A method for detecting shellfish toxins based on transition metal oxide / noble metal particle composite SERS substrate

Abstract

The present application belongs to the technical field of toxin detection, and particularly relates to a method for detecting shellfish toxin based on transition metal oxide / gold particle composite SERS substrate; paralytic shellfish poison, i.e. saxitoxin, in the shellfish toxin is selected as a detection object; the specific steps are as follows: firstly, a zinc oxide-silver composite nanoparticle SERS substrate is prepared to enhance the Raman signal of saxitoxin; then, SERS spectra of saxitoxin with different concentrations are collected; the collected spectra are introduced into matlab to establish a prediction model by using a PLS algorithm; an actual sample is treated according to a national standard method to obtain a treatment liquid; then, the SERS spectrum of the treatment liquid is collected and introduced into the prediction model to obtain a prediction result; the present application has the advantages of simple synthesis steps, good SERS enhancement effect, fast detection speed, high stability, and good application prospect in the technical field of harmful factor detection in food and the like.

Description

Technical Field

[0001] The present application relates to the technical field of marine toxin detection, and specifically to a method for detecting shellfish toxins based on a transition metal oxide / noble metal particle composite SERS substrate. Background Art

[0002] Shellfish are a major aquaculture species in my country, with an annual production exceeding 15 million tons, primarily including oysters, abalone, snails, and mussels. Shellfish farming is primarily concentrated in Shandong, Fujian, Liaoning, and Guangdong. Fujian Province produces over 3 million tons annually, accounting for over 20% of the national total. This large-scale aquaculture is primarily driven by market demand for shellfish. Shellfish have a comprehensive amino acid profile, providing essential amino acids such as valine and leucine, and are low in fat, making them a crucial component of the consumer diet. Shellfish filter algae, but toxin-producing algae, such as Alexandrium and dinoflagellates, are particularly susceptible to these algae. Ingestion of these toxin-producing algae directly leads to the accumulation of algal toxins in the shellfish, forming shellfish toxins. Toxins harmful to humans include paralytic shellfish toxins, diarrheic shellfish toxins, amnesic shellfish toxins, and neurotoxic shellfish toxins, all of which have varying degrees of harm to the human body. Therefore, effective monitoring of shellfish toxins is of great significance to protecting consumer health and the healthy development of my country's shellfish aquaculture industry.

[0003] To detect shellfish toxins, China has issued national standards that strictly limit the toxin content in common shellfish and prescribe specific detection methods. Conventional methods for detecting shellfish toxins include mouse bioassays, high-performance liquid chromatography, immunoassays, and cell-based assays. While these techniques can accurately detect shellfish toxins, they are subject to high operational requirements, slow detection speeds, and high costs, making them infeasible for rapid, on-site testing. The convergence of information and nanotechnology with spectroscopy has led to the widespread application of spectroscopy in the detection of trace contaminants in food. Surface-enhanced Raman spectroscopy (SERS), in particular, offers advantages in high sensitivity and rapid detection for trace organic biotoxins due to its signal amplification effect via plasmon resonance (SPR). It has been applied to okadaic acid, carnitine, pesticide residues, and heavy metal residues. SERS spectral data often contain thousands of variables. Using chemometric models to intelligently filter and regress SERS spectral data can effectively improve the reliability and scalability of detection results. Summary of the Invention

[0004] The present invention addresses the problems of complex modification of commonly used SERS substrates, which weaken the signal over large distances and are difficult to apply due to the complexity of substrate preparation. A transition metal oxide / noble metal particle composite SERS substrate is prepared to collect spectra of saxitoxin, a shellfish toxin. The collected SERS spectra are then processed and a quantitative model is established using chemometrics, successfully achieving rapid detection of saxitoxin in shellfish toxins. Chemometrics employs the partial least squares (PLS) method.

