Copper amino acid nano-enzyme colorimetric sensor, preparation method thereof and application of copper amino acid nano-enzyme colorimetric sensor in stored tea quality discrimination and catechin detection

Abstract

The invention discloses a copper amino acid nano-enzyme colorimetric sensor, a preparation method thereof and application of the copper amino acid nano-enzyme colorimetric sensor in stored tea quality discrimination and catechin detection, and belongs to the technical field of nano-enzyme and biological substance analysis and detection. The preparation method of the copper amino acid nano-enzyme comprises the following steps: uniformly mixing a Cu < 2 + > solution, NaOH and amino acid to obtain the copper amino acid nano-enzyme, the volume ratio of the Cu < 2 + > solution to the NaOH to the amino acid is (8-15): (3-7): (3-7); the concentrations of the Cu < 2 + > solution, the NaOH and the amino acid are all 1-3 mmol / L. The sensor has the beneficial effects that the sensor of the ketoamino acid nano-enzyme can qualitatively monitor the freshness of green tea Enshi haworthia cooperi in the storage process and quantitatively monitor catechin contained in the green tea Enshi haworthia cooperi, and a new choice is provided for quality evaluation and control of Enshi haworthia cooperi storage.

Description

Technical Field

[0001] This invention relates to the field of nanozyme and biomaterial analysis and detection technology, specifically to a copper amino acid nanozyme colorimetric sensor, its preparation method, and its application in the quality judgment and catechin detection of stored tea. Background Technology

[0002] Green tea is loved worldwide for its unique aroma and health benefits. In 2023, green tea accounted for 57.9% of China's total tea production, with a value of US$29.437 billion, representing 62.5% of the total output value, making it the largest tea category in China. In 2023, China's green tea production was 1.934 million tons, while sales reached 1.598 million tons. Due to the continuous expansion of the tea industry, tea production far exceeded sales, resulting in significant unsold tea.

[0003] During storage, tea is affected by environmental factors, leading to irreversible deterioration of its active ingredients and external color. Storing tea at room temperature for three months causes chlorophyll to degrade into pheophytin, changing the tea's color from green to yellowish-brown. In green tea, catechins undergo non-enzymatic oxidative polymerization in the presence of light or oxygen during storage, resulting in a decrease in their content. Studies show that most flavan-3-ols (catechins), which are positively correlated with green tea quality, decrease with increasing storage time, with a significant reduction in the total amounts of epigallocatechin (EGC), epigallocatechin gallate (EGCG), and epicatechin gallate (ECG). Storage at -20℃ and -80℃ effectively mitigates catechin degradation. Storing tea at 25℃ and 70% relative humidity also reduces the overall sensory acceptability of the leaves with increasing storage time, resulting in a loss of commercial and economic value for green tea. Driven by economic interests, some unscrupulous merchants often sell old tea as new tea, thereby harming consumers' rights and health and damaging the reputation of the tea industry.

[0004] Currently, the assessment of green tea storage quality mainly relies on professional evaluation and chemical testing. However, the number of professional evaluators is limited, making it difficult to conduct quality assessments on large quantities of stored samples. Chemical testing, such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), can differentiate the quality of stored tea, but these methods require specialized operators and sophisticated instruments, are demanding, and time-consuming. Due to these limitations, these chemical tests are mostly used in laboratory research and cannot meet the needs of on-site analysis. Therefore, a series of intelligent devices for judging tea quality, such as electronic tongues and electronic noses, have been invented. Compared to chemical testing devices, these devices are relatively simple to operate, but the results can only present the outline changes in taste or aroma, and cannot detect specific internal chemical substances, making them unsuitable for real-time and complex testing environments. For these reasons, it is crucial to develop a simple, low-cost sensor for real-time detection of green tea storage quality.

[0005] In recent years, nanozyme sensor arrays have attracted much attention due to their simple and intuitive operation and ability to simultaneously identify multiple analytes. Nanozymes possess various enzymatic activities, such as peroxidase (POD), oxidase, laccase, and hydrolase. For example, nanozymes with peroxidase activity can catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to a blue color (oxTMB), generating a colorimetric signal that can detect multiple analytes (antioxidants, pesticides, antibiotics, etc.). Gold, platinum, and palladium nanozymes have been successfully applied in medical, agricultural, and environmental detection. However, precious metal materials are expensive and their preparation processes are complex; they only exhibit POD activity under low pH conditions, making it difficult to meet the needs of large-scale detection.

[0006] Chinese patent application CN113295682A discloses a method for analyzing phenolic compounds based on polyphenol oxidase-active nanozymes, comprising: (1) preparation of an array sensor; (2) discriminant analysis of different phenolic pollutants; (3) discriminant analysis of different concentrations of the same phenolic substance; (4) discriminant analysis of a mixture of two phenolic substances; and (5) discriminant analysis of phenolic substances in actual samples. This method for analyzing phenolic compounds based on polyphenol oxidase-active nanozymes utilizes an array sensor constructed from a nanozyme system, exhibiting high detection sensitivity and scalability. It achieves the differentiation and analysis of different phenolic pollutants with high specificity and accuracy. Furthermore, by combining colorimetric arrays with chemometric algorithms and utilizing characteristic wavelengths to construct the sensor, the establishment of the sensor has a more theoretical basis. However, the sensor preparation operation of this patent is complex and has low sensitivity, thus requiring further research and improvement. Summary of the Invention

[0007] The technical problem to be solved by this invention is how to solve the problems of low detection sensitivity and slow response speed of existing sensors.

