Preparation of tobacco bud inhibitor based on eugenol and synergistic method of reducing dosage

Abstract

The application provides a eugenol-based tobacco bud inhibitor preparation and a compounding reduction-increase efficiency method thereof, and belongs to the technical field of tobacco bud inhibitor preparation. The specific process comprises the following steps: first, forming a clathrate of the eugenol mixture and beta cyclodextrin to realize molecular level protection; then, mixing the clathrate with gelatin and arabic gum to prepare an aqueous solution, adding chitosan to form a stable emulsion, and precisely controlling the particle size by using microemulsion technology; then, adding ultraviolet absorbers and antioxidants to enhance the environmental stability, and preparing core-shell structure microcapsules by optimizing the parameters of the spray drying method; finally, mixing the microcapsules with corn starch and dispersants to form the final slow-release product, thereby successfully solving the technical problems of poor stability, large volatile loss and limited application of the eugenol mixture used for tobacco bud inhibitor, and reducing the use of chemical bud inhibitor 2-chloro-3, 3- dimethyl-1-propene.

Description

Technical Field

[0001] This invention belongs to the field of tobacco bud inhibitor preparation technology, specifically, it relates to a method for preparing a tobacco bud inhibitor based on eugenol and its compounding method for reducing dosage and enhancing efficacy. Background Technology

[0002] Tobacco bud suppression is a crucial step in tobacco cultivation, promoting normal stem and leaf development by inhibiting axillary bud germination, thereby improving tobacco quality and yield. Traditional tobacco bud suppression primarily involves manual topping and bud removal, but this method is labor-intensive, inefficient, and prone to plant damage. With the modernization of agriculture, chemical bud suppressants such as butylated methylphenidate are widely used, but these suffer from problems such as high dosage, high residue, and short-lasting effects, posing potential threats to the environment and human health. In recent years, natural plant-derived bud suppressants have gained attention, among which eugenol, as a natural phenolic compound, exhibits good bud-suppressing activity and biocompatibility. However, eugenol's volatility, high photosensitivity, and poor stability limit its practical application. Currently, the market lacks green and environmentally friendly bud suppressant products that can maintain high bud-suppressing efficacy while significantly reducing the amount of chemical pesticides used. Therefore, developing a novel tobacco bud suppressant based on natural eugenol, using advanced formulation technology to improve its stability and slow-release properties, and combining it with traditional chemical bud suppressants to achieve reduced dosage and enhanced efficacy is of great significance. Summary of the Invention

[0003] In view of this, the present invention provides a method for preparing a tobacco sprout inhibitor based on eugenol and its compounding method for reducing dosage and enhancing efficacy. This method can solve the problem that the existing technology lacks efficient formulation technology of eugenol mixtures as tobacco sprout inhibitors, which limits their application and makes it difficult to achieve stable and long-lasting tobacco sprout inhibitory effects.

[0004] The present invention is implemented as follows: A method for preparing a tobacco sprout inhibitor based on eugenol, provided in the first aspect of the present invention, includes: mixing an eugenol mixture with β-cyclodextrin to form an eugenol inclusion complex; mixing the eugenol inclusion complex with gelatin and gum arabic and adding deionized water to prepare an aqueous solution; adding chitosan to the aqueous solution and stirring to form an emulsion; treating the emulsion using microemulsification technology to control the particle size within a specified range, the microemulsification process following the nanoagglomeration kinetic equation; adding an ultraviolet absorber and an antioxidant to the microemulsion and stirring; preparing microcapsules from the microemulsion using a spray drying method, and optimizing spray parameters using a microcapsule efficiency adaptive network model; mixing the microcapsules with corn starch and adding a dispersant to prepare a sustained-release tobacco sprout inhibitor product; and using a parameter adaptive adjustment function to calculate parameter adjustment factors and adjust parameters during the microcapsule production process.

[0005] The step of mixing the eugenol mixture with β-cyclodextrin to form an eugenol inclusion complex specifically involves mixing the eugenol mixture and β-cyclodextrin at a mass ratio of 1:5 and stirring at 75°C for 180 minutes to form the eugenol inclusion complex. The eugenol mixture is a mixture of eugenol and the chemical sprout inhibitor sec-butylamine, with a mass fraction ratio of 1–2:1–2.

[0006] Specifically, the step of mixing the eugenol inclusion complex with gelatin and gum arabic and adding deionized water to prepare an aqueous solution involves mixing the eugenol inclusion complex with gelatin and gum arabic in a mass ratio of 2:1:1 and adding deionized water to prepare an aqueous solution with a mass fraction of 15%.

[0007] The step of adding chitosan to the aqueous solution and stirring to form an emulsion specifically involves adding 0.5% chitosan by mass to the aqueous solution and stirring at 300 rpm for 90 minutes to form an emulsion.

[0008] Specifically, the step of treating the emulsion with microemulsification technology involves treating the emulsion at 50°C for 30 minutes using microemulsification technology to control the particle size to below 50 μm.

[0009] Specifically, the step of adding the ultraviolet absorber and antioxidant to the microemulsion and stirring involves adding 0.8% by mass of the ultraviolet absorber and 0.5% by mass of the antioxidant to the microemulsion and continuing to stir for 60 minutes.

[0010] The step of preparing microcapsules from microemulsions by spray drying specifically involves preparing microcapsules from microemulsions by spray drying, with an inlet temperature of 180°C and an outlet temperature of 85°C.

[0011] The step of mixing microcapsules with corn starch and adding a dispersant to prepare a sustained-release tobacco bud inhibitor product specifically involves mixing the microcapsules with corn starch at a mass ratio of 3:1, adding a dispersant with a mass fraction of 0.3%, and preparing the final sustained-release tobacco bud inhibitor product.

[0012] Specifically, the step of using a parameter adaptive adjustment function to calculate the parameter adjustment factor and adjust the parameters in the microcapsule production process involves using a parameter adaptive adjustment function to calculate the parameter adjustment factor, and then adjusting the feed rate parameter and atomizing airflow ratio parameter in the microcapsule production process according to the parameter adjustment factor.

[0013] The β-cyclodextrin refers to cyclic oligosaccharides with a hydrophobic inner cavity and a hydrophilic outer surface, which can form host-guest inclusion complexes to protect the eugenol mixture from oxidative degradation.

[0014] The gelatin and gum arabic serve as the wall materials of the polyelectrolyte complex, forming a dense network structure through electrostatic interactions to reduce the volatilization loss of the eugenol mixture. The chitosan is a natural polymer compound obtained by deacetylation of chitin, which enhances the mechanical strength and biocompatibility of the microcapsules.

[0015] The microemulsion technology refers to a processing technique that uses high shear force to shear oil-water two-phase substances into tiny droplets, so that the eugenol mixture is uniformly dispersed in the aqueous phase, thereby improving its stability.

[0016] The nanoagglomeration kinetic equation refers to a mathematical model describing the aggregation behavior of microparticles in a liquid medium. Its input parameters include initial microparticle concentration parameters, aggregation rate constant parameters, shear force coefficient parameters, stability factor parameters, and surfactant concentration parameters. The output parameters are microparticle concentration parameters and particle size distribution parameters.