[0005] To achieve the above-mentioned purpose, the present invention adopts the following technical solutions:

[0006] A method for detecting shellfish toxins based on a transition metal oxide / noble metal particle composite SERS substrate comprises the following steps:

[0007] (1) Preparation of zinc oxide nanoparticles (ZnO NPs): ZnONPs particles were prepared using a classic two-step wet chemical reaction method; the operation steps are as follows:

[0008] Zinc nitrate hexahydrate (Zn(NO3)2·6H20) was dissolved in ultrapure water to obtain a zinc nitrate hexahydrate solution; ammonia water (NH3·H2O) was added and the mixture was stirred continuously. After stirring, the precipitate was collected by centrifugation and then washed with anhydrous ethanol. After washing, the precipitate was collected by centrifugation again and vacuum dried to obtain zinc oxide nanoparticles, which were recorded as ZnO NPs.

[0009] (2) Preparation of zinc oxide nanoparticles / silver nanoparticles (ZnO@Ag): The ZnO NPs prepared in step (1) were used as a carrier to grow and load silver nanoparticles (Ag NPs);

[0010] First, ZnO NPs, polyvinylpyrrolidone K30 (PVP K30), and glucose were dissolved in ultrapure water, heated to a certain temperature, and stirred. Silver nitrate solution (AgNO3) was added under stirring conditions. After continued stirring, the mixture was centrifuged, washed, and dried to obtain zinc oxide nanoparticles / silver nanoparticles, which were recorded as ZnO@Ag.

[0011] (3) Preparation of saxitoxin standard solution: saxitoxin powder was dissolved in methanol solution to obtain saxitoxin standard solution with a concentration of 0.001-1000 ng / mL;

[0012] (4) Collection of SERS spectra of saxitoxin in shellfish:

[0013] The ZnO@Ag prepared in step (2) was dissolved in ethanol, and a ZnO@Ag solution was obtained after ultrasonic dispersion, which was evenly dropped on the surface of a silicon wafer. After drying, the saxitoxin standard solution prepared in step (3) was evenly dropped on the surface of a silicon wafer. The laser wavelength, spectral integration time, number of spectral repetitions, light source power, and scanning wavenumber range were set to collect SERS spectra and obtain SERS spectral data corresponding to saxitoxin standard solutions of different concentrations.

[0014] (5) Establishment of a quantitative prediction model: Based on the SERS spectral data of the saxitoxin standard solution of corresponding concentration collected in step (4), a quantitative model is established using the PLS algorithm to finally obtain a quantitative prediction model;

[0015] (6) Application of actual samples: After processing shellfish samples, obtain the treated liquid, repeat the operation in step (4), except that the saxitoxin standard solution is replaced by the treated liquid, and finally obtain the SERS spectrum; then input the obtained SERS spectrum into the quantitative prediction model established in step (5) to obtain the prediction result, thereby realizing the detection of saxitoxin in shellfish samples.

[0016] Preferably, the concentration of the Zn(NO3)2·6H2O solution in step (1) is 0.004-0.01 g / mL, the concentration of the NH3·H2O is 28 wt %; and the volume ratio of the Zn(NO3)2·6H2O solution to NH3·H2O is 125:1.

[0017] Preferably, the stirring reaction temperature in step (1) is 40°C and the rotation speed is 200 rpm; the stirring reaction time is 12-24 hours; the centrifugation conditions are 8000 rpm and centrifugation for 15 minutes; the vacuum drying temperature is 60°C and the time is 12 hours.

[0018] Preferably, the concentration range of the silver nitrate solution (AgNO3) in step (2) is 0.1 to 0.5 mol / L, and the amount of ZnONPs, polyvinyl pyrrolidone K30 (PVP K30) and glucose dissolved in ultrapure water and silver nitrate solution is 0.5 g: 2.5 g: 2 g: 50 mL: 1-5 mL; the stirring time after adding the silver nitrate solution is 0.5 to 2 h, and the temperature is 80°C.

[0019] Preferably, the drying temperature in step (2) is 60° C. and the drying time is 6 hours.

