Preparation of antibacterial film and application research of dairy product preservation and quality monitoring method

Abstract

The invention discloses preparation of an antibacterial film and application research of a dairy product preservation and quality monitoring method, and relates to a preparation method and application of a film. The invention aims to solve the problems that when bacterial cellulose is singly used in the existing method, the mechanical property is insufficient, the antibacterial activity is lacked, the application of the bacterial cellulose in the field of food preservation is limited, the bioavailability of the existing anthocyanin is poor, and the existing anthocyanin is easy to degrade under the conditions of pH, heat treatment, metal ions and the like. The method comprises the following steps: 1, preparing a mixed solution of anthocyanin and naringenin; and 2, adding bacterial cellulose, and casting and molding in a dark environment. According to the application of the prepared antibacterial film in detecting the freshness of the milk, Raman spectrum data of the milk are collected, the quality of the goat milk is analyzed by using three characteristic peaks of 870 cm <-1 >, 1302 cm <-1 > and 1441 cm <-1 >, and the accuracy rate of detecting the freshness of the milk can reach 100% by combining the collected Raman spectrum data of the milk with machine learning; the film can also be used for photocatalytic bacteriostasis and intelligent food packaging film systems.

Description

Technical Field

[0001] The invention relates to a preparation method and application of a film. Background Art

[0002] Foodborne diseases and food spoilage have been issues throughout human history, and despite years of innovation and technology, food safety in the restaurant industry remains a challenge for all countries. According to a study by the Centers for Disease Control and Prevention, approximately 9.4 million cases of foodborne illness occur in the United States each year. In this context, foodborne illness is defined as an illness caused by contaminated food or beverages, primarily by various bacteria or their toxins, viruses, and parasites, and is a public health concern in many countries. Improper food handling is one of the leading causes of foodborne illness, and contaminated food can cause up to 600 million foodborne illnesses, which can cause many health-related consequences such as death, disability, neurological disorders, and kidney failure. In addition, these diseases have considerable socioeconomic impacts, reducing national economic productivity, harming trade and tourism, and increasing costs to society, the agri-food industry, and governments.

[0003] Staphylococcus aureus is one of the most common highly pathogenic pathogens. Food contamination by Staphylococcus aureus and subsequent secretion of enterotoxins are the main causes of food poisoning caused by Staphylococcus. This type of highly pathogenic pathogen has a wide range of transmission and a fast speed, which can easily cause food poisoning and various inflammatory reactions, posing certain challenges to public health management. Food packaging can effectively prevent chemical contamination, extend shelf life, and reduce the risk of foodborne disease infection, thereby achieving food safety, facilitating handling and transportation, and providing convenience for consumers. A variety of materials, including plastics, glass, metals, paper and their composites, have been used for food packaging. Appropriate materials can effectively isolate food from external factors, slow down the process of food corruption, and inhibit or kill the growth of pathogenic bacteria. Therefore, the development of new environmentally friendly and degradable food packaging materials has become an urgent problem to be solved in the current field of food science.

[0004] Bacterial cellulose (BC) is a natural polymer material synthesized by aerobic bacteria such as Acetobacter, Agrobacterium, and Rhizobium, with the same chemical composition as natural (plant) cellulose. The nanostructure of BC determines its physical and mechanical properties. Compared with plant cellulose, BC is thinner, and the 3D network woven by nanofibers can increase its surface area to volume ratio, thereby interacting strongly with neighboring components. It also provides relatively outstanding mechanical strength, high polymerization and crystallinity (about 90%), and water retention capacity. In addition, it has attracted much attention due to its high purity, lack of free lignin, hemicellulose, pectin, etc., non-toxicity and biodegradability. These characteristics make it have great application potential in the fields of medicine, food, etc. It is worth mentioning that when BC is used alone, there are problems with insufficient mechanical properties and lack of antibacterial activity. There are limitations in its application in the field of food preservation. Therefore, it needs to be compounded with other polymer materials in the hope of improving its mechanical properties and expanding its practicality in food preservation and the scope of application in the field of polymer materials.