[0008] The present invention solves the above-mentioned technical problems through the following technical means: The first aspect of this invention provides a method for preparing copper amino acid nanozymes, comprising the following steps: Cu 2+ The solution, NaOH, and amino acids are mixed evenly to obtain the Cu. 2+ The volume ratio of the solution, NaOH, and amino acids is (8-15):(3-7):(3-7); the Cu 2+ The concentrations of the solution, NaOH, and amino acids are all 1-3 mmol / L; the amino acids are selected from any one of cysteine ​​(Cys), histidine (His), isoleucine (Ile), lysine (Lys), methionine (Met), proline (Pro), and pyroglutamic acid (pGlu).

[0009] Preferably, the Cu 2+ The volume ratio of the solution, NaOH, and amino acids is 10:5:5.

[0010] Preferably, the Cu 2+ The concentrations of the solution, NaOH, and amino acids were all 2 mmol / L.

[0011] Preferably, the Cu 2+ The solution can be any one of copper sulfate solution, copper chloride solution, copper nitrate solution, or copper acetate solution.

[0012] Preferably, the uniform mixing is specifically achieved by using a magnetic stirrer to mix the mixture evenly, with stirring conditions of 1000~2000 rpm for 1~8 min; more preferably 1500 rpm for 5 min.

[0013] A second aspect of the present invention provides a copper amino acid nanozyme prepared by the above preparation method.

[0014] A third aspect of the present invention provides a method for preparing a colorimetric sensor, comprising the following steps: mixing the above-mentioned copper amino acid nanozyme, H2O2, TMB (tetramethylbenzidine) and water to obtain a colorimetric sensor.

[0015] Preferably, the volume ratio of the amino acid nanozyme, H2O2, TMB, and water is (130~170):(80~120):(80~120):(640~660); more preferably, it is 150:100:100:650.

[0016] Preferably, the concentration of H2O2 is 1~3mM, more preferably 2 mM; the concentration of TMB is 1.25~80mM, more preferably 2 mM.

[0017] Preferably, the water is selected from any one of pure water, high-purity water, and ultrapure water.

[0018] A fourth aspect of the present invention provides a colorimetric sensor prepared by the above-described preparation method.

[0019] A fifth aspect of the present invention provides a kit for judging the quality of stored tea and / or detecting catechins, comprising the above-mentioned colorimetric sensor.

[0020] The sixth aspect of the present invention relates to the application of the aforementioned copper amino acid nanozyme, colorimetric sensor, and reagent kit in the quality assessment and / or detection of catechins in stored tea.

[0021] Preferably, the catechins include one or more of catechin (C), epicatechin (EC), epigallocatechin (EGC), epigallocatechin gallate (EGCG), epicatechin gallate (ECG), and gallatechin gallate (GCG).

[0022] The beneficial effects of this invention are as follows: 1. This invention constructs a colorimetric sensor for copper amino acid nanozymes, which is simple to prepare, highly sensitive, and capable of handling complex environments. Based on this sensor, combined with the freshness index of Enshi Yulu tea, the storage quality of tea samples can be monitored in real time. Compared with traditional sensory evaluation and chemical detection methods, this sensor has the advantages of being easy to operate, simple and portable, and having a fast response speed. Furthermore, the self-made copper amino acid nanozyme colorimetric sensor 1) overcomes the limitations of acidic conditions; 2) can quantitatively analyze catechins; and 3) enables the discrimination of the storage quality of Enshi Yulu tea under different storage conditions. 2. The detection limit of the copper amino acid colorimetric sensor of this invention is 0.005 mg / g, and the response time is 25 min, including 10 min of sonication and 15 min of reaction. Compared with other copper-based nanozyme sensors with a detection limit of 1 mg / mL and a response time of 20-60 min, this product has the advantages of high detection sensitivity and fast response speed. The sensor can qualitatively monitor the freshness of Enshi Yulu during storage and quantitatively monitor its catechin content, providing a new option for the quality evaluation and control of Enshi Yulu storage.

[0023] 3. This study uses a colorimetric sensor based on ketone amino acid nanozymes to detect the freshness index of green tea and the storage period of tea samples in real time. Compared with traditional sensory evaluation and chemical detection methods, this sensor has the advantages of easy operation, simple portability and fast response. (1) The catechin index of green tea stored for 0, 1, 2, 3, 6, 9 and 12 months under 5 storage conditions was detected; (2) Key compounds for storage were screened out by sensory evaluation and chemical indicators of tea: epigallocatechin gallate (EGCG), epicatechin (EC), epigallocatechin (EGC), epicatechin gallate (ECG), catechin (C) and gallatechin gallate (GCG); (3) A colorimetric sensor based on copper amino acid nanozymes was prepared by hydrothermal method and the reaction conditions were optimized; (4) A standard curve was established for catechin standards; (5) The storage period of green tea under different storage conditions was determined and catechins were predicted.

