the filter residue, and the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50 mL to obtain anthocyanin concentrate. The obtained anthocyanin concentrate was adjusted to pH 6.0 with 1M hydrochloric acid, and then 0.4 mL of the anthocyanin concentrate was mixed with 9 mL of the Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0114] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0115] That is, the only difference between this embodiment and embodiment 1 is that the amount of Au@AgNPs solution used in this embodiment is 9 mL.

[0116] Example 9

[0117] This embodiment provides a dual-mode aquatic product freshness intelligent indicator label, and its preparation method is as follows:

[0118] Step 1, preparation of Au@AgNPs / anthocyanin aggregate solution: Take purple cabbage leaves and chop them into 9 cm 2 After being formed into flakes, it was dried in an oven at 40°C. 60 g of the dried product was placed in 500 mL of 60% ethanol aqueous solution to obtain anthocyanin extract; the anthocyanin extract was stirred for 3 hours, then filtered with Whatman filter paper to remove the filter residue, and the anthocyanin extract was rotary evaporated using a rotary evaporator to concentrate the anthocyanin extract to 50 mL to obtain anthocyanin concentrate. The obtained anthocyanin concentrate was adjusted to pH 6.0 with 1M hydrochloric acid, and then 0.4 mL of the anthocyanin concentrate was mixed with 12 mL of the Au@AgNPs solution to obtain an Au@AgNPs / anthocyanin aggregate solution.

[0119] Step 2, compounding with agar and polyvinyl alcohol: 0.8g agar and 0.2g polyvinyl alcohol are dispersed in 50mL ultrapure water, heated to boiling and stirred for 1h. After the stirring is completed, agar / polyvinyl alcohol gel is obtained. When the agar / polyvinyl alcohol gel is cooled to 50°C, the above Au@AgNPs / anthocyanidin aggregate solution is added and mixed. 2.5mL of the mixed solution is added to a culture dish with a diameter of 60mm. After the solution is cooled and solidified, it is cut into a circle with a diameter of 1cm to obtain a dual-mode aquatic product freshness intelligent indicator label.

[0120] That is, the only difference between this embodiment and embodiment 1 is that the amount of Au@AgNPs solution used in this embodiment is 12 mL.

[0121] Comparative Example 1

[0122] This comparative example provides an intelligent indicator label for freshness of aquatic products, and the only difference between this comparative example and Example 1 is that Au@AgNPs is not added in this comparative example.

[0123] Experimental Section

[0124] In the following experimental section, for the sake of ease of expression, "label" will be used instead of "dual-mode aquatic product freshness intelligent indication label" or "aquatic product freshness intelligent indication label".

[0125] (I) Microscopic morphology test

[0126] The present invention respectively carried out SEM tests on the Au@AgNPs, Au@AgNPs / anthocyanidin aggregates, agar / polyvinyl alcohol gel, the label of comparative example 1 and the label of example 1 prepared in Example 1, and the test results are as follows: Figure 1 shown. Figure 1 In the figure, Figure A is a SEM image of Au@AgNPs, Figure B is a SEM image of Au@AgNPs / anthocyanin aggregates, Figure C is a SEM image of agar / polyvinyl alcohol gel, Figure D is a SEM image of the label of Comparative Example 1, Figure E is a SEM image of the label of Example 1 at a scale of 200 μm, and Figure F is a SEM image of the label of Example 1 at a scale of 2 μm.

[0127] And by Figure 1 It can be seen that the particle size of Au@AgNPs is about 40nm. When Au@AgNPs and purple cabbage anthocyanins are evenly mixed, they aggregate to form Au@AgNPs / anthocyanin aggregates, which have a large number of SERS "hotspot" areas and can effectively detect the structural changes of anthocyanins under different pH environments. After the Au@AgNPs / anthocyanin aggregates are added to the agar / polyvinyl alcohol gel, the presence of Au@AgNPs / anthocyanin aggregates can be observed in the gel network structure.

[0128] (II) Effect of testing the freshness of aquatic products

[0129] 1) Colorimetric and SERS signal responses to different pH buffers

[0130] In order to explore the effect of different pH values ​​on the colorimetry and SERS signal response of the label, the present invention takes the label of Example 1 as an example and places it in buffer solutions with different pH values ​​of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12. A smartphone was used to take photos to record the color change. The photo parameters were focal length: 5.58 mm, aperture: F / 1.6, ISO: 50. A portable Raman spectrometer was used to detect the SERS signal response. The excitation wavelength was 785 nm, the laser power was 60 mW, and the integration time was 2000 ms. And the test results are as follows Figure 2 shown. Figure 2 The SERS signal response results of the tag of Example 1 to buffer solutions of different pH values, wherein the inset is the colorimetric response results of the tag of Example 1 to buffer solutions of different pH values.