[0005] Anthocyanidins (ATH) are water-soluble natural pigments widely found in plants. They are metabolized from phenylalanine and are the main coloring substances in plants and fruits. Anthocyanidins are becoming increasingly popular as colorants in the food industry and can be used as a substitute for synthetic colorants. In addition, anthocyanidins are also effective antioxidants in vitro. However, the bioavailability of anthocyanidins is very poor, only about 1%, and they are easily degraded under conditions such as pH, heat treatment, and metal ions, which limits their application. Summary of the invention

[0006] The purpose of the present invention is to solve the problems that when bacterial cellulose is used alone in the existing method, the mechanical properties are insufficient and the antibacterial activity is lacking, the application in the field of food preservation is limited, the bioavailability of existing anthocyanins is poor, and it is easily degraded under conditions such as pH, heat treatment, metal ions, etc., and to provide an antibacterial film preparation and its application research on milk preservation and quality monitoring methods.

[0007] A method for preparing an antibacterial film is specifically completed by the following steps:

[0008] 1. dissolving anthocyanin and naringenin in deionized water to obtain a mixed solution of anthocyanin and naringenin;

[0009] 2. Add bacterial cellulose to a mixed solution of anthocyanin and naringenin, and homogenize it using a homogenizer at room temperature to obtain a mixed solution; cast the mixed solution under closed light to obtain an ATH-Nar-BC film, which is an antibacterial film.

[0010] An antibacterial film is used in detecting the freshness of milk.

[0011] An antibacterial film is used for photocatalytic antibacterial.

[0012] An antibacterial film is used to prepare an intelligent food packaging film system that can monitor the freshness of milk and extend the shelf life of milk.

[0013] Principle of the present invention:

[0014] 1. Naringenin (Nar) is the aglycone of naringin, belongs to flavonoids, is a relatively safe and non-toxic bioactive compound, and is mainly found in citrus fruits such as lemon, orange, tangerine and grapefruit. Naringenin is soluble in ethanol, ether and benzene, and has many biological and pharmacological abilities, such as antioxidant, antibacterial, anti-inflammatory, etc., but its functional application is limited by low lipophilicity and low hydrophilicity; the present invention utilizes naringenin (Nar) to be compounded with bacterial cellulose (BC) and anthocyanidin (ATH) to achieve the purpose of food preservation, so as to develop a more sensitive food packaging film;

[0015] 2. As a non-destructive analytical technology, Raman spectroscopy can provide detailed information on the molecular structure and chemical composition of substances; deep machine learning can process and analyze huge data sets, extract valuable information from them, and make predictions; Raman spectroscopy technology combined with machine learning algorithms has shown great potential in food quality monitoring and prediction; especially in the field of goat milk preservation, it can achieve accurate prediction and real-time monitoring of goat milk deterioration; the present invention uses the latest research progress of Raman-machine learning model to predict goat milk deterioration during storage, including model construction and verification; thus providing an efficient, accurate and reliable new method for goat milk preservation technology;

[0016] 3. The present invention uses bacterial cellulose as the base of bactericidal cling film, loads anthocyanins and naringenin onto the surface of bacterial cellulose film, applies it to photocatalytic antibacterial, and conducts deep machine learning analysis on its preservation process; this process aims to construct a machine learning-based intelligent food packaging film system that integrates monitoring of food freshness and extending the shelf life of food.

[0017] Advantages of the present invention:

[0018] 1. Raw material safety: Anthocyanins are often used as food colorants in ordinary beverages and foods. Naringenin is a natural product derived from plants and animals, and has wide application potential in the fields of food and medicine. Its impact on the environment and human health has been widely studied. Bacterial fiber is a natural inert material synthesized by bacteria and has been widely used in medicine, food and other fields. In short, this product has the characteristics of no metal elements, safety and environmental protection.