[0024] Of course, implementing any product or method of the present invention does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0025] Figure 1 The diagram shows the changes in catechin monomers in green tea samples under different storage conditions in Example 1 of the present invention, where (a) is EGCG, (b) is ECG, (c) is EGC, (d) is EC, (e) is C, (f) is GCG, and (g) is TC.

[0026] Figure 2 This is a two-dimensional scoring chart of catechin PCA in Example 1 of the present invention; Figure 3 The images show the SEM morphology, POD activity, and corresponding color photos of the copper amino acid nanozyme material in Example 2 of this invention, where (a) is Cu-Cys, (b) is Cu-His, (c) is Cu-Ile, and (d) is Cu-Lys. Figure 4 The images show the SEM morphology, POD activity, and corresponding color photos of the copper amino acid nanozyme material in Example 2 of this invention, where (e) represents Cu-Met, (f) represents Cu-pGlu, and (g) represents Cu-Pro. Figure 5 This is a graph showing the effect of the proportion of each raw material on the POD activity in Example 4 of the present invention, where (a1) is Cu-Cys, (b1) is Cu-His, (c1) is Cu-Ile, (d1) is Cu-Lys, (e1) is Cu-Met, (f1) is Cu-pGlu, and (g1) is Cu-Pro. Figure 6The diagram shows the effect of pH on POD activity in Example 4 of the present invention, where (a2) is Cu-Cys, (b2) is Cu-His, (c2) is Cu-Ile, (d2) is Cu-Lys, (e2) is Cu-Met, (f2) is Cu-pGlu, and (g2) is Cu-Pro. Figure 7 The diagram shows the effect of ultrasonic time on POD activity in Example 4 of the present invention, where (a3) ​​is Cu-Cys, (b3) is Cu-His, (c3) is Cu-Ile, (d3) is Cu-Lys, (e3) is Cu-Met, (f3) is Cu-pGlu, and (g3) is Cu-Pro. Figure 8 The following is a PCA discrimination result diagram of 0.005 mg / mL phenolic compounds in Example 5 of the present invention: (a) Cu-Cys, (b) Cu-His, (c) Cu-Ile, (d) Cu-Lys, (e) Cu-Met, (f) Cu-pGlu, and (g) Cu-Pro. Figure 9 The reaction rate diagram of ketone amino acid nanozymes determined by substrates with different concentrations of TMB in Example 4 of the present invention is shown; where (a1) is Cu-Cys, (b1) is Cu-His, (c1) is Cu-Ile, (d1) is Cu-Lys, (e1) is Cu-Met, (f1) is Cu-pGlu, and (g1) is Cu-Pro; Figure 10 The diagram shows the kinetic parameters of the ketone amino acid nanozymes determined by substrates with different concentrations of TMB in Example 4 of this invention; (a2) is Cu-Cys, (b2) is Cu-His, (c2) is Cu-Ile, (d2) is Cu-Lys, (e2) is Cu-Met, (f2) is Cu-pGlu, and (g2) is Cu-Pro. Figure 11 The graph shows the response results of Cu-Cys to different concentrations of catechin standards in Example 5 of this invention. Figure 12 The graph shows the response results of Cu-His to different concentrations of catechin standards in Example 5 of this invention. Figure 13 This is a graph showing the response results of Cu-Ile to different concentrations of catechin standards in Example 5 of the present invention; Figure 14 The graph shows the response results of Cu-Lys to different concentrations of catechin standards in Example 5 of this invention. Figure 15 The graph shows the response results of Cu-Met to different concentrations of catechin standards in Example 5 of this invention. Figure 16 The graph shows the response results of Cu-pGlu to different concentrations of catechin standards in Example 5 of this invention. Figure 17 This is a graph showing the response results of Cu-Pro to different concentrations of catechin standards in Example 5 of the present invention; Note: Figures 11-17 In the diagram, a1-a7 represent C, b2-b7 represent EC, c3-c7 represent ECG, d4-d7 represent EGC, e1-e7 represent EGCG, and f1-f7 represent GCG. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described 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 those skilled in the art without creative effort are within the scope of protection of the present invention. Unless otherwise defined, the technical terms used below have the same meaning as understood by those skilled in the art.

[0028] Unless otherwise specified, the test materials and reagents used in the following examples are commercially available or prepared by known methods.

[0029] Unless otherwise specified, all techniques or conditions described in the embodiments can be performed in accordance with the techniques or conditions described in the literature in this field or in the product manual. Unless otherwise specified, the quantitative experiments in the following embodiments are all repeated three times or more, and the results are averaged.

[0030] The tea (Enshi Yulu) was produced by the Enshi Academy of Agricultural Sciences in Hubei Province, and is from the same batch.

[0031] Reagent source: Catechins (C, 99%), epicatechin (EC, 99%), epigallocatechin (EGC, 99%), epigallocatechin gallate (EGCG, 99%), epicatechin gallate (ECG, 99%), and gallocatechin gallate (GCG, 99%) were purchased from Maclean Biotechnology Co., Ltd. (Shanghai, China) and were of high performance liquid chromatography (HPLC) grade.

[0032] Histidine (His, 99%), lysine (Lys, 99%), proline (Pro, 99%), methionine (Met, 99%), cysteine ​​(Cys, 99%), isoleucine (Ile, 99%), pyroglutamic acid (pGlu, 99%), 3,3',5,5'-tetramethylbenzidine (TMB, 99%), hydrated copper chloride (CuCl2·2H2O, 99%), and hydrogen peroxide (H2O2, 30%) were purchased from Maclean Biochemical Technology Co., Ltd. (Shanghai, China).