[0131] Depend on Figure 2 As can be seen from the illustration, when the label of Example 1 is placed in buffer solutions with different pH values, the label shows different colors. In acidic conditions, the label of Example 1 is red, and as the pH increases, the label color gradually changes to purple, blue, and light green. It can also be seen that for the SERS signal of anthocyanin, as the pH increases, the color at 1287 cm -1 and 1642cm -1 The intensity of the Raman characteristic peak increased, located at 1320cm -1 The intensity of the Raman characteristic peaks decreased, and the significant changes in these Raman characteristic peaks indicated that the label of Example 1 can be used to monitor the structural transformation of anthocyanins under different pH environments.

[0132] 2) Colorimetric and SERS signal responses to different volatile gases.

[0133] In order to explore the colorimetric-SERS dual-mode response of the tag to volatile gases, ammonia, dimethylamine, trimethylamine, alcohols, hydrocarbons, aldehydes and esters were selected as characteristic detection gases. 50mL of a solution that can produce volatile gases was poured into a 100mL beaker, in which ammonia water, dimethylamine solution and trimethylamine solution were set to different concentration gradients, which were 0mM, 1mM, 2mM, 5mM, 10mM, 20mM, 40mM and 80mM respectively, and the alcohol, hydrocarbon, aldehyde and ester solutions were all 20mM. The tag of Example 1 was placed above the beaker, and the colorimetric and SERS signals of the tag were detected after 3 hours. And the test results are as follows Figure 3 shown.

[0134] Figure 3 In the figure, Figure A shows the SERS signal response results and colorimetric response results of the label to ammonia; Figure B shows the SERS signal response results and colorimetric response results of the label to dimethylamine; Figure C shows the SERS signal response results and colorimetric response results of the label to trimethylamine; Figure D shows the SERS signal response results and colorimetric response results of the label to alcohols, hydrocarbons, aldehydes, and ester gases.

[0135] Depend on Figure 3 It can be seen that the tag of Example 1 has significant colorimetric and SERS responses to alkaline gases such as ammonia, dimethylamine and trimethylamine. In terms of color change, the color of the tag changes from purple-red to blue-green, then to green, and finally to yellow-green. For SERS response, as the concentration of amine gas increases, anthocyanin increases at 1287 cm -1 and 1642cm -1 The Raman peak at 1320cm -1 The peak at gradually weakens. This is because alkaline gases such as ammonia and amines can change the pH value of the tag microenvironment, and the change in pH value leads to changes in the structure of anthocyanins, resulting in colorimetric and SERS responses.

[0136] And by Figure 3 It can also be seen that the tag of Example 1 has neither significant color response nor SERS signal response to gases such as alcohols, hydrocarbons, aldehydes, lipids, etc. Therefore, the tag prepared by the present invention has good specificity for the detection of alkaline gases.

[0137] 3) Uniformity of dual-mode smart indicator labels

[0138] In order to ensure the signal uniformity of the probe tag, the present invention samples the color parameters and SERS signals of 20 random points on the tag of Example 1, and respectively Figure 4 and Figure 5 As shown. The color difference value ΔE is used as the color parameter, ΔE is the color change of the label after the response relative to the initial label, and its calculation formula is shown as follows: Among them, L*, a* and b* are the brightness value, redness, greenness and yellowness, blueness value of the label respectively; L, a and b are the brightness value, redness, greenness and yellowness, blueness value of the initial label.

[0139] Figure 4 is the color change of 20 random points on the label, Figure 5 is the SERS signal response change of 20 random points on the tag. Figure 4 and Figure 5 It can be seen that the ΔE value of the label is <5, and anthocyanin is at 1287 cm -1 、1320cm -1 and 1642cm-1 The relative standard deviations of the Raman peaks at 3.07%, 4.15% and 2.48% were respectively, all less than 5%. This indicates that the colorimetric and SERS signals of different regions of the label prepared by the present invention are relatively consistent and have excellent uniformity.

[0140] 4) Stability of dual-mode smart indicator labels

[0141] In order to investigate the stability of the label, the label of Example 1 was stored at 4°C for 18 days. During the 18-day storage period, the color change of the label was recorded as follows: Figure 6 As shown, the SERS signal response change of the tag is recorded as Figure 7 shown.

[0142] Depend on Figure 6 It can be seen that during the 18-day storage period, the color of the label remained purple-red with no significant change. On the 18th day of storage, compared with the initially prepared label, the ΔE of the label was 3.66<5, indicating that the label had good color stability during storage.