[0019] Second, the synthesis method is simple: anthocyanins and naringenin are well dispersed and dissolved in the bacterial cellulose solution by simple stirring and homogenization;

[0020] 3. The freshness of goat milk can be visually indicated: the antibacterial film is attached to the inner side of the lid and sealed. In the process of goat milk corruption, fat, protein, etc. are decomposed, resulting in coagulation and stratification of the product, while increasing the pH value in the package and changing the color of the film; the goat milk is evenly packed into the box, the inner side of the lid is covered with the antibacterial film, and the label (the antibacterial film prepared by the present invention, with a size of 1 cm×1 cm) is placed in the same environment at the same time, sealed and stored at 4°C for 14 days, and taken out for observation every eight hours. The label appears light pink before the experiment begins, and as the storage time increases, the label begins to turn pink and eventually turns purple;

[0021] 4. High sterilization efficiency: Under photocatalytic conditions (xenon lamp irradiation), it can achieve high efficiency in killing Staphylococcus aureus within 20 minutes; the main sterilization mechanism is that the naringenin on the film produces ROS during irradiation, which damages the surface of bacteria; it causes its cell membrane to rupture, thereby losing its original shape and function, and eventually leading to its death. The physical properties of the film are good; the composite film has good mechanical properties, hydrophilicity and water retention, and is suitable for use in packaging materials;

[0022] 5. Small detection range and high prediction accuracy: Raman technology-deep machine learning can more accurately detect the corruption of goat milk at different storage times, and predict the freshness of goat milk through machine learning. The application of Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) can achieve 100% prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The colors and UV-visible spectra of the ATH-Nar mixed solution, ATH solution and Nar solution prepared by the present invention at a pH of 3-10;

[0024] Figure 2 This is a color diagram of the ATH-Nar-BC film prepared in Example 1 of the present invention under the condition of pH 3-10;

[0025] Figure 3 This is a scanning electron microscope image of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0026] Figure 4 This is a graph showing the sterilization efficiency of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0027] Figure 5 This is a staining image of live and dead bacteria of the ATH-Nar-BC film prepared in Example 1 of the present invention after sterilization;

[0028] Figure 6This is a diagram of the mechanical properties of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0029] Figure 7 This is a water contact angle diagram of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0030] Figure 8 This is a graph of water vapor permeability of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0031] Fig. 9 This is a Raman spectrum of the ATH-Nar-BC film prepared in Example 1 of the present invention for keeping goat milk fresh;

[0032] Fig.10 This is a deep machine learning prediction graph of the ATH-Nar-BC film prepared in Example 1 of the present invention for the preservation of goat milk;

[0033] Fig.11 This is the structure diagram of the CNN model;

[0034] Fig.12 This is the structure diagram of the BP-ANN model. DETAILED DESCRIPTION

[0035] Specific implementation method 1: This implementation method is a method for preparing an antibacterial film, which is specifically completed by the following steps:

[0036] 1. dissolving anthocyanin and naringenin in deionized water to obtain a mixed solution of anthocyanin and naringenin;

[0037] 2. Add bacterial cellulose to a mixed solution of anthocyanin and naringenin, and homogenize it using a homogenizer at room temperature to obtain a mixed solution; cast the mixed solution under closed light to obtain an ATH-Nar-BC film, which is an antibacterial film.

[0038] Specific implementation method 2: This implementation method is different from specific implementation method 1 in that the mass ratio of anthocyanin to naringenin in step 1 is 1:(0.5-2). The other steps are the same as those in specific implementation method 1.

[0039] Specific implementation method 3: This implementation method is different from specific implementation method 1 or 2 in that the concentration of anthocyanin in the mixed solution of anthocyanin and naringenin in step 1 is 1 mg / mL to 2 mg / mL. The other steps are the same as those in specific implementation method 1 or 2.

[0040] Specific embodiment 4: This embodiment differs from specific embodiments 1 to 3 in that the homogenization time at room temperature using a homogenizer in step 2 is 3 to 8 minutes. The other steps are the same as those of specific embodiments 1 to 3.