[0020] Preferably, the laser wavelength in step (4) is 785 nm; the spectrum integration time is 3 s, the spectrum is collected 3 times, the light source power is 150 mw, and the scanning beam range is 400 to 3000 cm -1 .

[0021] Preferably, the treatment in step (6) is carried out in accordance with the national standard GB 5009.213-2016 to obtain a treated liquid.

[0022] Compared with the prior art, the advantages of the present invention are:

[0023] (1) The transition metal oxide / noble metal particle composite SERS substrate prepared by the present invention can still provide stable enhancement for the SERS signal of shellfish toxins without complex modification, thanks to the special three-dimensional structure of its composite nanoparticles that can provide a large number of "Raman hotspots".

[0024] (2) The present invention adopts the PLS algorithm to establish the quantitative model, the model effect is good, and the prediction results are stable.

[0025] (3) The detection method prepared by the present invention has been successfully applied to the rapid detection of saxitoxin among shellfish toxins, and is also applicable to other shellfish toxins. It has fast detection speed, good sensitivity, high stability, and a wide detection range. It has good application prospects in the field of food testing and has the potential for on-site rapid detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 TEM image of ZnO@Ag NPs.

[0027] Figure 2 The collected SERS spectrum data diagram.

[0028] Figure 3 This is a diagram of the training and prediction effects of the PLS model obtained in Example 1. DETAILED DESCRIPTION

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the following will be clearly described in conjunction with the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0030] Example 1:

[0031] (1) Preparation of ZnO NPs: ZnO NPs were prepared using a classic two-step wet chemical reaction method;

[0032] Zinc nitrate hexahydrate (Zn(NO3)2·6H2O) was dissolved in ultrapure water to obtain a zinc nitrate hexahydrate solution with a concentration of 0.005 g / mL; 125 mL of the zinc nitrate hexahydrate solution was added with 1 mL of 28 wt% NH3·H2O solution and the mixture was stirred at 40°C for 24 hours. After the reaction, a white turbid liquid was obtained, which was cooled to room temperature and then centrifuged at 8000 rpm for 15 minutes. The supernatant was discarded and the white precipitate was collected. The white precipitate was washed with anhydrous ethanol and centrifuged again at 8000 rpm for 15 minutes. The white precipitate was washed with ultrapure water and centrifuged to collect the resulting ZnO NPs. The precipitate was dried at 60°C for 12 hours to finally obtain white ZnO NPs powder.

[0033] (2) Preparation of ZnO@Ag NPs:

[0034] Take 0.5g of ZnO NPs, 2.5g of PVP K30 and 2g of glucose and dissolve them together in 50mL of ultrapure water. Then, 5mL of 0.5mol / L AgNO3 solution was quickly injected into the above mixed solution and stirred continuously at 80℃ for 1h. The resulting solution was centrifuged and washed 3 times, and then dried under vacuum conditions at 60℃ for 6h to obtain ZnO@Ag NPs.

[0035] Figure 1 TEM image of the prepared ZnO@Ag NPs substrate. It can be seen that the composite substrate is nanoflower-shaped, and AgNPs are successfully loaded on the surface of ZnO NPs.

[0036] (3) Preparation of saxitoxin standard solution: saxitoxin powder was dissolved in methanol solution to obtain saxitoxin standard solution; the concentrations were 1000, 100, 10, 1, 0.1, 0.01, and 0.001 ng / mL, respectively, and set aside;

[0037] (4) SERS spectrum acquisition: 0.25 g of the prepared ZnO@Ag powder was dissolved in 5 mL of ethanol, ultrasonically dispersed, and evenly dropped on the surface of the silicon wafer and dried. Then, saxitoxin standard solution was evenly dropped on the surface of the silicon wafer. The laser wavelength was set to 785 nm, the integration time was set to 3 s, the spectrum was repeatedly collected 3 times, the light source power was set to 150 mW, and the scanning beam range was set to 400-3000 cm -1 , collect SERS spectra;

[0038] Seven concentrations, ten replicates for each concentration, 7 sets of data were measured, and 70 SERS spectra of toxins at different concentrations were obtained. The results are as follows Figure 2 As shown;

[0039] (5) Establishment of prediction model:

[0040] The collected SERS spectral data were imported into Matlab, and then the PLS algorithm was run to screen the variables of the SERS spectrum. The selected variable combination was used to establish the model, and finally a quantitative prediction model was obtained.