[0143] Depend on Figure 7 It can be seen that anthocyanin is at 1287 cm -1 、1320cm -1 and 1642cm -1 The relative standard deviation of the Raman characteristic peak intensity at is less than 10%, which indicates that the label prepared by the present invention has good storage stability.

[0144] 5) Antibacterial properties of dual-mode smart indicator labels

[0145] In order to explore the antibacterial property of the label, the present invention takes the label of Example 1 and the label of Comparative Example 1 as examples to test the inhibitory effects on Escherichia coli and Salmonella respectively.

[0146] The test method is: the antibacterial activity of the gel indicator label against common bacteria: Escherichia coli (E. coli) and Salmonella (S. enterica) is determined by the antibacterial zone method. 5 CFU / mL of the above bacterial solution were inoculated on LB solid culture medium and evenly spread with a sterile coating rod. The label was sterilized under ultraviolet light and placed on the culture medium. The plate was incubated upside down in a 37°C incubator for 24 hours and the diameter of the inhibition zone was measured. The test results are as follows Figure 8 As shown, Figure 8 In the figure, Figure A shows the inhibitory effect of the label on Escherichia coli, and Figure B shows the inhibitory effect of the label on Salmonella. In Figures A and B, 1 is the label with added Au@AgNPs / anthocyanin aggregates, and 2 is the label with only added anthocyanin.

[0147] Depend on Figure 8It can be seen that the addition of Au@AgNPs to the label can further improve its antibacterial performance compared with the traditional freshness label without Au@AgNPs.

[0148] (III) Monitoring the freshness of Penaeus vannamei

[0149] The label of Example 1 was placed inside the package of white shrimp and stored at 4°C. The present invention records the color change of the label during storage as follows: Fig. 9 shown.

[0150] Depend on Fig. 9 It can be seen that during storage at 4°C, the label color changes from purple to dark purple, then to dark blue, and finally to light blue. When the label color is purple or dark purple, the white shrimp is in the first freshness state. When the label color changes to dark blue, the white shrimp is in the second freshness state. When the label changes to light blue, the white shrimp is completely corrupted.

[0151] The present invention also tests the TVB-N value inside the packaging of white shrimp during storage, and the test results are as follows: Fig.10 As shown, it can be seen that with the increase of storage time, the TVB-N value of the whiteleg shrimp shows an upward trend, and within the 5th to 6th day of storage, its TVB-N value is >30mgN / 100g, which meets the above-mentioned evaluation standard of the present invention, indicating that the whiteleg shrimp is completely corrupted at this time.

[0152] The freshness obtained according to the evaluation criteria of the present invention is consistent with the actual situation, that is, the changes in the color response of the label according to the present invention and the SERS signal response value can both be used to qualitatively judge the freshness of the white shrimp, indicating that the label prepared by the present invention has a dual-mode indication function.

[0153] The present invention also provides a method for storing the label at 800 cm -1 ~1800cm -1 The SERS signal in the range is detected, and the test results are as follows Fig.11 As shown. Fig.11 It can be seen that with the increase of storage time of white shrimp, 1287cm -1 and 1642cm -1 The peak at 1320cm -1 The peak at gradually decreases.

[0154] The present invention also establishes a PLSR prediction model by the following method: collecting tags 800cm -1 ~1800cm -1 The SERS signals in the range were collected by averaging 5 points for each tag and the Raman shift of 840 cm-1 The overall SERS spectrum of the tag is normalized by the Raman characteristic peak at , and a partial least squares regression PLSR model is established between the SERS signal of the tag and TVB-N. The model is as follows Fig.12 shown.

[0155] like Fig.12 As shown in Table 1, the present invention also establishes PLSR and principal component regression PCR models with different pretreatment methods. Among them, all modeling in the present invention uses The UnscramblerX 10.4 software, firstly using the software to perform different pretreatments on the data, and then establishing different quantitative models with the obtained pretreated data, and selecting the optimal pretreatment method and model type according to the model establishment effect and prediction effect.

[0156] Depend on Fig.12 As can be seen from Table 1, in comparison, the PLSR prediction model after SNV preprocessing showed good prediction performance, with R 2 C =0.949, R 2 CV =0.906, R 2 P =0.975, which proves that the PLSR prediction model has good prediction stability. Therefore, in addition to using the color of the label to semi-quantitatively evaluate the freshness of white shrimp, the SERS signal can be further used to predict the TVB-N content of white shrimp during storage. Compared with the traditional colorimetric freshness indicator label, the colorimetric-SERS dual-mode label developed in the present invention provides a more sensitive and accurate method for determining the freshness of aquatic products.