[0033] Methanol and acetonitrile (HPLC grade) were purchased from Anhui Tiandi High Purity Solvent Co., Ltd. (Anhui, China). Formic acid and acetic acid were purchased from Thermo Fisher Scientific (Waltham, Massachusetts, USA) as HPLC grade. L-ascorbic acid was purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China) with a purity of not less than 99.5%. Deionized water was prepared using a Millipore ultrapure water system (Bielerica, Massachusetts, USA).

[0034] software: Statistical analysis was performed using Origin 2025 (OriginLab Corp., Massachusetts, USA). Modeling was performed using MATLAB R2023b (Mathworks, Natick, USA). Bias analysis was performed using Excel. Significance scores were determined using SPSS. Principal component analysis (PCA) was performed using SIMCA (V14.1.0.2047, Umetrics, Umea, Sweden).

[0035] Model: Support Vector Machines (SVMs) are excellent classification decision models capable of handling nonlinearly separable problems. Least Squares Support Vector Machines (LSSVMs) inherit the advantages of SVMs, effectively handling both linear and nonlinear problems, and are suitable for regression and classification tasks. Backpropagation Neural Networks (BP) train multilayer perceptrons based on error backpropagation and are widely used in regression and classification. Random Forests (RFs) integrate multiple decision trees, exhibiting strong resistance to overfitting and are suitable for various types of data. When using these models for classification tasks, accuracy is typically used to evaluate model performance; an accuracy of 80% or higher is generally considered good, and 90% or higher is excellent.

[0036] Least Squares Support Vector Regression (LSSVR) was used to quantitatively predict the levels of key compounds. In the regression task, the performance of the LSSVR model was evaluated using the calibrated correlation coefficient (Rc) and prediction (Rp), the calibrated root mean square error (RMSEC) and prediction (RMSEP), and the prediction-to-bias ratio (RPD). Based on the RPD value, model performance was categorized as (i) Excellent (RPD ≥ 2.5), (ii) Good (1.8 ≤ RPD < 2.0), and (iii) Average (1.4 ≤ RPD < 1.8).

[0037] Example 1: Tea sample and sensory evaluation and sample pretreatment To study the quality change patterns and preservation effects of tea (Enshi Yulu) under different storage conditions, the tea was stored for 0, 1, 2, 3, 6, 9, and 12 months under the conditions shown in Table 1.

[0038] Table 1: Tea Sample Information

[0039] Samples were collected upon reaching the designated storage time and then submitted to a sensory panel of five experts for evaluation. The method was modified based on [Qianying D, Sitong L, Yurong J, et al. Recommended storage temperature for green tea based on sensory quality.[J]. Journal of food science and technology, 2019, 56(9):4333-4348.] (Table 2) to assess the quality of green tea during different storage processes. The experiment was approved by the Ethics Committee of Anhui Agricultural University. All participants were informed of the work requirements and risks and voluntarily participated in the complete sensory experiment. Information on all participants in the sensory evaluation was protected, and the release of all sensory data was authorized by the participants. The raw materials used in this project met food quality and safety standards and would not cause harm to humans, animals, or the environment. Furthermore, the samples were smelled but not consumed. There was no conflict of interest.

[0040] Table 2: Evaluation Table of Tea Storage Quality

[0041] HPLC method for the detection of catechins All tea samples were ground into powder using a portable electric grinder (IKA, Staufen, Germany). Catechin assays were repeated 20 times. The determination of catechins in tea was performed according to the national standard (GB / T8313–2018, Determination of Total Polyphenols and Catechins in Tea). The extraction and HPLC elution procedures for catechins were consistent with those described in [Feng W, Zhou H, Xiong Z, et al. Exploring the effect of different tea varieties on the quality of Lu'an Guapian tea based on metabolomics and molecular sensory science[J]. Food Chemistry: X, 2024, 23101534]. Monomer identification was performed using chemical standards for EGCG, ECG, GCG, EGC, EC, and C. The contents of EGCG, ECG, GCG, EGC, EC, and C were summed to calculate TC. The average value was calculated and used as a reference value for the samples.

[0042] Changes in catechins during green tea storage and sensory evaluation results of tea samples: Changes in catechins in tea samples under different storage conditions during storage, as follows: Figure 1 As shown, the catechin content of tea samples generally decreased during storage, with significant reductions in EGC, EGCG, ECG, EC, and total catechin content. Conversely, the contents of C and GCG showed an increasing trend. Catechins decreased during storage through auto-oxidation, epimerization, and oxidative degradation. EGCG, EGC, ECG, and EC could be epimerized into simpler catechins C and GCG, leading to an increase in their content, results similar to previous studies.

[0043] Set 1 conditions, characterized by high temperature, humidity, and oxygen levels, resulted in the fastest catechin degradation rate and the greatest loss compared to other conditions. This accelerated degradation was primarily driven by the synergistic effects of auto-oxidative degradation, epimerization, and hydrolysis. Specifically, under these conditions, ester-type catechins exhibited decreased stability, readily undergoing epimerization and transforming into acidic gallic acid (GA). The accumulation of GA led to increased acidity in the tea leaves, and the resulting acidic microenvironment further accelerated catechin degradation. Furthermore, the higher oxygen content promoted oxidative degradation of catechins, exacerbating the overall loss.