[0041] (6) Application of actual samples: Take shellfish samples and pre-treat them according to the national standard method (GB 5009.213-2016) to obtain a treatment solution. Repeat the operation in step (4), except that the saxitoxin standard solution is replaced by the treatment solution, and finally obtain a SERS spectrum; then input the obtained SERS spectrum into the quantitative prediction model established in step (5) to obtain the prediction result.

[0042] Figure 3 The results show that the fitting relationship between the actual value and the predicted value of the toxin concentration in the established prediction model is good and accurate, and it can be used to detect shellfish toxins in real samples.

[0043] Example 2:

[0044] (1) Preparation of ZnO NPs: ZnO NPs were prepared using a classic two-step wet chemical reaction method;

[0045] Zinc nitrate hexahydrate (Zn(NO3)2·6H2O) was dissolved in ultrapure water to obtain a zinc nitrate hexahydrate solution with a concentration of 0.006 g / mL; 125 mL of the zinc nitrate hexahydrate solution was added with 1 mL of 28 wt% NH3·H2O solution and the mixture was stirred at 40°C for 24 hours. After the reaction, a white turbid liquid was obtained, which was cooled to room temperature and then centrifuged at 8000 rpm for 15 minutes. The supernatant was discarded and the white precipitate was collected. The white precipitate was washed with anhydrous ethanol and centrifuged again at 8000 rpm for 15 minutes. The white precipitate was washed with ultrapure water and centrifuged to collect the resulting ZnO NPs. The precipitate was dried at 60°C for 12 hours to finally obtain white ZnO NPs powder.

[0046] (2) Preparation of ZnO@Ag NPs:

[0047] Take 0.5g of ZnO NPs, 2.5g of PVP K30 and 2g of glucose and dissolve them together in 50mL of ultrapure water. Then, 5mL of 0.3mol / L AgNO3 solution was quickly injected into the above mixed solution and stirred continuously at 80℃ for 1h. The resulting solution was centrifuged and washed 3 times, and then dried under vacuum conditions at 60℃ for 6h to obtain ZnO@Ag NPs.

[0048] (3) Preparation of saxitoxin standard solution: dissolve saxitoxin powder in methanol solution to obtain saxitoxin standard solution; the concentrations are 1000, 100, 10, 1, 0.1, 0.01, 0.001 ng / mL, respectively, and are ready for use;

[0049] (4) Collection of SERS spectrum: dissolve 0.25 g of prepared ZnO@Ag powder in 5 mL of ethanol, uniformly drop on the surface of silicon wafer after ultrasonic dispersion, and dry; then take the saxitoxin standard solution and uniformly drop it on the surface of silicon wafer, set the laser wavelength to 785 nm, the integral time to 3 s, the spectrum repetition collection times to 3 times, the light source power to 150 mw, and the scanning beam range to 400-3000 cm -1 , collect SERS spectrum; seven concentrations, fifteen parallel for each concentration, measure 7 groups of data, and correspondingly obtain 105 SERS spectrum graphs of different concentrations of toxins.

[0050] (5) Establishment of prediction model:

[0051] Import the above collected SERS spectrum data into matlab, then run PLS algorithm, use PLS algorithm to perform variable screening on SERS spectrum, and select the variable combination for model establishment, finally obtain the quantitative prediction model.