[0157] Table 1 Prediction results of TVB-N content of white shrimp by different prediction models

[0158]

[0159]

[0160] PLSR: partial least squares regression; PCR: principal component regression; Nor: no pretreatment; SNV: standard normal variate variation; MSC: multivariate scatter correction; R 2 C : Calibration set correlation coefficient; RMSEC calibration set root mean square error; R 2 CV : Cross-validation set correlation coefficient; RMSECV: Cross-validation set root mean square error; R 2 P : prediction set correlation coefficient; RMSEP: prediction set root mean square error; RPD: residual prediction deviation.

[0161] (IV) Effect of pH value of anthocyanin concentrate on the detection performance of smart indicator labels

[0162] In order to explore the effect of anthocyanin concentrates of different pH values ​​on the detection performance of the tag, the present invention takes the tags of Examples 1 to 3 as examples, and uses them to monitor the freshness of white shrimp stored at 4°C, and detects the colorimetric and SERS signals of the tags during the storage of white shrimp for 0 to 5 days. The detection results are as follows: Fig.13 shown. Fig.13 In the figure, Figure A shows the SERS signal response result and the colorimetric response result of Example 2; Figure B shows the SERS signal response result and the colorimetric response result of Example 1; and Figure C shows the SERS signal response result and the colorimetric response result of Example 3.

[0163] Depend on Fig.13 It can be seen that when the anthocyanin concentrate is adjusted to pH 5 and pH 7, the tag will also respond to colorimetry and SERS signals during monitoring of white shrimp. When the pH is 6, the colorimetry and SERS signal responses are more sensitive.

[0164] (V) Effect of anthocyanin concentrate dosage on the detection performance of smart indicator labels

[0165] In order to explore the effect of the amount of anthocyanin concentrate on the detection performance of the label, the present invention takes the labels of Example 1, Example 4-Example 6 as examples, and uses them to monitor the freshness of white shrimp under 4°C storage conditions, and detects the colorimetric and SERS signals of the labels during the storage of white shrimp for 0 to 5 days. The detection results are as follows: Fig.14 shown. Fig.14 In the figure, Figure A shows the SERS signal response results and colorimetric response results of Example 4; Figure B shows the SERS signal response results and colorimetric response results of Example 5; Figure C shows the SERS signal response results and colorimetric response results of Example 1; and Figure D shows the SERS signal response results and colorimetric response results of Example 6.

[0166] Depend on Fig.14 It can be seen that when the anthocyanin concentrate is 0.2mL, 0.3mL, 0.4mL and 0.5mL, the tag will also respond to colorimetry and SERS signals during monitoring of white shrimp. However, when the addition amount is 0.4mL, the colorimetry and SERS signal responses are more sensitive.

[0167] (VI) Effect of the dosage of Au@AgNPs on the detection performance of smart indicator tags

[0168] In order to explore the effect of the amount of anthocyanin concentrate on the detection performance of the label, the present invention takes the labels of Example 1, Example 7-Example 12 as examples, and uses them to monitor the freshness of white shrimp under 4°C storage conditions, and detects the colorimetric and SERS signals of the labels during the storage of white shrimp for 0 to 5 days. The detection results are as follows: Fig.15 shown. Fig.15 In the figure, Figure A shows the SERS signal response results and colorimetric response results of Example 7; Figure B shows the SERS signal response results and colorimetric response results of Example 1; Figure C shows the SERS signal response results and colorimetric response results of Example 8; and Figure D shows the SERS signal response results and colorimetric response results of Example 9.

[0169] Depend on Fig.15 It can be seen that when the volume of Au@AgNPs solution is 3mL, 6mL, 9mL and 12mL, the tag will also respond to colorimetry and SERS signals during monitoring of white shrimp. However, when the addition amount is 6mL, the colorimetry and SERS signal responses are more sensitive.

[0170] In summary, the dual-mode aquatic product freshness intelligent indicator label, preparation method and application of the present invention utilize the alkaline gas generated by aquatic products during the spoilage process to induce the pH-responsive anthocyanin structure inside the intelligent indicator label to change.