[0044] Compared to Set 1, Set 2 exhibited lower humidity, and while the degradation behavior of catechins was similar to Set 1, hydrolysis was inhibited. Sensory evaluation results showed no significant differences between the two sets. Set 3 was characterized by extremely low oxygen content, showing significant differences in both sensory evaluation and catechin content compared to Set 1. Under Set 3 conditions, catechin degradation was primarily heat-induced auto-oxidation, and anaerobic conditions mitigated the deterioration of tea quality. Sets 4 and 5 were stored at lower temperatures. Under low-temperature and frozen conditions, the half-life of catechin degradation was prolonged. Compared to room temperature conditions, highly significant differences were observed in sensory characteristics and catechin content, indicating that these conditions effectively maintained tea quality.

[0045] The sensory evaluation results are shown in Table 4. Based on the acceptance scores, the overall acceptability of tea decreased with increasing storage time. Under Set 1 conditions, sensory attributes deteriorated most rapidly, with all scores falling below the acceptable threshold after 6 months. Under Set 5 conditions, all scores remained at a relatively high level. The time points for tea to lose freshness under different storage conditions were as follows: under Set 1 conditions, tea lost freshness after 3 months of storage; under Set 2 conditions, tea lost freshness after 3 months of storage; under Set 3 conditions, tea lost freshness after 6 months of storage; under Set 4 conditions, tea lost freshness after 9 months of storage; and under Set 5 conditions, tea lost freshness after 12 months of storage. In conclusion, temperature has the greatest impact on sensory quality and catechin degradation, while low-oxygen conditions can alleviate catechin degradation and maintain tea quality.

[0046] Table 4. Sensory evaluation results of tea samples under different storage conditions

[0047] Table 5: Performance of key compounds in differentiating storage periods

[0048] Note: c: penalty coefficient; g: kernel function parameter; gam: penalty coefficient; sig: radial basis function.

[0049] Using the contents of EGC, ECG, EC, C, GCG, EGCG, and TC as variables in principal component analysis (PCA), a two-dimensional scoring plot was obtained (Figure 2). The results showed that with increasing storage time, the samples shifted from negative to positive values ​​along the PC1 axis. When tea reached its desiccation point under different storage conditions, the catechin data in the PCA results were all at the same moisture level, indicating that catechins can be considered key compounds for distinguishing stored tea. To verify that EGC, ECG, EC, C, GCG, EGCG, and TC are key compounds for quality changes during storage, a model was built using the key compounds and sensory evaluation results. The results are shown in Table 5. The SVM and LSSVM results show that the accuracy of the screened compounds reached over 95% in both the calibration set and the standard calibration set, verifying the correctness of the selected substances.

[0050] Example 2: Synthesis, characterization, and evaluation of peroxidase-like activity of copper amino acid nanozymes A method for preparing a copper lysine nanozyme includes the following steps: A mixture of NaOH solution and lysine (Lys) was added dropwise to a CuCl2·2H2O solution (10 mL, 2 mmol / L). The solution was then placed on a magnetic stirrer and stirred vigorously at 1500 rpm for 5 min. The solution was observed to gradually change from an initial blue color to a brownish-brown colloid, indicating that copper and lysine underwent coordination self-assembly. After the reaction was completed, copper-lysine nanozyme (denoted as Cu-Lys) was obtained, transferred to a brown light-proof glass bottle, and stored at 4 ℃.

[0051] (The mixture of NaOH solution and lysine (Lys) is prepared by mixing 2 mmol / L NaOH solution (5 mL) with 2 mmol / L lysine (5 mL).) Similarly, by replacing the lysine (Lys) with cysteine ​​(Cys), histidine (His), isoleucine (Ile), methionine (Met), proline (Pro), and pyroglutamic acid (pGlu), respectively, while keeping the rest unchanged, we obtain copper cysteine ​​nanozymes (Cu-Cys), copper histidine nanozymes (Cu-His), copper isoleucine nanozymes (Cu-Ile), copper methionine nanozymes (Cu-Met), copper proline nanozymes (Cu-Pro), and copper pyroglutamic acid nanozymes (Cu-pGlu).

[0052] Seven copper amino acid nanozyme materials were prepared, and 5 μL solutions were transferred to single-crystal silicon wafers, dried, and then tightly attached to sample trays. The seven copper amino acid nanozyme materials were then characterized using an S-4800 scanning electron microscope (SEM, Hitachi High Technology Corporation, Japan).

[0053] The results are as follows Figures 3-4As shown, Cu-His, Cu-Cys, Cu-Met, and Cu-pGlu exhibit similar shapes, being spherical with relatively uniform dimensions, with diameters ranging from approximately 100 to 300 nm; Cu-Pro, Cu-Lys, and Cu-Ile exhibit relatively uniform square shapes with side lengths ranging from approximately 150 to 300 nm. The high specific area of ​​the spherical structure and the polyhedral structure of the square shape can enhance the exposure of surface active sites, which is beneficial for contact and reaction with compounds, thereby increasing the reaction rate.