[0041] Specific embodiment 5: This embodiment differs from specific embodiments 1 to 4 in that the mass ratio of bacterial cellulose to the mixed solution of anthocyanin and naringenin in the mixed solution described in step 2 is 1:(0.5-2). The other steps are the same as those of specific embodiments 1 to 4.

[0042] Specific implementation method six: This implementation method is an antibacterial film used in detecting the freshness of milk.

[0043] Specific embodiment 7: This embodiment differs from specific embodiments 1 to 6 in that: by collecting Raman spectrum data of milk and combining it with machine learning, the accuracy of detecting the freshness of milk can reach 100%; the milk is goat milk. The other steps are the same as those of specific embodiments 1 to 6.

[0044] Specific implementation eight: This implementation differs from specific implementations one to seven in that the machine learning method is an ANN algorithm or a CNN algorithm. The other steps are the same as those of specific implementations one to seven.

[0045] Specific implementation method 9: This implementation method is an antibacterial film used for photocatalytic antibacterial.

[0046] Specific implementation method ten: This implementation method is an antibacterial film used to prepare an intelligent food packaging film system that monitors the freshness of milk and extends the shelf life of milk.

[0047] The following examples are used to verify the beneficial effects of the present invention:

[0048] Embodiment 1: A method for preparing an antibacterial film, characterized in that the method for preparing the antibacterial film is specifically completed according to the following steps:

[0049] 1. dissolving anthocyanidin (ATH) and naringenin (Nar) in deionized water to obtain a mixed solution of anthocyanidin and naringenin (ATH-Nar mixed solution);

[0050] The mass ratio of anthocyanin and naringenin described in step 1 is 1:1;

[0051] The concentration of anthocyanin in the mixed solution of anthocyanin and naringenin described in step 1 is 1.5 mg / mL;

[0052] 2. Add bacterial cellulose (BC) to the mixed solution of anthocyanin and naringenin, and homogenize with a homogenizer for 10 minutes at room temperature to obtain a mixed solution; cast the mixed solution under dim light to obtain an ATH-Nar-BC film, which is an antibacterial film;

[0053] The mass ratio of bacterial cellulose to the mixed solution of anthocyanin and naringenin in the mixed solution described in step 2 is 1:1.

[0054] Comparative Example 1: The preparation method of ATH solution is specifically completed according to the following steps:

[0055] Anthocyanidin (ATH) was dissolved in deionized water to obtain an anthocyanidin solution (ATH solution).

[0056] Comparative Example 2: The preparation method of Nar solution is specifically completed according to the following steps:

[0057] Naringenin (Nar) was dissolved in deionized water to obtain a naringenin solution (Nar solution).

[0058] Figure 1 The colors and UV-visible spectra of the ATH-Nar mixed solution, ATH solution and Nar solution prepared by the present invention at a pH of 3-10;

[0059] from Figure 1 It can be seen that: the color changes of individual materials and mixed materials in different buffers; when the pH value rises from 3 to 10, the color of the individual pigment and mixed pigment solution changes from pink to purple; from the color changes in the figure, it can be seen that the color of the mixed solution becomes richer; at pH values ​​of 5, 6 and 7, the color change is more obvious; the pH color change sensitivity of the mixed solution is higher than that of the solution using ATH alone; it can be better used for color indication of the degree of goat milk deterioration.

[0060] Figure 2 This is a color diagram of the ATH-Nar-BC film prepared in Example 1 of the present invention under the condition of pH 3-10;

[0061] from Figure 2 It can be seen that the color of the film is different at different pH values. When the pH is 3, the ATH-Nar-BC film is pink; as the pH value increases, the color gradually deepens, turns purple, and finally turns purple-brown, and the color gradient changes significantly.

[0062] Figure 3 This is a scanning electron microscope image of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0063] from Figure 3 It can be seen that the ATH-Nar-BC film prepared in Example 1 of the present invention appears to be dense and comprehensively interlaced fiber filaments under a scanning electron microscope.