[0017] The ultraviolet absorber refers to 2-hydroxy-4-methoxybenzophenone, which can absorb ultraviolet radiation and prevent the eugenol mixture from being degraded by light; the antioxidant refers to tert-butylhydroxyanisole, which can capture free radicals and inhibit the oxidation reaction of the eugenol mixture.

[0018] The microcapsule efficiency generation adaptive network model is a hybrid architecture combining multilayer convolutional neural networks and recurrent neural networks. It includes convolutional layers to extract microemulsion features, bidirectional long short-term memory networks to capture the dynamic effects of temperature changes on the drying process, and fully connected layers to output spray parameters.

[0019] The second aspect of this invention provides a method for compounding a tobacco sprout inhibitor based on eugenol with reduced dosage and enhanced efficacy, comprising the following steps: Eugenol and β-cyclodextrin are mixed at a mass ratio of 1:5 and stirred at 75°C for 180 minutes to form an eugenol inclusion complex; the eugenol inclusion complex is mixed with gelatin and gum arabic at a mass ratio of 2:1:1, and deionized water is added to prepare a 15% aqueous solution; 0.5% chitosan is added to the aqueous solution, and the mixture is stirred at 300 rpm for 90 minutes to form an emulsion; the emulsion is treated at 50°C using microemulsification technology for 30 minutes to control the particle size to below 50 μm; 0.8% ultraviolet absorber and 0.5% antioxidant are added to the microemulsion, and stirring is continued for 60 minutes; the microemulsion is spray-dried to prepare microcapsules, with an inlet temperature of 180°C and an outlet temperature of 85°C. The microcapsules were mixed with corn starch at a mass ratio of 3:1, and a dispersant with a mass fraction of 0.3% was added to prepare eugenol microcapsule sprout inhibitor; the eugenol microcapsule sprout inhibitor was compounded with terbufotalin at a mass ratio of 10%-90%:90%-10% to prepare a compound tobacco sprout inhibitor.

[0020] The microemulsion technology employs a high-pressure homogenizer for staged processing: the first stage is processed at 10 MPa for 10 minutes, the second stage at 15 MPa for 10 minutes, and the third stage at 20 MPa for 10 minutes. The ultraviolet absorber is 2-hydroxy-4-methoxybenzophenone, the antioxidant is tert-butylhydroxyanisole, and the dispersant is polyvinylpyrrolidone. The optimal mass ratio of the eugenol microcapsule sprout inhibitor to sec-butylamine is 50%:50.

[0021] In the compound bud inhibitor, eugenol achieves sustained release through dual protection of β-cyclodextrin inclusion and microcapsule, forming a synergistic effect with sec-butylamine. While maintaining the bud-inhibiting effect, the amount of chemical bud inhibitor sec-butylamine used is reduced by 50%, the bud-inhibiting effect is extended to more than 35 days, and the total residue in tobacco leaves is reduced by more than 30%.

[0022] The mechanism of reducing dosage and enhancing efficacy of chemical reagents based on the combination of eugenol and sec-butylamine is mainly reflected in the following aspects:

[0023] Molecular synergistic mechanism: Eugenol and terbufoten have different bud-inhibiting mechanisms, forming a complementary synergistic effect. Terbufoten, as a cell division inhibitor, mainly inhibits the initial germination of axillary buds by interfering with microtubule polymerization and blocking the cell division process. Eugenol, on the other hand, inhibits bud development at the metabolic level by inhibiting auxin polar transport and interfering with cell wall synthase activity. The two active ingredients act through different biochemical pathways, producing a synergistic effect greater than the sum of its parts (1+1>2), allowing a low-concentration combination to achieve the effect of a single high-concentration chemical bud-inhibiting agent.

[0024] Sustained-release coordination mechanism: Through β-cyclodextrin inclusion and microencapsulation technology, eugenol achieves precise sustained-release control, with its release curve complementing that of sec-butylamine. sec-butylamine, at a high initial concentration, provides a potent immediate sprout-inhibiting effect, but its activity gradually decreases over time. During this phase, eugenol microcapsules continuously release the active ingredient, taking over the sprout-inhibiting effect from sec-butylamine, forming a "relay" long-lasting inhibition mode. This temporal coordination avoids the gap period after the fading of the single sprout-inhibiting agent, extending the overall sprout-inhibiting duration.

[0025] Target complementarity mechanism: Butylene primarily acts on key nodes of cell division, exhibiting high sensitivity to rapidly dividing young tissues, but its effect on differentiated tissues is limited. Eugenol, on the other hand, has an inhibitory effect on bud tissues at multiple developmental stages, particularly by influencing hormone signaling and gene expression regulation, thus exerting a sustained impact on the entire bud development process. The complementary targets of these two agents ensure comprehensive inhibition from bud germination to all stages of development, improving the thoroughness and stability of bud suppression.

[0026] Permeation-enhancing mechanism: Microencapsulated eugenol exhibits improved tissue permeability and bioavailability. The polyelectrolyte composite wall material gradually degrades and releases the active ingredient within the plant tissue environment. As a lipid-soluble molecule, eugenol can better penetrate cell membranes and cell walls to reach its intracellular target site. Simultaneously, the presence of eugenol improves the distribution and permeation of terbufos in plant tissues, enhancing the binding efficiency of terbufos with its target protein, thereby achieving the same inhibitory effect at lower concentrations.

[0027] Resistance mitigation mechanism: Long-term use of chemical shoot inhibitors alone can easily lead to the development of adaptation and resistance in plants. The combined use of multiple agents reduces the likelihood of plants developing resistance to a single chemical component through the synergistic effect of their multiple mechanisms of action. Eugenol, as a natural component, has multi-component characteristics and a complex mode of action, making it difficult for plants to develop specific resistance mechanisms. This resistance mitigation effect allows even low concentrations of butylparaben to remain effective, avoiding the need to increase dosage due to resistance development.

[0028] Stability Enhancement Mechanism: β-cyclodextrin inclusion and microencapsulation technology significantly improve the stability of eugenol, reducing activity loss caused by environmental factors such as light and oxidation. Stable eugenol can continue to exert its effects throughout the entire bud-inhibiting period, compensating for the natural decline in the flexibility of sec-butyl. Simultaneously, the protective effect of the microencapsulation carrier indirectly improves the overall stability of the compound system, allowing the active ingredients to exert their bud-inhibiting effect more fully, thus achieving the goal of reducing dosage without reducing efficacy.

[0029] Through the aforementioned multi-level synergistic mechanism, the compound sprout inhibitor achieves a significant reduction in the amount of chemical reagents while maintaining or even enhancing the sprout-inhibiting effect, providing an important technical path for green agricultural development and environmental protection.

[0030] In summary, this invention successfully overcomes key technical obstacles in the application of eugenol mixtures as tobacco sprout inhibitors through a dual protection technology of β-cyclodextrin inclusion and microcapsule encapsulation, combined with an intelligent parameter control system. The microcapsule sprout inhibitor product prepared by this method achieves efficient encapsulation and multi-layered protection of the eugenol mixture, significantly reducing its volatilization loss and improving its stability against light and oxidation. This invention employs gelatin-gum arabic composite wall material and chitosan reinforcement technology to form core-shell structured microcapsules with excellent mechanical strength, enabling the slow release of the eugenol mixture and ensuring a sustained and stable sprout inhibitory effect. The application of microemulsification technology and nanoagglomeration kinetics equations allows for precise control of particle size below 50 μm, significantly improving the dispersion uniformity and bioavailability of the eugenol mixture, and solving the technical problems of poor stability, high volatilization loss, and limited application of eugenol mixtures as tobacco sprout inhibitors. Attached Figure Description

[0031] Figure 1 This is a flowchart of the method of the present invention.