[0171] Obviously, the above embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Claims

1. A method for preparing a dual-mode aquatic product freshness intelligent indicator label, characterized in that: The following steps are involved: A gold core-silver shell nanoparticle solution is prepared by a reducing agent reduction method; wherein the reducing agent is one or more of trisodium citrate and ascorbic acid; Anthocyanins in anthocyanin-rich plant materials are extracted by an alcohol method using an alcohol solution as an extraction solvent to obtain anthocyanin extract; the anthocyanin extract is concentrated to 1 / 11 to 1 / 9 of the original volume to obtain anthocyanin concentrated solution; the pH of the anthocyanin concentrated solution is adjusted to acidic, and then mixed with the gold core-silver shell nanoparticle solution to allow anthocyanins to be adsorbed on the surface of the gold core-silver shell nanoparticles and induce aggregation between the gold core-silver shell nanoparticles to obtain a gold core-silver shell nanoparticle / anthocyanin aggregate solution; Agar and polyvinyl alcohol are dispersed in water, heated to boiling and then stirred, and then cooled to 45°C to 50°C to obtain an agar / polyvinyl alcohol gel; the gold core-silver shell nanoparticle / anthocyanin aggregate solution is added to the agar / polyvinyl alcohol gel and mixed, and after cooling and solidification, the dual-mode aquatic product freshness intelligent indicator label is obtained.

2. The preparation method according to claim 1, characterized in that The volume ratio of the anthocyanin concentrate to the gold core-silver shell nanoparticle solution is 0.2-0.5:3-12.

3. The preparation method according to claim 1, characterized in that: The mass ratio of agar to polyvinyl alcohol is 4:1-3; The dosage ratio of the gold core-silver shell nanoparticle / anthocyanin aggregate solution to agar is 3.4 mL to 12.4 mL: 0.8 g.

4. The preparation method according to claim 1, characterized in that: When anthocyanins are extracted from anthocyanin-rich plant materials by alcohol method, the solid-liquid ratio is 50g-80g:500mL; The alcohol solution is an ethanol aqueous solution with a volume fraction of 55% to 65%.

5. The preparation method according to claim 1, characterized in that: The gold core-silver shell nanoparticle solution is prepared by the following steps: Colloidal gold nanoparticles were prepared by trisodium citrate reduction method; Dispersing the reducing agent in water to form a reducing agent aqueous solution, dispersing the colloidal gold nanoparticles in the reducing agent aqueous solution to obtain a mixed solution; The silver salt solution is added dropwise to the mixed solution and shaken to reduce the silver ions provided by the silver salt solution to elemental silver by the reducing agent in the reducing agent aqueous solution and form a silver layer on the surface of the gold nanoparticles to obtain a gold core-silver shell nanoparticle solution.

6. The preparation method according to claim 5, characterized in that: The molar ratio of the reducing agent in the reducing agent aqueous solution to the silver salt in the silver salt solution is 1:0.8-1.

7. The preparation method according to claim 5, characterized in that: The volume ratio of the colloidal gold nanoparticles to the silver salt solution is 3 mL:60 μL to 180 μL; The concentration of the silver salt in the silver salt solution is 8 mM to 12 mM.

8. A dual-mode aquatic product freshness intelligent indicator label prepared by the preparation method according to any one of claims 1 to 7.

9. Use of the dual-mode aquatic product freshness intelligent indicator label according to claim 8 in reflecting the freshness of food.

10. The use according to claim 9, characterized in that The freshness of aquatic products can be evaluated through the following steps: 1) Establish an evaluation model: Collect intelligent indicator tags 800~1800cm -1 The SERS signals in the range were collected by averaging 5 points for each tag and the Raman shift of 840 cm -1 The overall SERS spectrum of the tag is normalized by the Raman characteristic peak at , and a partial least squares regression PLSR prediction model is established between the SERS signal of the indicator tag and TVB-N; 2) placing the dual-mode intelligent indicator label inside the package of the aquatic product to be tested and storing it at 0-37° C.; 3) Detecting the colorimetric and SERS signals of the intelligent indicator tag, so as to qualitatively judge the freshness of the aquatic product to be tested through the change of the tag color response; and quantitatively judge the TVB-N value of the aquatic product to be tested through the change of the SERS signal response; Among them, according to the change of label color response, the freshness of the aquatic product to be tested is qualitatively judged according to the following standards: When the label color is purple or dark purple, the aquatic product to be tested is in the first-level freshness state; When the label color turns dark blue, the aquatic product to be tested is in the second level of freshness; When the label turns light blue, the aquatic product to be tested is completely spoiled; According to the response value of the SERS signal, it is brought into the PLSR prediction model to obtain the corresponding TVB-N content. The freshness grade of aquatic products is evaluated based on the obtained TVB-N content: When TVB-N < 20mgN / 100g, it is the first-level freshness; When TVB-N is 20mgN / 100g~30mgN / 100g, it is the second level of freshness; When TVB-N>30mgN / 100g, it is corrupt.

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