[0064] Test Example 1:

[0065] Staphylococcus aureus (S. aureus) was selected as the indicator bacteria. All utensils and culture media were inactivated by high temperature before use. First, 108 CFU / mL bacterial suspension. Then, the antibacterial film (1 cm×1 cm) prepared in Example 1 was placed in a 6-well plate, and 100 μL (1×10 8 CFU / mL) of bacterial solution was dropped on the film. A transparent 6-well plate was placed under a xenon lamp (λ>420nm, light intensity: 200mW cm -2 ) and irradiated once every 20 minutes for a total of 2 times, then the mixture and the film were transferred to 900 μL of physiological saline, mixed and 100 μL was drawn and applied to the LB plate. The LB plate was then placed in a 37°C incubator for 24 hours.

[0066] The antibacterial results are as follows Figure 4 As shown;

[0067] Figure 4 This is a graph showing the sterilization efficiency of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0068] from Figure 4 It can be seen that the ATH-Nar-BC film prepared in Example 1 of the present invention can kill 10 6 CFU / mL of Staphylococcus aureus, indicating that the ATH-Nar-BC film prepared by the present invention has a strong antibacterial efficiency.

[0069] Test Example 2:

[0070] Staphylococcus aureus (S. aureus) was selected as the indicator bacteria. All utensils and culture media were inactivated by high temperature before use. First, 10 8 CFU / mL bacterial suspension. Then, the antibacterial film (referred to as BC-ATH-NAR) (1 cm×1 cm) prepared in Example 1 was placed in a 6-well plate, and 100 μL (1×10 8 CFU / mL) of bacterial solution was dropped on the film. A transparent 6-well plate was placed under a xenon lamp (λ>420nm, light intensity: 200mWcm -2 ) and irradiated once every 20 minutes. After irradiation for 2 times, the mixture and film were transferred to 900 μL of physiological saline, mixed and 100 μL was drawn and applied to the LB plate. The LB plate was then placed in a 37°C incubator for 24 hours; the irradiated BC-ATH-NAR was stained with SYTO 9 / PI dye and observed by laser confocal microscopy; the results are shown in Figure 2. Figure 5 As shown;

[0071] Similarly, bacterial cellulose film (denoted as BC), naringenin film (denoted as Nar) and anthocyanin film (denoted as ATH) were used to replace the antibacterial film prepared in Example 1 (denoted as BC-ATH-NAR) and the same steps were followed. The results are shown in FIG. Figure 5 As shown;

[0072] Figure 5 This is a staining image of live and dead bacteria of the ATH-Nar-BC film prepared in Example 1 of the present invention after sterilization;

[0073] from Figure 5 It can be seen that as the illumination time increases, the red fluorescence signal gradually increases, and the green fluorescence gradually weakens, indicating that the number of dead cells gradually increases. When the illumination is 60 minutes, the red fluorescence signal occupies the vast majority, indicating that the vast majority of bacteria have died at this time. Therefore, it can be inferred that the ATH-Nar-BC film kills bacteria by destroying the bacterial cell membrane.

[0074] Test Example 3:

[0075] The mechanical properties of the film, including elongation at break and tensile modulus, were tested by a texture analyzer. The mechanical properties test results are as follows: Figure 6 As shown;

[0076] Figure 6 This is a diagram of the mechanical properties of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0077] from Figure 6 It can be seen that the incorporation of pigments leads to a decrease in the tensile strength of the film, and finally the tensile strength increases with the increase of pigment concentration, which may be due to the hydrogen bonding between the pigment and the matrix. The trend of the elongation at break is similar to that of the tensile strength, which is due to the cross-linking of the phenolic hydroxyl groups in ATH / Nar with the substrate, resulting in a decrease in flexibility. In conclusion, the pigment-doped ATH-Nar-BC film has a high tensile strength, but the elongation at break value is limited.

[0078] Test Example 4:

[0079] The hydrophobicity of the films was measured using a water contact angle meter;

[0080] The water contact angle test results are as follows Figure 7 ;

[0081] Figure 7 This is a water contact angle diagram of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0082] from Figure 7It can be seen that the pigment-modified ATH-BC film has a smaller water contact angle. Subsequently, with the addition of Nar, more hydroxyl groups are provided to combine with hydrogen bonds, increasing the repulsive force of water molecules and leading to an increase in the water contact angle.

[0083] Test Example 5:

[0084] This test determines the water vapor transmission rate (WVP) of a film. The film is sealed on a permeation cup containing CaCl2 and placed in a desiccator. The container is removed and weighed at different times. The WVP is calculated using the following formula:

[0085] WVP=(Δm×d) / (S×Δt×Δp)

[0086] Where Δm (g) is the weight difference, d (mm) is the thickness of the film, S (m 2 ) is the permeation area of ​​the membrane, Δt(h) is the permeation time of the membrane, and Δp(kPa) is the pressure difference on both sides of the membrane; Figure 8 As shown;

[0087] Figure 8 This is a graph of water vapor permeability of the ATH-Nar-BC film prepared in Example 1 of the present invention;

[0088] from Figure 8 It can be seen that the WVP of ATH-Nar-BC is lower than that of the BC film without pigment, indicating that the composite film has improved water barrier ability; this is beneficial to improving the water retention capacity of the film.

[0089] Test Example 6:

[0090] The goat milk was packed into sterile boxes according to 50 ml and divided into 5 groups. The experimental group used the ATH-Nar-BC film prepared in Example 1, the control group used BC, ATH-BC, and Nar-BC films, and the last group did not do any treatment. The film was attached to the inside of the box lid and sealed. A fresh-keeping label made of ATH-Nar-BC was placed in each sterile fresh-keeping box. This test measured the Raman spectra of goat milk treated with the membrane at different storage times. The goat milk sample was dropped onto the carrier chip, placed on the stage, the surface microstructure of the goat milk was observed under a 20x objective lens, and the Raman spectrum data was collected. The Raman spectrum wavelength range is 500-30000cm -1 , exposure time was 20ms, number of scans was 1, and excitation intensity was 1.5mW.

[0091] like Fig. 9 As shown, Fig. 9 This is a Raman spectrum of the ATH-Nar-BC film prepared in Example 1 of the present invention for keeping goat milk fresh; Fig. 9 The left picture in the middle is the experimental group, and the right picture is the blank control group;

[0092] Use 870, 1302 and 1441cm -1 The Raman spectrum data corresponding to these three characteristic peaks are analyzed. -1 The peak between 800-900cm is mainly CS vibration, while the sulfur bond mainly maintains the structural and conformational stability of proteins and peptides. Therefore, the change of this peak can be regarded as the change of protein content. -1 The Raman peak at 1300-1400cm is significantly higher than that of goat milk treated with ATH-Nar-BC. In other words, the protein content in untreated goat milk is higher than that in goat milk treated with ATH-Nar-BC film. -1 The peak at 1302 cm -1 Mainly high-frequency CH vibration, composed of the main molecules of aliphatic compounds. 1460-1410cm -1 The peak at 1441 cm -1 It is mainly attributed to the C=C vibration, which constitutes the double bond of aliphatic hydrocarbons. The change of peak value in this range can be regarded as the change of fat content. As can be seen from the figure, the peak value gradually decreases with the passage of time, and the peak value in untreated goat milk is significantly lower than that in goat milk treated with ATH-Nar-BC film. In short, as time goes by, the degree of deterioration of goat milk treated with ATH-Nar-BC membrane is significantly lower than that of untreated goat milk. ATH-Nar-BC membrane can effectively inhibit the growth of microorganisms in goat milk, and the nutritional components of goat milk treated with this membrane are not significantly damaged. ATH-Nar-BC membrane can extend the shelf life of goat milk.