[0032] Figure 2 This is a diagram showing the effect of applying the simple eugenol mixture in Example 2 14 days after application.

[0033] Figure 3 This is a diagram showing the effect of the bud-inhibiting agent applied 14 days after Example 2. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0035] like Figure 1 The diagram shown is a flowchart of a method for preparing a tobacco sprout inhibitor based on eugenol provided by the present invention. This method includes the following steps:

[0036] S01. The eugenol mixture and β-cyclodextrin are mixed at a mass ratio of 1:5 and stirred at 75°C for 180 minutes to form an eugenol inclusion complex.

[0037] S02. The eugenol inclusion complex is mixed with gelatin and gum arabic in a mass ratio of 2:1:1, and deionized water is added to prepare an aqueous solution with a mass fraction of 15%.

[0038] S03. Add 0.5% chitosan by mass to the aqueous solution and stir at 300 rpm for 90 minutes to form an emulsion;

[0039] S04. The emulsion is treated at 50°C for 30 minutes using microemulsification technology to control the particle size to below 50 μm. The microemulsification process follows the nanoagglomeration kinetic equation.

[0040] S05. Add 0.8% by mass of ultraviolet absorber and 0.5% by mass of antioxidant to the microemulsion, and continue stirring for 60 minutes.

[0041] S06. The microemulsion is prepared into microcapsules by spray drying. The drying inlet temperature is 180°C and the outlet temperature is 85°C. The spray parameters are optimized using a microcapsule efficiency generation adaptive network model.

[0042] S07. The microcapsules are mixed with corn starch at a mass ratio of 3:1, and a dispersant with a mass fraction of 0.3% is added to prepare the final slow-release tobacco sprout inhibitor product.

[0043] S08. Calculate the parameter adjustment factor using the parameter adaptive adjustment function, and adjust the feed rate parameter and atomizing airflow ratio parameter in the microcapsule production process according to the parameter adjustment factor.

[0044] Among them, β-cyclodextrin specifically refers to cyclic oligosaccharides with hydrophobic cavities and hydrophilic outer surfaces, which can form host-guest inclusion complexes to protect eugenol mixtures from oxidative degradation;

[0045] Specifically, gelatin and gum arabic are used as wall materials for polyelectrolyte complexes, forming a dense network structure through electrostatic interactions to reduce the volatilization loss of eugenol mixtures.

[0046] Chitosan specifically refers to a natural polymer compound obtained by deacetylation of chitin, which can enhance the mechanical strength and biocompatibility of microcapsules.

[0047] Among them, microemulsion technology specifically refers to the processing technology that uses high shear force to shear oil and water two-phase substances into tiny droplets, so that eugenol mixtures are uniformly dispersed in the aqueous phase and their stability is improved.

[0048] Specifically, the nanoagglomeration kinetic equation refers to a mathematical model describing the aggregation behavior of microparticles in a liquid medium. Its input parameters include the initial concentration of microparticles measured from the emulsion, the aggregation rate constant determined by shear conditions, the shear force coefficient obtained by stirring speed, the stability factor calculated from the polyelectrolyte concentration, and the concentration of added surfactant. The output parameters are the microparticle concentration parameter and the particle size distribution parameter, which are used to adjust the microemulsion treatment time and intensity.

[0049] Among them, the ultraviolet absorber specifically refers to 2-hydroxy-4-methoxybenzophenone, which can absorb ultraviolet radiation and prevent the eugenol mixture from being degraded by light.

[0050] Among them, the antioxidant specifically refers to tert-butylhydroxyanisole, which can capture free radicals and inhibit the oxidation reaction of eugenol mixtures;

[0051] Spray drying specifically refers to the technique of rapidly dehydrating liquid in hot air after atomization to form dry particles, thereby preparing microcapsules with a core-shell structure.

[0052] The minimum spanning tree algorithm specifically refers to a computational method for optimizing the structure of a microcapsule dispersion network. The microcapsule is regarded as a network node, and the interaction force between nodes is the edge weight. The optimal dispersion state is constructed by the minimum spanning tree algorithm. The interaction force is obtained by measuring the surface potential of the microcapsule, and the edge weight is calculated from the distance and charge difference between two microcapsules. The optimal dispersion state is used to guide the amount of dispersant added.

[0053] The microcapsule efficiency generation adaptive network model is specifically structured as a hybrid architecture combining multi-layer convolutional neural networks and recurrent neural networks. It includes convolutional layers to extract microemulsion features, a bidirectional long short-term memory network to capture the dynamic impact of temperature changes on the drying process, and fully connected layers to output spray parameters. The steps for establishing the training dataset for the microcapsule efficiency generation adaptive network model specifically include collecting drying process data of different microemulsion formulations under various spray conditions, recording the correspondence between inlet temperature parameters, outlet temperature parameters, atomization pressure parameters, feed rate parameters, and final microcapsule morphology and quality parameters, and constructing training and validation sets. The training steps for the microcapsule efficiency generation adaptive network model specifically include parameter optimization using an optimizer, setting the learning rate parameter and employing an annealing strategy, setting the batch size parameter, setting the training epochs, using an error function as the loss function, and avoiding overfitting through early stopping.

[0054] The dispersant specifically refers to polyvinylpyrrolidone, which can improve the dispersibility of microcapsules in water and prevent aggregation.

[0055] The specific calculation steps of the parameter adaptive adjustment function include obtaining temperature parameters, humidity parameters, pressure parameters, flow rate parameters, and output parameters of the microcapsule efficiency generation adaptive network model. The temperature parameters are obtained from the temperature sensor of the drying equipment, the humidity parameters are obtained from the ambient humidity sensor, the pressure parameters are obtained from the pressure sensor of the spray system, the flow rate parameters are obtained from the feed pump speed sensor, and the output parameters of the microcapsule efficiency generation adaptive network model are obtained from the microcapsule efficiency generation adaptive network model. The input parameters are weighted through a gating mechanism to generate parameter adjustment factors. The parameter adjustment factors are used to adjust the feed rate parameters and the atomized airflow ratio parameters to achieve dynamic control of microcapsule quality.

[0056] Specifically, the gating mechanism refers to a mathematical method for dynamically adjusting weights. It combines the model output with environmental parameters and generates weight coefficients for each parameter through an activation function. Then, it sums these coefficients with the original parameters to obtain the final parameter adjustment factor.

[0057] The specific implementation methods of the above steps are described in detail below.

[0058] The specific implementation of step S01 involves mixing the eugenol mixture with β-cyclodextrin at a mass ratio of 1:5. Specifically, β-cyclodextrin is first added to the reaction vessel and preheated to 75°C under a constant temperature water bath, maintaining temperature fluctuations within ±2°C. Then, the eugenol mixture is slowly added, and simultaneously, the stirring device is started at 350 rpm for initial stirring for 5 minutes to ensure thorough mixing. The stirring speed is then reduced to 180 rpm and continued for 180 minutes. During this period, samples are collected every 30 minutes for infrared spectroscopy analysis to confirm the inclusion reaction progress. When 2850... When the intensity of the characteristic peak decreases to below 20% of the initial value, the inclusion reaction is considered complete, and eugenol inclusion complexes are formed through intermolecular supramolecular forces. The purpose of this step is to utilize the amphiphilic properties of β-cyclodextrin's hydrophobic inner cavity and hydrophilic outer surface to encapsulate eugenol mixture molecules within the β-cyclodextrin cavity through host-guest inclusion interactions, forming stable inclusion complexes. This effectively protects the eugenol mixtures from oxidative degradation and improves their stability.

[0059] The specific implementation of step S02 involves mixing the above-mentioned eugenol inclusion complex with gelatin and gum arabic at a mass ratio of 2:1:1. Specifically, the gelatin is first preheated in a 60°C water bath for 15 minutes to allow it to fully swell. Simultaneously, gum arabic is fully dissolved in another container at 55°C with a stirring speed controlled at 250 rpm. The dissolved gum arabic solution is then slowly added to the gelatin solution, and stirring continues for 10 minutes. Next, the eugenol inclusion complex is added, followed by deionized water to adjust the total mass fraction of the mixture to 15%. During this process, the pH of the solution is maintained between 4.3 and 4.5. This pH range is below the isoelectric point of gelatin, and gum arabic carries a negative charge, which is conducive to the formation of a stable polyelectrolyte complex. This step utilizes the electrostatic interaction between gelatin and gum arabic to form a dense network structure as the wall material of the microcapsules. The aim is to enhance the mechanical strength and barrier properties of the microcapsule wall material through the polyelectrolyte complexation, reducing the volatilization loss of the eugenol mixture.

[0060] The specific implementation of step S03 involves adding a 0.5% (w / w) chitosan solution to the above aqueous solution. Specifically, the chitosan is first dissolved in a 1% acetic acid solution, and the mixture is stirred for at least 120 minutes to ensure complete dissolution. Then, the chitosan solution is slowly added dropwise to the aqueous solution obtained in step S02 at a rate of 5 ml / min, while simultaneously adjusting the stirring speed to 300 rpm and maintaining this speed for 90 minutes. During this period, the viscosity of the mixture is measured every 15 minutes. When the viscosity stabilizes within the range of 120–150 mPa·s, it indicates that the emulsion formation is stable. This process utilizes the principle of high-energy emulsification, using mechanical shear force to uniformly disperse the eugenol inclusion complex in the continuous phase, forming a stable emulsion. As a natural polymer compound, chitosan enhances the mechanical strength of microcapsules through the cross-linking of amino groups with gelatin carboxyl groups, and further stabilizes the wall material structure and improves biocompatibility through the electrostatic interaction between the positive charge and the negative charge of gum arabic.

[0061] The specific implementation of step S04 involves treating the emulsion at 50°C using microemulsification technology for 30 minutes. Specifically, a high-pressure homogenizer is used to pass the emulsion through a microporous membrane at a pressure of 10 MPa. The first stage of treatment lasts 10 minutes, followed by increasing the pressure to 15 MPa and continuing treatment for another 10 minutes. The final stage pressure is set to 20 MPa and treated for 10 minutes. Dynamic light scattering is used to monitor the particle size in real time, ensuring that the final particle size is controlled below 50 μm, with the median particle size preferably controlled within the range of 25–35 μm. The microemulsification process follows the nanoagglomeration kinetic equation, whose input parameters include the initial particle concentration measured from the emulsion. Aggregation rate constant parameter determined by shear conditions Shear force coefficient parameters obtained from stirring speed Stability factor parameters calculated from polyelectrolyte concentration and the concentration parameters of the added surfactant The output parameter is the particle concentration parameter. and particle size distribution parameters These parameters are used to dynamically adjust the microemulsion treatment time and intensity. The purpose of this step is to shear the oil-water two-phase substances into tiny droplets through high shear force, so that the eugenol mixture is uniformly dispersed in the aqueous phase, improving the stability of the emulsion and laying the foundation for subsequent microcapsule formation.

[0062] The specific implementation of step S05 involves adding 0.8% by mass of the ultraviolet absorber 2-hydroxy-4-methoxybenzophenone and 0.5% by mass of the antioxidant tert-butylhydroxyanisole to the microemulsion. Specifically, the two additives are first dissolved in a small amount of ethanol (not exceeding 5% of the total system volume). Then, the solution is slowly added dropwise to the microemulsion at a rate of 3 ml / min while maintaining a stirring speed of 250 rpm. After the addition is complete, stirring continues for 60 minutes to ensure uniform dispersion of the additives. During this period, the absorbance of the system in the wavelength range of 320–350 nm is monitored using a UV-Vis spectrophotometer. When the absorbance reaches 0.8 or higher, it indicates good dispersion of the ultraviolet absorber. This step utilizes the benzene ring structure of the ultraviolet absorber to absorb ultraviolet radiation energy and convert this energy into heat through a π-electron conjugation system, thereby preventing the degradation of the eugenol mixture due to light exposure. Simultaneously, the antioxidant effectively captures free radicals, blocks free radical chain reactions, inhibits the oxidation reaction of the eugenol mixture, and improves the product's stability and shelf life.

[0063] The specific implementation of step S06 involves preparing microcapsules from the microemulsion using a spray drying method. Specifically, the microemulsion is preheated to 40°C and then pumped into the spray drying equipment at a rate of 20 ml / min using a peristaltic pump. The inlet temperature is set to 180°C, the outlet temperature is controlled at 85°C, the atomization pressure is set to 0.2 MPa, the nozzle diameter is selected to be 0.5 mm, and the drying airflow rate is adjusted to 0.6. / minute. During the drying process, an adaptive network model for microcapsule efficiency generation is used to monitor and optimize spray parameters. This model receives real-time sensor data such as temperature, pressure, and humidity, and uses deep learning algorithms to predict the impact of spray parameters on microcapsule quality. It also dynamically adjusts the feed rate and atomization pressure to maintain microcapsule encapsulation efficiency above 90% and breakage rate below 3%. The purpose of this step is to achieve effective encapsulation and protection of the eugenol mixture by rapidly dehydrating the atomized liquid in hot air to form microcapsules with a core-shell structure.

[0064] The specific implementation of step S07 involves mixing the microcapsules with corn starch at a mass ratio of 3:1, and adding 0.3% (by mass) of polyvinylpyrrolidone (PVP) as a dispersant. Specifically, the microcapsules and corn starch are first dry-mixed in a V-type mixer for 15 minutes, with the mixing uniformity controlled within 3% by sampling tests. Then, the dispersant is dissolved in an appropriate amount of deionized water to prepare a solution, with the amount used controlled at 20% of the total solid weight. This solution is then evenly sprayed onto the mixture, and mixing continues for 10 minutes. The minimum spanning tree algorithm is used to optimize the dispersion network structure. This algorithm treats the microcapsules as network nodes, with the interaction forces between nodes as edge weights. The algorithm constructs the optimal dispersion state, where the interaction forces are obtained by measuring the surface potential of the microcapsules, and the edge weights are calculated from the distance and charge difference between two microcapsules. The optimal dispersion state guides the amount of dispersant added. Finally, the mixture is dried at 40°C until the moisture content does not exceed 5%, and particles with a particle size range of 75–150 μm are screened to obtain the final slow-release tobacco sprout inhibitor product. The purpose of this step is to use corn starch as a carrier to improve the flowability and dispersibility of the product, while the addition of a dispersant prevents the microcapsules from agglomerating during storage and use, ensuring that the product can be uniformly dispersed and stably release the active ingredients in practical applications.

[0065] The specific implementation of step S08 involves calculating the parameter adjustment factor using a parameter adaptive adjustment function. Specifically, this involves obtaining temperature parameters from the production system. Humidity parameters Pressure parameters Flow velocity parameters And microcapsule efficacy to generate adaptive network model output parameters Temperature parameters were obtained from the drying equipment temperature sensor with an accuracy of ±0.5℃; humidity parameters were obtained from the ambient humidity sensor with an accuracy of ±2%; pressure parameters were obtained from the spray system pressure sensor with an accuracy of ±0.01MPa; flow rate parameters were obtained from the feed pump speed sensor with an accuracy of ±0.5ml / min; and the output parameters of the microcapsule efficiency generation adaptive network model were obtained from this model. The parameter adaptive adjustment function uses a gating mechanism to weight the input parameters. The gating mechanism is a mathematical method for dynamically adjusting weights. After combining the model output with the environmental parameters, an activation function is used to generate weight coefficients for each parameter. The activation function uses a modified hyperbolic tangent function to ensure that the weight coefficients are within the range of 0 to 1. These weighted coefficients are then summed with the original parameters to obtain the final parameter adjustment factor. Adjustment factor The value is usually between 0.8 and 1.2, used to adjust the feed rate parameter and the atomizing gas ratio parameter. Increase parameter value when This process involves dynamically adjusting parameter values ​​to achieve microcapsule quality control. The goal is to improve product quality consistency and production efficiency by monitoring production environment parameters in real time and combining these with deep learning model predictions.

[0066] The detailed structure of the adaptive network model for microcapsule efficacy generation is a hybrid architecture combining multi-layer convolutional neural networks and recurrent neural networks. Its structure includes: an input layer receiving microemulsion characteristic parameters and process parameters, with a total of 18 input nodes; a first convolutional layer containing 32 3×3 convolutional kernels for extracting microemulsion features using the ReLU activation function; a pooling layer employing 2×2 max pooling; a second convolutional layer containing 64 3×3 convolutional kernels for further extracting high-level features; a bidirectional long short-term memory network layer containing 128 hidden units to capture the dynamic impact of temperature changes on the drying process, paying particular attention to parameter change trends; an attention mechanism layer to assign higher weights to key parameters; a fully connected layer containing 256 nodes, using a dropout rate of 0.3 to prevent overfitting; and an output layer containing 5 nodes, corresponding to key parameters such as spray inlet temperature, outlet temperature, atomization pressure, feed rate, and atomization airflow ratio. The detailed steps for establishing the training dataset for this model include: First, designing an orthogonal experimental scheme to determine five factors in the microemulsion formulation, such as the wall material ratio, eugenol mixture concentration, and chitosan concentration, with four levels for each factor; second, determining spray condition variables, such as five levels for inlet temperature in the range of 160–200℃, five levels for outlet temperature in the range of 75–95℃, three levels for atomization pressure in the range of 0.15–0.25 MPa, and three levels for feed rate in the range of 15–25 ml / min; then conducting small-scale experiments, and setting parameters for each group of conditions. The experiment was repeated three times, for a total of 900 experiments. Process parameters such as inlet temperature, outlet temperature, atomization pressure, and feed rate were recorded. The morphological quality parameters of the final microcapsules were measured, including particle size distribution, encapsulation efficiency, microcapsule integrity, sustained release time, and stability of active ingredients. Training and validation sets were constructed, with 80% of the data used as the training set and 20% as the validation set. Data augmentation techniques were used to expand the training data, including adding noise and fine-tuning parameters. The data was standardized to normalize all parameter values ​​to the 0-1 range. The training steps for the microcapsule efficacy generation adaptive network model include: parameter optimization using the Adam optimizer, with an initial learning rate set to 0.001 and a cosine annealing strategy, the learning rate decreasing to 0.9 times its original value every 50 epochs; batch size set to 64; training epochs set to 300; mean squared error used as the loss function; early stopping to avoid overfitting, stopping training when the loss on the validation set fails to improve for 20 consecutive epochs; K-fold cross-validation used during model optimization, with K set to 5; and the final model achieving a prediction accuracy of over 92% on the validation set, with a correlation coefficient of no less than 0.90 between the predicted values ​​and the actual microcapsule quality parameters.

[0067] It should be noted that this invention achieves a reduced dosage replacement and significantly enhanced sprout-inhibiting effect compared to the traditional chemical sprout inhibitor, butylphenanthrene, by constructing a dual protection mechanism of molecular inclusion and microcapsule. From a molecular level perspective, the host-guest inclusion structure formed by the β-cyclodextrin and eugenol mixture not only provides stabilizing protection for eugenol, but more importantly, through the selective encapsulation effect of the hydrophobic cavity, it allows eugenol molecules to maintain a higher bioactive concentration during release, thus achieving a sprout-inhibiting effect comparable to or even better than butylphenanthrene with a smaller dosage. The polyelectrolyte composite network structure of gelatin and gum arabic in the microcapsule wall material system, combined with the reinforcing effect of chitosan, constructs a precise sustained-release control mechanism, enabling eugenol to be released directionally according to the tobacco growth rhythm, avoiding the waste of efficacy and environmental burden caused by the burst release phenomenon common in chemical sprout inhibitors such as butylphenanthrene. Simultaneously, the uniform dispersion achieved through microemulsification technology and the particle size optimization controlled by the nano-aggregation kinetic equation significantly improve the contact efficiency and permeability of eugenol with tobacco tissue, enhancing the targeting of the sprout-inhibiting effect. The synergistic protective mechanism of ultraviolet absorbers and antioxidants ensures the long-term stability of eugenol in complex field environments and prolongs its effective action time, thereby achieving the dual goals of reduced dosage and enhanced efficacy, and providing a green alternative to reduce dependence on chemical pesticides.

[0068] Specifically, the principle of this invention is as follows: This invention utilizes a dual protection strategy of molecular inclusion and microencapsulation, combined with adaptive parameter control technology, to transform eugenol mixtures from laboratory-grade active substances into practical sprout inhibitor products. This technical principle is mainly reflected in the following aspects:

[0069] Firstly, at the molecular level, the formation of host-guest inclusion complexes between β-cyclodextrin and eugenol mixtures is fundamental to the stabilization of eugenol mixtures. β-cyclodextrin possesses a unique barrel-shaped molecular structure with a hydrophobic inner cavity and a hydrophilic outer surface, enabling it to selectively encapsulate eugenol mixture molecules within the hydrophobic inner cavity, forming stable inclusion complexes. This inclusion process blocks the direct interaction of external oxygen and light with the eugenol mixtures, effectively reducing oxidative decomposition and photodegradation reactions, thus improving the chemical stability of the eugenol mixtures at the molecular level. A full reaction at 75°C for 180 minutes ensured a high inclusion rate and structural stability, laying the foundation for subsequent microencapsulation.

[0070] Secondly, in terms of microstructure, this invention innovatively uses gelatin and gum arabic as polyelectrolyte composite wall materials, forming a dense network structure through electrostatic interactions to construct the basic framework of the microcapsules. The introduction of chitosan further enhances the mechanical strength and biocompatibility of the microcapsule wall, forming a more robust protective barrier. Microemulsion technology promotes the uniform dispersion of eugenol mixtures in the aqueous phase, and the particle size and distribution are precisely controlled through the nano-aggregation kinetic equation, solving the problem of poor dispersibility of eugenol mixtures as hydrophobic substances in the aqueous phase. The addition of ultraviolet absorbers and antioxidants forms a synergistic protection mechanism; the former absorbs ultraviolet radiation to prevent photodegradation, while the latter captures free radicals to inhibit oxidation reactions, further improving the stability of eugenol mixtures in complex environments.

[0071] Finally, at the process control level, this invention introduces an adaptive network model for microcapsule efficiency generation and an adaptive parameter adjustment function, achieving intelligent optimization of key parameters during the preparation process. This model combines convolutional neural networks and recurrent neural networks, enabling it to learn the optimal combination of process parameters from historical data and dynamically adjust the feed rate and atomization gas flow ratio through a gating mechanism, ensuring consistent microcapsule quality and optimal sustained-release performance. Precisely controlled temperature parameters (inlet 180℃, outlet 85℃) in the spray drying process guarantee rapid microcapsule formation and complete retention of active ingredients, solving the problem of severe active ingredient loss in traditional drying processes.

[0072] Through the aforementioned multi-layered protection mechanism and precise process control, this invention has successfully overcome the technical bottleneck of using eugenol blends as tobacco bud inhibitors, achieving efficient encapsulation, stable protection, and slow release of eugenol blends, providing a new technical path and solution for their practical application in the field of tobacco bud inhibitors.

[0073] The following provides a specific embodiment 1 of the present invention, and the specific implementation of each step in this embodiment 1 is described in detail below.

[0074] The specific implementation of step S01 involves mixing the eugenol mixture with β-cyclodextrin at a mass ratio of 1:5. Specifically, β-cyclodextrin is first added to the reaction vessel and preheated to 75°C under a constant temperature water bath, maintaining temperature fluctuations within ±2°C. Then, the eugenol mixture is slowly added, and simultaneously, the stirring device is started at 350 rpm for initial stirring for 5 minutes to ensure thorough mixing. The stirring speed is then reduced to 180 rpm and continued for 180 minutes. During this period, samples are collected every 30 minutes for infrared spectroscopy analysis to confirm the inclusion reaction progress. When 2850... When the intensity of the characteristic peak decreases to below 20% of its initial value, the inclusion reaction is considered to be fully completed. The inclusion process conforms to a pseudo-first-order kinetic model, and its inclusion reaction progress... It can be represented by the following equation:

[0075] ;

[0076] In the formula, The extent of inclusion reaction is dimensionless and represents the proportion of eugenol mixtures included. The inclusion reaction rate constant is The value ranges from 0.015 to 0.025 at 75℃. ; For reaction time, This equation describes the kinetics of inclusion complex formation between eugenol mixtures and β-cyclodextrin, reflecting the change in the inclusion complex formation rate over time, and is used to guide the determination of reaction time. The interaction energy between the eugenol mixtures and β-cyclodextrin during inclusion complex formation is also considered. It can be represented as:

[0077] ;

[0078] In the formula, The total interaction energy, ; For van der Waals force energy, ; The hydrogen bond energy. ; It is the energy of electrostatic interaction. .when Value less than -20 When the inclusion complex is stable, it indicates that the inclusion complex has been formed. The purpose of this step is to utilize the amphiphilic properties of the hydrophobic inner cavity and hydrophilic outer surface of β-cyclodextrin to encapsulate the eugenol mixture molecules within the inner cavity of β-cyclodextrin through host-guest inclusion interaction, forming a stable inclusion complex. This effectively protects the eugenol mixture from oxidative degradation and improves its stability.

[0079] The specific implementation of step S02 involves mixing the eugenol inclusion complex with gelatin and gum arabic at a mass ratio of 2:1:1. Specifically, the gelatin is first preheated in a 60°C water bath for 15 minutes to allow it to fully swell. Simultaneously, gum arabic is fully dissolved in another container at 55°C with a stirring speed controlled at 250 rpm. The dissolved gum arabic solution is then slowly added to the gelatin solution, and stirring continues for 10 minutes. Next, the eugenol inclusion complex is added, followed by deionized water to adjust the total mass fraction of the mixture to 15%, maintaining the pH value of the solution between 4.3 and 4.5 throughout the process. This pH range is below the isoelectric point of gelatin, and the negative charge of gum arabic promotes the formation of a stable polyelectrolyte complex. The electrostatic interaction strength between gelatin and gum arabic... It can be represented as:

[0080] ;

[0081] In the formula, The electrostatic interaction strength, ; The charge carried by gelatin molecules. When the pH value is 4.3 to 4.5, the range is 0.8 × ; The charge carried by gum arabic molecules. When the pH value is 4.3 to 4.5, the range is -1.5× ~-1.0× C; The vacuum permittivity, F / m; is the relative permittivity of the solution, dimensionless, and approximately 78 in aqueous solution; This refers to the distance between gelatin and gum arabic molecules. The typical value range is 1 to 5. .when Absolute value greater than At step J, the polyelectrolyte complex forms a stable structure. This step utilizes the electrostatic interaction between gelatin and gum arabic to form a dense network structure, which serves as the wall material for microcapsules. The aim is to enhance the mechanical strength and barrier properties of the microcapsule wall material through the polyelectrolyte complexation, thereby reducing the volatilization loss of the eugenol mixture.

[0082] The specific implementation of step S03 involves adding a 0.5% (w / w) chitosan solution to the above aqueous solution. Specifically, the chitosan is first dissolved in a 1% acetic acid solution, and the mixture is stirred for at least 120 minutes to ensure complete dissolution. Then, the chitosan solution is slowly added dropwise to the aqueous solution obtained in step S02 at a rate of 5 ml / min, while simultaneously adjusting the stirring speed to 300 rpm and maintaining this speed for 90 minutes. During this period, the viscosity of the mixture is measured every 15 minutes. When the viscosity stabilizes within the range of 120–150 MPa·s, it indicates that the emulsion formation is stable. Emulsion stability coefficient. It can be calculated using the following equation:

[0083] ;

[0084] In the formula, The emulsion stability coefficient is dimensionless. The viscosity of the mixture, ; For continuous phase viscosity, ; The charge sensitivity coefficient is dimensionless and typically takes a value of [value missing]. ; The charge carried by chitosan molecules. Under pH conditions of 4.3–4.5, the value range is 1.0 × ~1.5× C. When At a value greater than 3.0, the emulsion exhibits good stability. This process utilizes the principle of high-energy emulsification, using mechanical shear force to uniformly disperse the eugenol inclusion complex in the continuous phase, forming a stable emulsion. Chitosan, as a natural polymer compound, enhances the mechanical strength of the microcapsules through cross-linking of amino groups with gelatin carboxyl groups, and further stabilizes the wall material structure and improves biocompatibility through the electrostatic interaction between the positive charge and the negative charge of gum arabic.

[0085] The specific implementation of step S04 involves treating the emulsion at 50°C using microemulsification technology for 30 minutes. Specifically, a high-pressure homogenizer is used to pass the emulsion through a microporous membrane at a pressure of 10 MPa. The first stage of treatment lasts 10 minutes, followed by increasing the pressure to 15 MPa and continuing treatment for another 10 minutes. The final stage pressure is set to 20 MPa and treated for 10 minutes. Dynamic light scattering is used to monitor the particle size in real time, ensuring that the final particle size is controlled below 50 μm, with the median particle size preferably controlled within the range of 25–35 μm. The microemulsification process follows the nanoagglomeration kinetic equation, expressed as follows:

[0086] ;

[0087] In the formula, Let be the particle concentration at time t. ; For processing time, ; The aggregation rate constant is The range of values ​​is ; The shear force coefficient, It is related to the stirring speed, and the calculation formula is: ,in For stirring speed, ; Let be the particle concentration at time t. ; This refers to the polyelectrolyte concentration. ; This represents the maximum effective concentration of the polyelectrolyte. The value is 5 ; This refers to the surfactant concentration. ; This represents the maximum effective concentration of the surfactant. The value is 2 Particle size distribution parameters The relationship with particle concentration can be expressed as:

[0088] ;

[0089] In the formula, Let be the particle size at time t. ; Initial particle size, ; The initial particle concentration, ; Let be the particle concentration at time t. This equation describes the dynamic equilibrium between particle aggregation and dispersion during microemulsification, guiding the adjustment of microemulsification time and intensity. The purpose of this step is to shear the oil-water two-phase substances into tiny droplets through high shear force, ensuring uniform dispersion of the eugenol mixture in the aqueous phase, improving emulsion stability, and laying the foundation for subsequent microcapsule formation.

[0090] The specific implementation of step S05 involves adding 0.8% (by mass) of the UV absorber 2-hydroxy-4-methoxybenzophenone and 0.5% (by mass) of the antioxidant tert-butylhydroxyanisole to the microemulsion. Specifically, the two additives are first dissolved in a small amount of ethanol (not exceeding 5% of the total system volume). Then, the solution is slowly added dropwise to the microemulsion at a rate of 3 ml / min while maintaining a stirring speed of 250 rpm. After the addition is complete, stirring continues for 60 minutes to ensure uniform dispersion of the additives. During this period, the absorbance of the system in the wavelength range of 320–350 nm is monitored using a UV-Vis spectrophotometer. When the absorbance reaches 0.8 or higher, it indicates good dispersion of the UV absorber. UV protection factor. The calculation formula is:

[0091] ;

[0092] In the formula, The UV protection factor is dimensionless. In terms of solar ultraviolet irradiance, ; is the coefficient of ultraviolet-induced erythema, dimensionless; The transmittance is a dimensionless coefficient that is related to the absorbent concentration. The relationship is , ,in The molar absorptivity is 1. , This refers to the absorbent concentration. , For optical path, ; For wavelength, .when A value greater than 15 indicates good UV protection. The oxidation kinetic equation for eugenol mixtures can be expressed as:

[0093] ;

[0094] In the formula, This refers to the concentration of the eugenol mixture. ; For time, ; Let be the rate constant of the oxidation reaction. ; Oxygen concentration, ; Antioxidant concentration, ; This represents the maximum effective concentration of the antioxidant. The value is 0.02. This step utilizes the benzene ring structure of the ultraviolet absorber to absorb ultraviolet radiation energy and convert it into heat energy through a π-electron conjugation system, thereby preventing the degradation of eugenol mixtures due to light exposure. At the same time, the antioxidant can effectively capture free radicals, block free radical chain reactions, inhibit the oxidation reaction of eugenol mixtures, and improve the stability and shelf life of the product.

[0095] The specific implementation of step S06 involves preparing microcapsules from the microemulsion using a spray drying method. Specifically, the microemulsion is preheated to 40°C and then pumped into the spray drying equipment at a rate of 20 ml / min using a peristaltic pump. The inlet temperature is set to 180°C, the outlet temperature is controlled at 85°C, the atomization pressure is set to 0.2 MPa, the nozzle diameter is selected to be 0.5 mm, and the drying airflow rate is adjusted to 0.6. / minute. During the drying process, an adaptive network model based on microencapsulation efficiency is used to monitor and optimize spray parameters. The water mass transfer equation during spray drying can be expressed as:

[0096] ;

[0097] In the formula, The water content of the droplets, ; This refers to the drying time. ; The mass transfer coefficient is . ; Specific surface area ; To balance the moisture content, . With temperature The relationship can be represented as:

[0098] ;

[0099] In the formula, For frequency factors, ; For mass transfer activation energy, ; is the gas constant, 8.314. ; Absolute temperature Encapsulation efficiency of microcapsules The calculation formula is:

[0100] ;

[0101] In the formula, For encapsulation efficiency, % This represents the actual measured content of eugenol mixtures within the microcapsules. ; This represents the theoretical amount of eugenol mixture to be added. The microcapsule efficiency is optimized using an adaptive network model to maintain encapsulation efficiency above 90% and breakage rate below 3%. This step aims to effectively encapsulate and protect the eugenol mixture by rapidly dehydrating the atomized liquid in hot air to form core-shell microcapsules.

[0102] The specific implementation of step S07 involves mixing the microcapsules with corn starch at a mass ratio of 3:1, and adding 0.3% (by mass) of polyvinylpyrrolidone (PVP) as a dispersant. Specifically, the microcapsules and corn starch are first dry-mixed in a V-type mixer for 15 minutes, with the mixing uniformity controlled to within 3% relative standard deviation through sampling tests. Then, the dispersant is dissolved in an appropriate amount of deionized water to prepare a solution, with the amount controlled to be 20% of the total solid weight. This solution is then evenly sprayed onto the mixture, and mixing continues for 10 minutes. The minimum spanning tree algorithm is then used to optimize the dispersed network structure. The specific implementation process of the minimum spanning tree algorithm is as follows:

[0103] First, construct a network model of the microcapsule distributed system: let the microcapsules be the set of network nodes. The interactions between nodes form an edge set. edge weight The calculation formula is:

[0104] ;

[0105] In the formula, For nodes With nodes Edge weights between them ; and They are nodes and nodes Surface potential, This is obtained by measuring with a potentiometer; For nodes With nodes The distance between them The minimum spanning tree was obtained through microscopic observation and measurement. It is a set of edges that satisfy the following conditions:

[0106] ;

[0107] In the formula, For the image The minimum spanning tree is any spanning tree. The minimum spanning tree algorithm is implemented using Kruskal's algorithm, and the specific steps are: sort all edges in ascending order of weight; initialize the minimum spanning tree. Traverse each edge in order. If join in If no loop is formed, then... join in ;when The number of middle edges reached The algorithm ends when the optimal dispersion condition is reached. The optimal amount of dispersant added is... The calculation formula is:

[0108] ;

[0109] In the formula, This refers to the amount of dispersant added. ; This is the proportionality coefficient. The value ranges from 0.005 to 0.01. ; The total surface area of ​​the system. The moisture content was determined using the BET method. Finally, the mixture was dried at 40°C until the moisture content did not exceed 5%, and particles with a size range of 75–150 μm were screened to obtain the final slow-release tobacco sprout inhibitor product. The purpose of this step is to utilize corn starch as a carrier to improve the product's flowability and dispersibility, while the addition of a dispersant prevents the aggregation of microcapsules during storage and use, ensuring that the product can be uniformly dispersed and stably release the active ingredients in practical applications.

[0110] The specific implementation of step S08 involves calculating the parameter adjustment factor using a parameter adaptive adjustment function. Specifically, this involves obtaining temperature parameters from the production system. Humidity parameters Pressure parameters Flow velocity parameters And microcapsule efficacy to generate adaptive network model output parameters The temperature parameter is obtained from the temperature sensor of the drying equipment, with a temperature monitoring accuracy of ±0.5℃; the humidity parameter is obtained from the ambient humidity sensor, with a humidity monitoring accuracy of ±2%; the pressure parameter is obtained from the pressure sensor of the spray system, with a pressure monitoring accuracy of ±0.01MPa; the flow rate parameter is obtained from the feed pump speed sensor, with a flow rate monitoring accuracy of ±0.5ml / min; and the output parameters of the microcapsule efficiency generation adaptive network model are obtained from this model. The parameter adaptive adjustment function performs weighted processing on the input parameters through a gating mechanism, and its mathematical expression is:

[0111] ;

[0112] In the formula, This is a dimensionless parameter adjustment factor. For the first The weighting coefficients of each parameter are dimensionless. For the normalized first Individual parameter values, dimensionless. Weighting coefficients. Calculated via gating mechanism:

[0113] ;

[0114] In the formula, For the first The weight matrix of each parameter is obtained by training the microcapsule efficacy generation adaptive network model. Parameter normalization is performed using the following formula:

[0115] ;

[0116] In the formula, The original value of the parameter; and These are the minimum and maximum values ​​of the parameter, respectively. Adjustment factor. The value is usually between 0.8 and 1.2, used to adjust the feed rate parameter and the atomizing gas ratio parameter. Increase parameter value when When the parameter value is reduced, the specific adjustment formula is as follows:

[0117] ;

[0118] ;

[0119] In the formula, The adjusted feed rate, ; This is the original feed rate. ; The adjusted atomized airflow ratio is dimensionless. The original atomized airflow ratio is dimensionless. The purpose of this step is to precisely adjust production process parameters by real-time monitoring of production environment parameters and combining the prediction results of deep learning models, thereby improving product quality consistency and production efficiency.

[0120] The detailed structure of the adaptive network model for microcapsule efficacy generation is a hybrid architecture combining multi-layer convolutional neural networks and recurrent neural networks. Its structure includes: an input layer receiving microemulsion characteristic parameters and process parameters, with a total of 18 input nodes; a first convolutional layer containing 32 3×3 convolutional kernels for extracting microemulsion features using the ReLU activation function; a pooling layer employing 2×2 max pooling; a second convolutional layer containing 64 3×3 convolutional kernels for further extracting high-level features; a bidirectional long short-term memory network layer containing 128 hidden units to capture the dynamic impact of temperature changes on the drying process, paying particular attention to parameter change trends; an attention mechanism layer to assign higher weights to key parameters; a fully connected layer containing 256 nodes, using a dropout rate of 0.3 to prevent overfitting; and an output layer containing 5 nodes, corresponding to key parameters such as spray inlet temperature, outlet temperature, atomization pressure, feed rate, and atomization airflow ratio.

[0121] The detailed steps for establishing the training dataset for this model include: First, designing an orthogonal experimental scheme to determine five factors in the microemulsion formulation, such as the wall material ratio, eugenol mixture concentration, and chitosan concentration, with four levels for each factor; second, determining spray condition variables, such as five levels for inlet temperature in the range of 160–200℃, five levels for outlet temperature in the range of 75–95℃, three levels for atomization pressure in the range of 0.15–0.25 MPa, and three levels for feed rate in the range of 15–25 ml / min; then conducting small-scale experiments, and setting parameters for each group of conditions. The experiment was repeated three times, for a total of 900 experiments. Process parameters such as inlet temperature, outlet temperature, atomization pressure, and feed rate were recorded. The morphological quality parameters of the final microcapsules were measured, including particle size distribution, encapsulation efficiency, microcapsule integrity, sustained release time, and stability of active ingredients. Training and validation sets were constructed, with 80% of the data used as the training set and 20% as the validation set. Data augmentation techniques were used to expand the training data, including adding noise and fine-tuning parameters. The data was standardized to normalize all parameter values ​​to the 0-1 range. The training steps for the microcapsule efficacy generation adaptive network model include: parameter optimization using the Adam optimizer, with an initial learning rate set to 0.001 and a cosine annealing strategy, the learning rate decreasing to 0.9 times its original value every 50 epochs; batch size set to 64; training epochs set to 300; mean squared error used as the loss function; early stopping to avoid overfitting, stopping training when the loss on the validation set fails to improve for 20 consecutive epochs; K-fold cross-validation used during model optimization, with K set to 5; and the final model achieving a prediction accuracy of over 92% on the validation set, with a correlation coefficient of no less than 0.90 between the predicted values ​​and the actual microcapsule quality parameters.

[0122] To better understand and implement this invention, the following is a specific application scenario of the invention, Example 2: This example compares the differences in the effects of eugenol mixture and slow-release microcapsule tobacco bud inhibitor in the mid-to-late stage bud inhibition treatment of tobacco. The specific implementation steps are as follows.

[0123] First, experimental materials were prepared. The tobacco variety Yunyan 87 was selected and planted in an experimental field with the same soil conditions. The plants grew uniformly, and the experimental treatment was carried out immediately after the terminal buds were removed. The experiment was divided into a control group and an experimental group. The control group used a mixture of eugenol as a bud inhibitor, while the experimental group used a microcapsule sustained-release bud inhibitor of the mixture of eugenol prepared by the method of this invention.

[0124] Preparation method of control group: Take 10g of the eugenol mixture (the mass ratio of the two components is 1:1), dissolve it in 40ml of anhydrous ethanol to prepare a 20% eugenol mixture solution, stir well and use directly.

[0125] Preparation method of the bud inhibitor in the experimental group: The preparation was carried out in accordance with the specific implementation method of the present invention. The specific steps are as follows: (1) Take 10g of eugenol mixture and 50g of β-cyclodextrin and mix them at a mass ratio of 1:5. Stir for 180 minutes under a water bath at 75℃ to form eugenol inclusion complex; (2) Mix 20g of the obtained eugenol inclusion complex with 10g of gelatin and 10g of gum arabic, and add deionized water to prepare an aqueous solution with a mass fraction of 15%; (3) Add a chitosan solution with a mass fraction of 0.5% to the above aqueous solution and stir at a speed of 300 rpm for 90 minutes to form an emulsion; (4) Microemulsify the obtained emulsion at 50℃ using a high-pressure homogenizer for 30 minutes, and treat it for 10 minutes each under the conditions of 10MPa, 15MPa and 20MPa respectively. (5) Add 0.8% by mass of 2-hydroxy-4-methoxybenzophenone and 0.5% by mass of tert-butylhydroxyanisole to the microemulsion and continue stirring for 60 minutes; (6) Prepare microcapsules from the microemulsion by spray drying, with an inlet temperature of 180°C and an outlet temperature of 85°C; (7) