Research on the Preparation of Antibacterial Film and Its Application in Milk Preservation and Quality Monitoring

Abstract

This invention relates to the preparation method and application of an antibacterial film in milk preservation and quality monitoring. The purpose of this invention is to address the limitations of existing methods that use bacterial cellulose alone, which suffer from insufficient mechanical properties and lack of antibacterial activity, resulting in limited application in food preservation. It also addresses the poor bioavailability of existing anthocyanins and their susceptibility to degradation under conditions such as pH, heat treatment, and metal ions. The method involves: 1. Preparing a mixed solution of anthocyanins and naringenin; 2. Adding bacterial cellulose and casting under dark conditions. The antibacterial film prepared by this invention is used in detecting milk freshness, collecting Raman spectral data of the milk at 870, 1302, and 1441 cm⁻¹. ‑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%. It can also be used for photocatalytic antibacterial and intelligent food packaging film systems.

Description

Technical Field

[0001] This invention relates to methods for preparing thin films and their applications. Background Technology

[0002] Foodborne illnesses and food spoilage have been problems throughout human history, and despite years of innovation and technological advancements, food safety in the food service 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 annually in the United States. In this context, foodborne illness is defined as disease caused by contaminated food or beverages, primarily by various bacteria or their toxins, viruses, and parasites, and is a significant public health concern in many countries. Improper food handling is one of the leading causes of foodborne illnesses; contaminated food can lead to up to 600 million different foodborne illnesses, resulting in numerous health-related consequences such as death, disability, neurological disorders, and kidney failure. Furthermore, these illnesses have substantial socioeconomic impacts, reducing national economic productivity, harming trade and tourism, and increasing costs for society, the agri-food industry, and governments.

[0003] Staphylococcus aureus is one of the most common highly pathogenic pathogens. Food contamination by Staphylococcus aureus, followed by the secretion of enterotoxins, is the main cause of food poisoning. These highly pathogenic bacteria spread widely and rapidly, easily causing food poisoning and various inflammatory responses, posing a challenge to public health management. Food packaging can effectively prevent chemical contamination, extend shelf life, and reduce the risk of foodborne illnesses, thereby achieving food safety, facilitating handling and transportation, and providing convenience for consumers. A wide variety of materials, including plastics, glass, metals, paper, and their composites, have been used in food packaging. Appropriate materials can effectively isolate external factors from food, slow down the spoilage process, and inhibit or kill the growth of pathogenic bacteria. Therefore, developing new environmentally friendly and biodegradable food packaging materials has become an urgent problem to be solved in the field of food science.

[0004] Bacterial cellulose (BC) is a natural polymer material synthesized by aerobic bacteria such as *Acetobacter*, *Agrobacterium*, and *Rhizobium*, with a chemical composition similar to natural (plant) cellulose. The nanostructure of BC determines its physical and mechanical properties. Compared to plant cellulose, BC is thinner, and its 3D network of woven nanofibers increases its surface area to volume ratio, enabling strong interactions with neighboring components. It also offers relatively outstanding mechanical strength, high polymerization and crystallinity (approximately 90%), and water retention capacity. Furthermore, its high purity, absence of free lignin, hemicellulose, pectin, etc., non-toxicity, and biodegradability have attracted considerable attention, making it a promising candidate for applications in medicine, food, and other fields. It is worth noting that BC, when used alone, suffers from insufficient mechanical properties and a lack of antibacterial activity, limiting its application in food preservation. Therefore, it needs to be compounded with other polymer materials to improve its mechanical properties and expand its practicality in food preservation and its application range in the field of polymer materials.

[0005] Anthocyanins (ATH) are water-soluble natural pigments widely found in plants, metabolized from phenylalanine, and are the main coloring substances in plants and fruits. Anthocyanins are increasingly popular as colorants in the food industry and can serve as a substitute for synthetic colorants. In addition, anthocyanins are effective antioxidants in vitro. However, the bioavailability of anthocyanins is very poor, only about 1%, and they are easily degraded under conditions such as pH, heat treatment, and metal ions, limiting their applications. Summary of the Invention

[0006] The purpose of this invention is to address the problems of insufficient mechanical properties and lack of antibacterial activity when using bacterial cellulose alone in existing methods, which limit its application in the field of food preservation, as well as the poor bioavailability of existing anthocyanins and their easy degradation under conditions such as pH, heat treatment, and metal ions. The invention provides an application study of antibacterial film preparation and its method for dairy product preservation and quality monitoring.

[0007] A method for preparing an antibacterial film, specifically comprising the following steps:

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

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

[0010] An antibacterial film is used to detect the freshness of milk.

[0011] An antibacterial film for photocatalytic antibacterial use.

[0012] An antibacterial film is used to prepare an intelligent food packaging film system that integrates monitoring milk freshness and extending milk shelf life.

[0013] The principle of this invention:

[0014] I. Naringenin (Nar) is the aglycone of naringin, belonging to the flavonoid class. It is a relatively safe and non-toxic bioactive compound, mainly found in citrus fruits such as lemons, oranges, tangerines, and grapefruits. Naringenin is soluble in ethanol, ether, and benzene, and possesses many biological and pharmacological abilities, such as antioxidant, antibacterial, and anti-inflammatory properties. However, its functional applications are limited by its low lipophilicity and low hydrophilicity. This invention utilizes a synergistic combination of naringenin (Nar) with bacterial cellulose (BC) and anthocyanins (ATH) to achieve food preservation, thereby developing a more sensitive food packaging film.

[0015] II. Raman spectroscopy, as a non-destructive analytical technique, can provide detailed information about the molecular structure and chemical composition of substances; deep machine learning can process and analyze massive datasets, extract valuable information, and make predictions; Raman spectroscopy combined with machine learning algorithms shows 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 spoilage; this invention utilizes the latest research progress in predicting goat milk spoilage during preservation using a Raman-machine learning model, including model construction and validation; thus providing a new, efficient, accurate, and reliable method for goat milk preservation technology;

[0016] Third, this invention uses bacterial cellulose as the base of the sterilization and preservation film, loads anthocyanins and naringenin onto the surface of the bacterial cellulose film, applies photocatalytic antibacterial treatment, and performs deep machine learning analysis on its preservation process; this process aims to build a machine learning-based intelligent food packaging film system that integrates monitoring food freshness and extending food shelf life.

[0017] Advantages of this invention:

[0018] I. Raw Material Safety: Anthocyanins are commonly used as food coloring agents in everyday beverages and foods. Naringin is a natural product derived from plants and animals, with broad application potential in the food and pharmaceutical fields. Its impact on the environment and human health has been extensively studied. Bacterial fiber is a natural inert material synthesized by bacteria and has been widely used in pharmaceuticals, food, and other fields. In short, this product is characterized by being free of metal elements, safe, and environmentally friendly.

[0019] II. Simple synthesis method: Anthocyanins and naringenin are well dispersed and dissolved in bacterial cellulose solution through simple stirring and homogenization;

[0020] 3. Visual indication of goat milk freshness: The antibacterial film is affixed to the inside of the box lid and sealed. During the spoilage process, fats and proteins in the goat milk are decomposed, causing the product to coagulate and separate, while also increasing the pH value in the packaging and causing the film to change color. The goat milk is evenly divided into equal portions and placed in the box. The inside of the box lid is covered with the antibacterial film and placed in the same environment as the label (the antibacterial film prepared in this invention, with a size of 1cm×1cm). It is sealed and stored at 4℃ for 14 days. It is taken out and observed every eight hours. The label is light pink before the experiment begins. As the storage time increases, the label begins to turn pink and eventually turns purple.

[0021] IV. High sterilization efficiency: Under photocatalytic conditions (xenon lamp irradiation), it can efficiently kill Staphylococcus aureus within 20 minutes; the main sterilization mechanism is that naringenin on the film generates ROS during irradiation, which damages the surface of bacteria; it causes their cell membranes to rupture, thereby losing their original morphology and function, ultimately leading to their death; the film has good physical properties; the composite film has good mechanical properties, hydrophilicity and water retention, and is suitable for use in packaging materials;

[0022] V. Small detection range and high prediction accuracy: Raman technology-deep machine learning can more accurately detect the spoilage 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 accuracy. Attached Figure Description

[0023] Figure 1 Color and UV-Vis spectra of the ATH-Nar mixed solution, ATH solution, and Nar solution prepared for this invention at pH 3-10;

[0024] Figure 2 The color diagram of the ATH-Nar-BC film prepared in Example 1 of this invention under pH conditions of 3-10;

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

[0026] Figure 4 The image shows the bactericidal efficiency of the ATH-Nar-BC film prepared in Example 1 of this invention.

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

[0028] Figure 6The mechanical properties of the ATH-Nar-BC thin film prepared in Example 1 of this invention are shown in the figure.

[0029] Figure 7 The image shows the water contact angle of the ATH-Nar-BC thin film prepared in Example 1 of this invention.

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

[0031] Figure 9 The Raman spectrum of the ATH-Nar-BC film prepared in Example 1 of this invention for preserving goat milk;

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

[0033] Figure 11 Here is a diagram of the CNN model structure;

[0034] Figure 12 This is a diagram of the BP-ANN model structure. Detailed Implementation

[0035] Specific Implementation Method 1: This implementation method describes a method for preparing an antibacterial film, which is specifically completed according to the following steps:

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

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

[0038] Specific Implementation Method Two: This implementation method differs from Specific Implementation Method One in that the mass ratio of anthocyanins to naringenin in step one is 1:(0.5-2). The other steps are the same as in Specific Implementation Method One.

[0039] Specific Implementation Method Three: This implementation method differs from Specific Implementation Method One or Two in that the concentration of anthocyanins in the mixed solution of anthocyanins and naringenin described in step one is 1 mg / mL to 2 mg / mL. The other steps are the same as in Specific Implementation Method One or Two.

[0040] Specific Implementation Method Four: This implementation method differs from Specific Implementation Methods One to Three in that the homogenization time using a homogenizer at room temperature in step two is 3 to 8 minutes. The other steps are the same as in Specific Implementation Methods One to Three.

[0041] Specific Implementation Method Five: This implementation method differs from Specific Implementation Methods One to Four in that the mass ratio of bacterial cellulose to the mixed solution of anthocyanins and naringenin in the mixed solution described in step two is 1:(0.5-2). The other steps are the same as in Specific Implementation Methods One to Four.

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

[0043] Specific Implementation Method Seven: This implementation method differs from Specific Implementation Methods One to Six in that: by collecting Raman spectral data of milk and combining it with machine learning, the accuracy of detecting milk freshness can reach 100%; the milk mentioned is goat milk. Other steps are the same as in Specific Implementation Methods One to Six.

[0044] Specific Implementation Method Eight: This implementation method differs from Specific Implementation Methods One to Seven in that the machine learning method used is either the ANN algorithm or the CNN algorithm. The other steps are the same as in Specific Implementation Methods One to Seven.

[0045] Specific Implementation Method Nine: This implementation method is an antibacterial film used for photocatalytic antibacterial treatment.

[0046] Specific Implementation Method 10: This implementation method is an antibacterial film used to prepare an intelligent food packaging film system that integrates monitoring the freshness of milk and extending its shelf life.

[0047] The beneficial effects of the present invention are verified using the following embodiments:

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

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

[0050] The mass ratio of anthocyanins and naringenin mentioned in step one is 1:1;

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

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

[0053] In step two, the mass ratio of bacterial cellulose to the mixed solution of anthocyanins and naringenin in the mixed solution is 1:1.

[0054] Compare with Example 1: The preparation method of ATH solution is carried out according to the following steps:

[0055] Anthocyanins (ATH) are dissolved in deionized water to obtain an anthocyanin solution (ATH solution).

[0056] Compare with Example 2: The preparation method of Nar solution is specifically carried out according to the following steps:

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

[0058] Figure 1 Color and UV-Vis spectra of the ATH-Nar mixed solution, ATH solution, and Nar solution prepared for this invention at pH 3-10;

[0059] from Figure 1 It can be seen that: the color changes of individual and mixed materials in different buffer solutions; when the pH value increases from 3 to 10, the color of the individual pigment and mixed pigment solutions changes from pink to purple; the color changes in the figure show that the color of the mixed solution becomes richer; the color changes are more obvious at pH values ​​of 5, 6 and 7; 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 spoilage.

[0060] Figure 2 The color diagram of the ATH-Nar-BC film prepared in Example 1 of this invention under pH conditions of 3-10;

[0061] from Figure 2 It can be seen that the color of the film is different at different pH values. At pH 3, the ATH-Nar-BC film is pink. As the pH value increases, the color gradually deepens, turns into purple, and finally turns into purplish brown, with obvious color gradient changes.

[0062] Figure 3 This is a scanning electron microscope image of the ATH-Nar-BC thin 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 exhibits a dense and intricately interwoven fibrous structure under a scanning electron microscope.

[0064] Test Example 1:

[0065] Staphylococcus aureus was selected as the indicator bacterium. All glassware and culture media were inactivated by high temperature before use. First, through inoculation, streaking, bacterial proliferation, centrifugation, washing, and dilution, 10⁻⁶ bacteria were obtained.8 A bacterial suspension of CFU / mL was prepared. Then, the antibacterial film (1cm × 1cm) prepared in Example 1 was placed in a 6-well plate, and 100 μL (1 × 10⁻⁶ CFU / mL) of the film was added. 8 A bacterial solution of CFU / mL was dropped onto a membrane. A transparent 6-well plate was then placed under a xenon lamp (λ>420nm, light intensity: 200mW / cm²). -2 Irradiate the sample every 20 minutes for a total of 2 times. After irradiation, transfer the mixture and the membrane to 900 μL of physiological saline, mix, and then apply 100 μL of the mixture onto an LB plate. Then incubate the LB plate at 37°C for 24 h.