[0093] Test Example 7:

[0094] Through supervised learning algorithms, we can achieve an overall accuracy of 100% in predicting goat milk spoilage. Fig.10 The accuracy of predicting goat milk spoilage is shown, which provides the possibility for different algorithms to correctly predict goat milk spoilage. The ANN and CNN models show good recognition performance, and the overall accuracy of training performance is 100%, with both accuracy and precision reaching the highest level, which provides a new research path for food preservation.

[0095] A one-dimensional convolutional neural network (CNN) model was used to process Raman spectroscopy data. The overall structure consists of a convolutional layer, a pooling layer, a BN layer, a fully connected layer, and an output layer. The activation function used in the model is the ReLU activation function. The model takes 1349 bands as input and constructs convolutional layers consisting of 32 convolution kernels of size 3×1, 64 convolution kernels of size 3×1, and 128 convolution kernels of size 3×1; a maximum pooling layer of size 2×1 is added after each convolution layer for data dimensionality reduction; a BN layer is added after each maximum pooling layer, and a BN layer and a Dropout layer are added after the fully connected layer to prevent the model from overfitting.

[0096] BP neural network is a learning algorithm that uses an error feedback mechanism to adjust neural network parameters. BP neural network (back propagation artificial neural network, BP-ANN) is a classic machine learning algorithm. After the input spectral data is processed by the input layer activation function, it is converted into a signal in the hidden layer and finally outputs the result in the output layer. If there is a large difference between the output result and the actual value, the error back propagation algorithm will be enabled to reversely transfer the error back to the hidden layer and input layer, update the weights, and iterate the network until the preset training termination condition is reached, so that the network output gradually approaches the actual label, and the spectral data is classified.

Claims

1. A method for preparing an antibacterial film, characterized in that The preparation method of the antibacterial film is specifically completed according to the following steps:

1. dissolving anthocyanin and naringenin in deionized water to obtain a mixed solution of anthocyanin and naringenin; 2. Add bacterial cellulose to a mixed solution of anthocyanin and naringenin, and homogenize it using a homogenizer at room temperature to obtain a mixed solution; cast the mixed solution under closed light to obtain an ATH-Nar-BC film, which is an antibacterial film.

2. The method for preparing an antibacterial film according to claim 1, characterized in that The mass ratio of anthocyanin to naringenin described in step 1 is 1:(0.5-2).

3. The method for preparing an antibacterial film according to claim 1, characterized in that The concentration of anthocyanin in the mixed solution of anthocyanin and naringenin in step 1 is 1 mg / mL to 2 mg / mL.

4. The method for preparing an antibacterial film according to claim 1, characterized in that In step 2, the homogenization time using a homogenizer at room temperature is 3 minutes to 8 minutes.

5. The method for preparing an antibacterial film according to claim 1, characterized in that The mass ratio of bacterial cellulose to the mixed solution of anthocyanin and naringenin in the mixed solution described in step 2 is 1:(0.5-2).

6. Use of an antibacterial film prepared by the preparation method according to claim 1, characterized in that An antibacterial film is used in detecting the freshness of milk.

7. The use of an antibacterial film according to claim 6, characterized in that Raman spectroscopic data of milk were collected using 870, 1302 and 1441 cm -1 These three characteristic peaks are used to analyze the quality of goat milk. By collecting Raman spectral data of milk and combining it with machine learning, the accuracy of detecting the freshness of milk can reach 100%; the milk is goat milk.

8. The use of an antibacterial film according to claim 7, characterized in that The machine learning method is an ANN algorithm or a CNN algorithm.

9. Use of an antibacterial film prepared by the preparation method according to claim 1, characterized in that An antibacterial film is used for photocatalytic antibacterial.

10. Use of an antibacterial film prepared by the preparation method according to claim 1, characterized in that An antibacterial film is used to prepare an intelligent food packaging film system that can monitor the freshness of milk and extend the shelf life of milk.

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