[0052] (6) Application of actual sample: take the shellfish sample, pretreat it according to the national standard method (GB 5009.213-2016) to obtain the treatment liquid, repeat the operation in step (4), the only difference is that the saxitoxin standard solution is replaced by the treatment liquid, and finally the SERS spectrum is obtained; then input the obtained SERS spectrum into the quantitative prediction model established in step (5) to obtain the prediction result.

[0053] Example 3:

[0054] (1) Preparation of ZnO NPs: ZnO NPs were prepared by the classical two-step wet chemical reaction method;

[0055] Zinc nitrate hexahydrate (Zn(NO3)2·6H2O) was dissolved in ultrapure water to obtain a zinc nitrate hexahydrate solution with a concentration of 0.01 g / mL; 125 mL of the zinc nitrate hexahydrate solution was added with 1 mL of an NH3·H2O solution with a concentration of 28 wt%, and then continuously stirred at 40°C for 24 h; after the reaction, a white turbid liquid was obtained, which was cooled to room temperature, then centrifuged at a speed of 8000 rpm for 15 min, and the supernatant was discarded; the white precipitate was washed with anhydrous ethanol, then centrifuged again at a speed of 8000 rpm for 15 min, and then washed with ultrapure water and collected; the white precipitate obtained after centrifugation was ZnO NPs, which were dried at 60°C for 12 h to obtain white ZnO NPs powder.

[0056] (2) Preparation of ZnO@Ag NPs:

[0057] ZnO NPs 0.5 g, PVP K30 2.5 g and glucose 2 g were dissolved in 50 mL of ultrapure water, and then 4 mL of 0.5 mol / L AgNO3 solution was quickly injected into the above mixed solution; the obtained solution was continuously stirred at 80°C for 1 h, then centrifuged and washed 3 times, and then dried at 60°C under vacuum for 6 h to obtain ZnO@Ag NPs.

[0058] (3) Preparation of saxitoxin standard solution: Saxitoxin powder was dissolved in methanol solution to obtain a saxitoxin standard solution; the concentrations were 1000, 100, 10, 1, 0.1, 0.01 and 0.001 ng / mL, respectively, and were ready for use;

[0059] (4) Collection of SERS spectra: 0.25 g of the prepared ZnO@Ag powder was dissolved in 5 mL of ethanol, ultrasonically dispersed, and then uniformly dropped on the surface of a silicon wafer and dried; then the saxitoxin standard solution was uniformly dropped on the surface of the silicon wafer, and the laser wavelength was set to 785 nm, the integration time was set to 3 s, the spectral repetition collection times were set to 3 times, the light source power was set to 150 mw, and the scanning beam range was set to 400-3000 cm -1 ; the SERS spectra were collected; seven concentrations, twenty parallel samples for each concentration, seven groups of data were measured, and 140 SERS spectra of different concentrations of toxins were obtained;

[0060] (5) Establishment of prediction model:

[0061] The collected SERS spectral data were imported into matlab, and then the PLS algorithm was run to perform variable screening on the SERS spectra; the selected variable combination was used for model establishment, and finally a quantitative prediction model was obtained.

[0062] (6) Application of actual samples:

[0063] A shellfish sample was pretreated according to the national standard method (GB 5009.213-2016) to obtain a treatment solution, and the operation in step (4) was repeated, except that the saxitoxin standard solution was replaced by the treatment solution, and finally a SERS spectrum was obtained; the obtained SERS spectrum was then input into the quantitative prediction model established in step (5) to obtain a prediction result.