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

[0067] Figure 4 The image shows the bactericidal efficiency of the ATH-Nar-BC film prepared in Example 1 of this invention.

[0068] from Figure 4 It can be seen that the ATH-Nar-BC film prepared in Example 1 of this invention can kill 10 within 60 minutes. 6 The presence of CFU / mL Staphylococcus aureus indicates that the ATH-Nar-BC membrane prepared in this invention has a strong antibacterial efficiency.

[0069] Test Example 2:

[0070] Staphylococcus aureus was selected as the indicator bacterium. All glassware and culture media were inactivated by high temperature before use. First, through inoculation, streaking, bacterial proliferation, centrifugation, washing, and dilution, 10⁻⁶ bacteria were obtained. 8 A bacterial suspension of CFU / mL was prepared. Then, the antibacterial film (denoted as BC-ATH-NAR) (1cm × 1cm) prepared in Example 1 was placed in a 6-well plate, and 100 μL (1 × 10⁻⁶ CFU / mL) of the film was added. 8 A bacterial solution of CFU / mL was dropped onto a membrane. A transparent 6-well plate was then placed under a xenon lamp (λ>420nm, light intensity: 200mWcm²). -2 Irradiation was performed under light every 20 minutes for a total of two irradiations. Afterward, the mixture and membrane were transferred to 900 μL of physiological saline, mixed, and 100 μL was spread onto an LB plate. The LB plate was then incubated at 37°C for 24 h; irradiation was performed for 0 min and 60 min respectively, followed by staining with SYTO 9 / PI dye. The results were observed using a laser confocal microscope. Figure 5 As shown;

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

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

[0073] from Figure 5 It can be observed that as the illumination time increases, the red fluorescence signal gradually increases, while the green fluorescence gradually weakens, indicating that the number of dead cells gradually increases. When the illumination time reaches 60 minutes, the red fluorescence signal dominates, indicating that the vast majority of bacteria have died by this point. Therefore, it can be inferred that the ATH-Nar-BC membrane kills bacteria by disrupting their cell membranes.

[0074] Test Example 3:

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

[0076] Figure 6 The mechanical properties of the ATH-Nar-BC thin film prepared in Example 1 of this invention are shown in the figure.

[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 the tensile strength eventually increases with increasing pigment concentration, possibly due to hydrogen bonding between the pigment and the matrix. The trend of elongation at break is similar to that of tensile strength, which is due to the cross-linking of the phenolic hydroxyl groups in ATH / Nar with the substrate, resulting in reduced flexibility. In summary, pigment-doped ATH-Nar-BC films exhibit high tensile strength, but limited elongation at break.

[0078] Test Example 4:

[0079] The hydrophobicity of the film was determined using a water contact angle meter;

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

[0081] Figure 7 The image shows the water contact angle of the ATH-Nar-BC thin film prepared in Example 1 of this invention.

[0082] from Figure 7It can be seen that the ATH-BC film modified with pigment has a smaller water contact angle. Subsequently, with the addition of Nar, more hydroxyl groups are provided, which 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 determined the water vapor transmission rate (WVP) of the membrane. The membrane was sealed in a permeation cup containing CaCl2 and placed in a desiccator. The container was removed and weighed at different times. WVP was calculated using the following formula:

[0085] WVP=(Δm×d) / (S×Δt×Δp)

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

[0087] Figure 8 This is a water vapor transmission rate diagram of the ATH-Nar-BC thin 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 membrane without pigments, indicating that the composite membrane improves the water-blocking ability; this is beneficial to improving the water retention capacity of the membrane.

[0089] Test Example 6:

[0090] Goat milk was divided into 50 ml portions and placed in sterile containers, resulting in 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 received no treatment. The films were affixed to the inside of the container lids and sealed. A preservation label made of ATH-Nar-BC was placed in each sterile container. This test determined the Raman spectra of goat milk stored for different times after film treatment. Goat milk samples were dropped onto a sample chip, placed on a stage, and the surface microstructure of the goat milk was observed under a 20x objective lens, and Raman spectral data were collected. The Raman spectral wavelength range was 500-30000 cm⁻¹. -1 The exposure time was 20ms, the number of scans was 1, and the excitation intensity was 1.5mW.