[0054] To evaluate the peroxidase-like activity of the seven copper amino acid nanozymes, 150 μL of each copper amino acid nanozyme solution was independently taken and mixed with 100 μL of hydrogen peroxide (H2O2, 10 mM) and 100 μL of TMB (10 mM) solution. The total volume of the mixture was then adjusted to 1 mL with pure water (pH = 7.0). The mixture was sonicated for 10 min to promote reactant diffusion and exposure of the nanozyme catalytic active sites. Immediately afterwards, 200 μL of the reaction mixture was transferred to a 96-well plate, and tests and data acquisition were performed using a multifunctional enzyme labeler (Spectra Max M2, CA, USA) at 10 nm intervals within the wavelength range of 552–752 nm.

[0055] After the synthesis of copper amino acid nanozymes, the oxidized (ox-TMB) substrate turned blue and showed a distinct absorption peak at 652 nm, demonstrating that the synthesized copper amino acid nanozymes have peroxidase-like activity (POD) characteristics.

[0056] like Figure 3 As shown, copper amino acid nanozymes, TMB, and H2O2 are colorless (white) when present alone and do not exhibit a significant absorption peak at 652 nm. In the individual nanozyme systems (copper amino acid nanozyme + TMB, copper amino acid nanozyme + H2O2) and the blank control group (TMB + H2O2), no significant color change was observed, and the absorption spectra at 652 nm did not show any obvious characteristic absorption peaks. This indicates that the catalytic oxidation ability of copper amino acid nanozymes for TMB substrates has not been activated under conditions lacking H2O2.

[0057] A significant color change was observed in the nanozyme-TMB-H2O2 ternary reaction system, with a distinct characteristic absorption peak at 652 nm. This phenomenon is perfectly consistent with the colorimetric characteristics of oxidized TMB (ox-TMB). Color change and UV-Vis spectroscopy analysis confirmed that the copper amino acid nanozyme can efficiently catalyze the oxidation of TMB only in the presence of H2O2. The significant color and absorbance changes demonstrate that the copper amino acid nanozyme possesses peroxidase-like catalytic activity.

[0058] Example 3: Fabrication of a colorimetric sensor A method for preparing a solution colorimetric sensor includes the following steps: Mix 150 μL of copper lysine nanozyme (Cu-Lys) with 100 μL of TMB (10 mM), add 100 μL of H2O2 (10 mM), and bring the volume to 1 mL with ultrapure water (pH = 7, 650 μL). Sonicate for 10 min to obtain a solution colorimetric sensor based on copper amino acid nanozyme (denoted as Cu-Lys colorimetric sensor).

[0059] Similarly, by replacing the copper lysine nanozyme (Cu-Lys) with copper cysteine ​​nanozyme (Cu-Cys), copper histidine nanozyme (Cu-His), copper isoleucine nanozyme (Cu-Ile), copper methionine nanozyme (Cu-Met), copper proline nanozyme (Cu-Pro), and copper pyroglutamic acid nanozyme (Cu-pGlu), while keeping the rest unchanged, we obtain the corresponding solution colorimetric sensors for copper amino acid nanozymes: Cu-Cys colorimetric sensor, Cu-His colorimetric sensor, Cu-Ile colorimetric sensor, Cu-Met colorimetric sensor, Cu-Pro colorimetric sensor, and Cu-pGlu colorimetric sensor.

[0060] Example 4: Exploration of Optimization of Colorimetric Sensor Fabrication Conditions The preparation conditions for the colorimetric sensor based on the solution of the seven ketone amino acid nanozymes obtained in Example 3 were optimized: A single-factor orthogonal experiment was used to study the effects of keto-amino acid nanozymes, H2O2, and TMB dosage on peroxidase-like activity (POD) (specific parameters are shown in Table 3, and results are as follows). Figure 5 (As shown); solutions with pH values ​​of 3, 5, 7, 9, and 11 were prepared to determine the effect of pH on peroxidase activity (e.g. Figure 6 (As shown); the effect of reaction times of 2, 4, 6, 8, 10, and 12 min on peroxide-like activity was confirmed under ultrasonic conditions (e.g. Figure 7 As shown in the figure, the changes in the ultraviolet-visible absorption peaks were observed to determine the optimal reaction conditions.

[0061] For the analysis of enzyme kinetic constants, different concentrations of 100 μL TMB (1.25–80 mM) were added at 300 s intervals, and absorbance at 652 nm was collected using a UV-Vis spectrophotometer. Finally, the kinetic parameters were calculated using the Michaelis-Menten equation, as shown below:

[0062] Where Km is the Michaelis constant, Vmax is the maximum reaction rate, and [S] represents the TMB concentration.

[0063] To explore the catalytic mechanism of ketone amino acid nanozymes, 5 μL of tert-butanol (IPA), tryptophan (Trp), and p-benzoquinone (p-BQ) were added to the reaction system, and the changes in the light value of the reaction system at 520 nm were observed to determine the catalytic mechanism of the reaction system.