[0064] Note: The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described in the present invention. Therefore, although this specification has described the present invention in detail with reference to the above embodiments, it should be understood by those skilled in the art that the present invention may still be modified or replaced by equivalents. All technical solutions and improvements that do not depart from the spirit and scope of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for detecting shellfish toxins based on a transition metal oxide / noble metal particle composite SERS substrate, characterized in that: Here are the steps: (1) Preparation of zinc oxide nanoparticles: Dissolving zinc nitrate hexahydrate in ultrapure water to obtain a zinc nitrate hexahydrate solution; then adding ammonia water and stirring the mixture continuously; collecting the precipitate by centrifugation after stirring the mixture; then washing the precipitate with anhydrous ethanol; and then centrifuging the precipitate again after washing. After vacuum drying, zinc oxide nanoparticles (ZnO NPs) are obtained; wherein the concentration of the zinc nitrate hexahydrate solution is 0.004 to 0.01 g / mL, and the volume ratio of the zinc nitrate hexahydrate solution to the ammonia water is 125:1; (2) First, the ZnO NPs, polyvinyl pyrrolidone K30 and glucose obtained in step (1) are dissolved in ultrapure water, heated and stirred, and a silver nitrate solution is added under stirring conditions. After stirring for 0.5 to 2 hours, the mixture is centrifuged, washed and dried to obtain zinc oxide nanoparticles / silver nanoparticles, which are recorded as ZnO@Ag; the concentration range of the silver nitrate solution is 0.1 to 0.5 mol / L, and the amount of ZnO NPs, polyvinyl pyrrolidone K30 and glucose dissolved in ultrapure water and the silver nitrate solution is 0.5 g: 2.5 g: 2 g: 50 mL: 1-5 mL; (3) Preparation of saxitoxin standard solution: saxitoxin powder was dissolved in methanol solution to obtain saxitoxin standard solution with a concentration of 0.001-1000 ng / mL; (4) Collection of SERS spectra of saxitoxin in shellfish: The ZnO@Ag prepared in step (2) is dissolved in ethanol, and a ZnO@Ag solution is obtained after ultrasonic dispersion, which is evenly dropped on the surface of a silicon wafer. After drying, the saxitoxin standard solution prepared in step (3) is evenly dropped on the surface of a silicon wafer. Then, the laser wavelength, spectral integration time, number of spectral repeated acquisitions, light source power, and scanning wavenumber range are set to collect SERS spectra and obtain SERS spectral data corresponding to saxitoxin standard solutions of different concentrations. (5) Establishment of a quantitative prediction model: Based on the SERS spectral data of the saxitoxin standard solution of corresponding concentration collected in step (4), a quantitative model is established using the PLS algorithm, and finally a quantitative prediction model is obtained; (6) Application of actual samples: Take shellfish samples and obtain the treated liquid after treatment. Repeat the operation in step (4), except that the saxitoxin standard solution is replaced by the treated liquid, and finally obtain the SERS spectrum; then input the obtained SERS spectrum into the quantitative prediction model established in step (5) to obtain the prediction result, thereby realizing the detection of saxitoxin in shellfish samples.

2. The method for detecting shellfish toxins based on a transition metal oxide / noble metal particle composite SERS substrate according to claim 1, characterized in that: The concentration of the ammonia water in step (1) is 28 wt %.

3. The method for detecting shellfish toxins based on a transition metal oxide / noble metal particle composite SERS substrate according to claim 1, characterized in that: In step (1), the stirring reaction temperature is 40°C and the rotation speed is 200 rpm; the stirring reaction time is 12-24 hours; the centrifugation conditions are all 8000 rpm and centrifugation for 15 minutes; the vacuum drying temperature is 60°C and the time is 12 hours.

4. The method for detecting shellfish toxins based on a transition metal oxide / noble metal particle composite SERS substrate according to claim 1, characterized in that: The temperature of heating and stirring in step (2) is 80°C.

5. The method for detecting shellfish toxins based on a transition metal oxide / noble metal particle composite SERS substrate according to claim 1, characterized in that: The drying temperature in step (2) is 60°C and the drying time is 6 hours.

6. The method for detecting shellfish toxins based on a transition metal oxide / noble metal particle composite SERS substrate according to claim 1, characterized in that: The laser wavelength in step (4) is 785 nm; the spectrum integration time is 3 s, the spectrum is collected 3 times, the light source power is 150 mw, and the scanning beam range is 400 to 3000 cm -1 .

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