[0091] like Figure 9 As shown, Figure 9 The Raman spectrum of the ATH-Nar-BC film prepared in Example 1 of this invention for preserving goat milk; Figure 9 The left image shows the experimental group, and the right image shows the blank control group;

[0092] Using 870, 1302 and 1441cm -1 We analyzed the Raman spectral data corresponding to these three characteristic peaks. The 800-900 cm⁻¹ peaks appearing in the curve... -1 The peaks between these peaks are primarily due to CS vibrations, while disulfide bonds mainly maintain the structural and conformational stability of proteins and peptides. Therefore, changes in this peak can be considered as changes in protein content. After 40 hours, untreated goat milk showed a peak at 800-900 cm⁻¹. -1 The Raman peak at 1300-1400 cm⁻¹ was significantly higher than that of ATH-Nar-BC treated goat milk. This means that the protein content in untreated goat milk was higher than that in goat milk treated with the ATH-Nar-BC membrane. -1 The peak value that appeared between was 1302cm. -1 It is mainly composed of high-frequency CH vibrations, and is mainly composed of aliphatic compound molecules. 1460-1410 cm⁻¹ -1 The peak value that appeared between them was 1441cm. -1 This is primarily attributed to the C=C vibration, which forms the double bond in aliphatic hydrocarbons. Changes in the peak value within this range can be considered as changes in fat content. As shown in the figure, the peak value gradually decreases over time, with the peak value in untreated goat milk being significantly lower than that in goat milk treated with the ATH-Nar-BC membrane. In summary, over time, the degree of spoilage in goat milk treated with the ATH-Nar-BC membrane is significantly lower than that in untreated goat milk. The ATH-Nar-BC membrane effectively inhibits the growth of microorganisms in goat milk, and the nutritional components of goat milk treated with this membrane are not significantly damaged. The ATH-Nar-BC membrane can extend the shelf life of goat milk.

[0093] Test Example 7:

[0094] Using supervised learning algorithms, we can achieve an overall accuracy of 100% in predicting goat milk spoilage. Figure 10 The accuracy of predicting goat milk spoilage was demonstrated, providing a possibility for different algorithms to correctly predict goat milk spoilage. The ANN and CNN models showed good recognition performance, with an overall training accuracy of 100%, achieving the highest levels of accuracy and precision. This provides a new research avenue for food preservation.

[0095] A one-dimensional convolutional neural network (CNN) model was used to process Raman spectral data. The overall structure consists of convolutional layers, pooling layers, batch normalization (BN) layers, fully connected layers, and an output layer. The ReLU activation function was used in the model. The model took 1349 bands as input and constructed convolutional layers consisting of 32, 64, and 128 convolutional kernels of size 3×1, respectively. A 2×1 max pooling layer was added after each convolutional layer for dimensionality reduction. A batch normalization (BN) layer was added after each max pooling layer, and a BN layer and a dropout layer were added after the fully connected layers to prevent overfitting.

[0096] Backpropagation (BP) neural networks are learning algorithms that use an error feedback mechanism to adjust the network parameters. A classic machine learning algorithm, BP-ANN takes input spectral data, processes it through an activation function in the input layer, converts it into a signal in the hidden layer, and finally outputs the result in the output layer. If the output differs significantly from the actual value, the backpropagation algorithm is activated to propagate the error back to the hidden and input layers, updating the weights and iteratively optimizing the network until a preset training termination condition is met. This process gradually brings the network output closer to the actual label, achieving the classification of the spectral data.

Claims

1. A method for preparing an antibacterial film, characterized in that... The antibacterial film is prepared by following these steps:

1. Dissolve anthocyanins and naringenin in deionized water to obtain a mixed solution of anthocyanins and naringenin; 2. Add bacterial cellulose to a mixed solution of anthocyanins and naringenin, homogenize the solution at room temperature using a homogenizer to obtain a mixed solution; cast the mixed solution under dark conditions 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 anthocyanins and naringenin mentioned in step one is 1:(0.5-2).

3. The method for preparing an antibacterial film according to claim 1, characterized in that... The concentration of anthocyanins in the mixed solution of anthocyanins and naringenin described in step one 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 two, the homogenization time using a homogenizer at room temperature is 3 to 8 minutes.

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

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

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

8. The application of the antibacterial film according to claim 7, characterized in that... The machine learning method is either the ANN algorithm or the CNN algorithm.

9. The application of an antibacterial film prepared by the preparation method according to claim 1, characterized in that... An antibacterial film for photocatalytic antibacterial use.

10. The application 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 integrates monitoring milk freshness and extending milk shelf life.

Images