[0064] Table 3 Orthogonal Table of Raw Material Proportions Results: Single-factor orthogonal experiments showed that increasing the content of keto-amino acid nanozymes effectively increased the absorbance. The absorbance was significantly increased in the presence of H₂O₂ and keto-amino acid nanozymes. TMB also showed an effective increase in absorbance with increasing H₂O₂ and keto-amino acid nanozyme content. The fourth reaction system exhibited the best absorbance values ​​with 150 μL keto-amino acid nanozymes, 100 μL H₂O₂, and 100 μL TMB. Figure 5 (As shown) Taking into account both the experimental dosage and the experimental results, the fourth group of reaction conditions was finally selected as the optimal ratio of raw material dosage.

[0065] The effect of pH on POD activity, the results are as follows Figure 6 As shown, the absorbance first increases and then decreases with the increase of pH value, reaching its highest value at pH 7. Therefore, pH 7 can be taken as the optimal reaction condition.

[0066] The effect of reaction time on POD activity is shown in the following results. Figure 7 As shown, the absorbance values ​​increased with time in the 2-8 min range, and stabilized after 10-12 min, with no significant differences between groups. Considering both reaction speed and practicality, 10 min of sonication was ultimately selected as the optimal reaction time.

[0067] The optimal reaction conditions for the sensor were confirmed by experiments in this embodiment as follows: 1 mL reaction system containing 150 μL ketone amino acid nanozyme, 100 μL H2O2 (2 mM), 100 μL LTMB (2 mM) and 650 μL pure water (pH=7), and sonicated at room temperature for 10 min.

[0068] Reaction mechanism and enzyme kinetics results: The potential catalytic performance of a copper amino acid nanosensor system was explored by adding relevant scavengers of reactive oxygen species (ROS). Experimental results on the capture of ROS by different scavengers were summarized. Tert-butanol (IPA), tryptophan (Trp), and p-benzoquinone (p-BQ) were used to target hydroxyl radicals (-OH) and singlet oxygen (-OH), respectively. 1 O2), superoxide anion (O2 .-When these scavengers were introduced, the absorbance of the reaction system containing IPA and p-BQ remained almost unchanged compared to the blank. However, the absorbance decreased and the color lightened upon the addition of Trp, indicating that singlet oxygen plays a major role in the oxidation of TMB in this system, while the other two free radicals do not participate in the reaction.

[0069] Kinetic parameters were determined by oxidizing TMB with a keto amino acid nanozyme. The substrate concentration of TMB was gradually varied, and absorbance changes were recorded over 5 min to calculate the initial rate. The Michaelis equation was plotted on... Figures 9-10 In the study, the order of enzyme activity, confirmed by comparing Km values, was Cu-Lys, Cu-Met, Cu-Cys, Cu-His, Cu-ILe, Cu-Pro, and Cu-pGlu.

[0070] Example 5: Application of the seven colorimetric sensors prepared in Example 3 in the quality judgment and catechin detection of stored tea: I. Detection of six phenolic compounds, including catechins, as standards To test the discrimination capability of the fabricated colorimetric sensor, we selected six key phenolic compounds from tea samples during storage: EGCG, EGC, EC, C, ECG, and GCG (0.005 mg / mL, 5 μL each). Specifically: Different types of phenolic compounds (5 μL each, 0.005 mg / mL) were independently added to colorimetric sensors (1 mL each) of seven copper amino acid nanozymes, and the absorbance of the reaction systems at 652 nm was recorded. Finally, the differences in the reactions of the six phenolic compounds in different systems were calculated by the differences in absorbance. (Results are shown below) Figure 8 (As shown) Different phenolic compounds exhibit varying degrees of inhibition on the oxidation of TMB by different copper amino acid nanozymes. These differences lead to varying absorbance values ​​at 652 nm, resulting in distinct colorimetric responses and thus unique fingerprint reactions for individual phenolic substances. Principal component analysis (PCA) is used to identify different catechins, such as... Figures 11-17 As shown, it can effectively distinguish different catechins. This proves that this sensor can be used to distinguish catechins.

[0071] To assess the quantitative analytical capabilities of the sensors, the dependence of phenolic compound (EGCG, EGC, EC, C, ECG, GCG) sensors on antioxidant concentration was discussed.

[0072] Similarly, different concentrations of phenolic substances were analyzed (0.005 mg / mL was replaced with 0.05, 0.1, 0.2, 0.3 and 0.5 mg / mL of phenolic substances, while the rest remained unchanged), to quantitatively detect catechin standards.

[0073] The colorimetric sensor for copper amino acid nanozymes detected six concentrations of each phenolic compound in the range of 0.005–0.5 mg / mL. The standard curve results are shown below. Figures 11-17 As shown, the correlation coefficient (R) 2 ECG (0.9998), EGC (0.9915), EGCG (0.9959), C (0.9791), GCG (0.9915), EC (0.9739) within the linear range of 0.005-0.5 mg / mL.

[0074] II. Testing and Analysis of Stored Tea Samples To distinguish the storage period of green tea (Enshi Yulu) under different storage conditions, a colorimetric sensor using seven copper amino acid nanozymes was employed to identify tea samples. Specifically, 0.1 g of tea powder was accurately weighed and then added to 10 mL of pure water. The sample was steeped at a constant temperature of 70 ℃ for 10 min, with thorough shaking every 5 min. The solution was then filtered using a 0.22 µm PTFE filter. 5 μL of the filtered tea solution was added to the colorimetric sensor, and the absorbance value at 652 nm was recorded to construct a discriminant model, further enabling the determination of the storage period of green tea during storage.

[0075] To distinguish the storage period of green tea under different storage conditions and for different storage times (0, 1, 2, 3, 6, 9, and 12 months under the conditions of Set 1, Set 2, Set 3, Set 4, and Set 5), the dataset was analyzed using BP and RF models. The discrimination results of the calibration set and the prediction set are shown in Table 6. The discrimination effect of the copper amino acid nanoenzyme colorimetric sensor is greater than 80.00%, and the discrimination of storage period by the copper amino acid nanoenzyme colorimetric sensor reaches 94.59%, which proves that the colorimetric sensor prepared in this invention can effectively distinguish the storage period of green tea.

[0076] Table 6: Performance of using BP and RF models to determine the storage quality of Enshi Yulu dew

[0077] Note: n: number of iterations, goal: target error, r: learning rate, tresa: number of decision trees, leaf: minimum number of leaf nodes.

[0078] The LSSVR prediction models for catechins, based on each catechin, are shown in Table 7. The LSSVR models achieved satisfactory performance for both individual catechins and total catechins. The Rp values ​​for EGC, C, GCG, and TC were 0.9238, 0.918, 0.9281, and 0.9573, respectively; the RMSEP values ​​were 1.5451, 0.0737, 0.3045, and 2.6346, respectively; and the RPD values ​​were 4.4230, 2.6450, 2.7590, and 3.4400, respectively. The LSSVR models achieved acceptable prediction accuracy for both individual catechins and the total catechin count, meeting the requirements for rapid detection.

[0079] Table 7: Performance of different catechin prediction models

[0080] Note: gamma is the penalty factor and a parameter of the sig kernel function.

[0081] Summarize: In this invention, changes in catechins during the storage of green tea were detected. It was found that low temperature and low oxygen conditions alleviated the decrease in catechins, effectively maintaining tea quality. Temperature had the strongest effect on catechin degradation and quality preservation. Six key compounds that differentiate storage quality were successfully screened, and a colorimetric sensor for seven ketone amino acid nanozymes, characterized by mild reaction conditions, low cost, and high sensitivity, was successfully constructed. The sensor's detection principle involves the oxidation of TMB to oxTMB in the presence of H2O2, resulting in a change in absorbance at 652 nm and a color change from colorless to blue. Catechins in tea have the property of inhibiting the oxidation process of TMB. The reaction conditions of the sensor were optimized by adjusting the dosage ratio, pH, and reaction time. The optimal conditions were: a 1 mL reaction system containing 150 μL of ketone amino acid nanozyme, 100 μL of H2O2 (2 mM), 100 μL of TMB (2 mM), and 650 μL of pure water (pH=7), followed by sonication at room temperature for 10 min. Sensors were applied to the qualitative and quantitative monitoring of the quality of catechin standards and Enshi Yulu liquor during storage.

[0082] The results showed that the quantitative correlation coefficient of catechin standards based on UV absorption spectroscopy data was above 98%, and the constructed BP and RF models achieved accurate discrimination of storage quality, with a prediction set accuracy of 94%. The LSSVR model demonstrated acceptable performance in predicting catechin monomers and TC, with PRD values ​​ranging from 1.907 to 4.423. In conclusion, the developed ketone amino acid nanozyme colorimetric sensor can identify phenolic compounds in stored green tea, providing a new option for real-time monitoring of green tea storage.

[0083] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for preparing a copper amino acid nanoscale enzyme, characterized in that, Includes the following steps: Cu 2+ The solution, NaOH, and amino acids are mixed evenly to obtain the Cu. 2+ The volume ratio of the solution, NaOH, and amino acids is (8-15):(3-7):(3-7); the Cu 2+ The concentrations of the solution, NaOH, and amino acids are all 1-3 mmol / L; the amino acids are selected from any one of cysteine, histidine, isoleucine, lysine, methionine, proline, and pyroglutamic acid.

2. The method of claim 1, wherein, The Cu 2+ The solution is any one of a copper sulfate solution, a copper chloride solution, a copper nitrate solution, and a copper acetate solution.

3. The copper amino acid nanozyme prepared by the preparation method according to any one of claims 1-2.

4. A method of preparing a colorimetric sensor, characterized by, The process includes the following steps: mixing the copper amino acid nanozyme described in claim 3, H2O2, TMB, and water to obtain a colorimetric sensor.

5. The preparation method according to claim 4, characterized in that, The volume ratio of the amino acid nanozyme, H2O2, TMB, and water is (130~170):(80~120):(80~120):(640~660).

6. The preparation method according to claim 4, characterized in that, The concentration of H2O2 is 1~3 mM; the concentration of TMB is 1.25~80 mM.

7. The preparation method according to claim 4, characterized in that, The water is selected from any one of pure water, high-purity water, and ultrapure water.

8. A colorimetric sensor prepared by the method according to any one of claims 4-7.

9. A kit for judging the quality of stored tea and / or detecting catechins, characterized in that, It includes the colorimetric sensor as described in claim 8.

10. The application of the copper amino acid nanozyme of claim 3, the colorimetric sensor of claim 8, and the kit of claim 9 in the quality judgment and / or detection of catechins in stored tea.

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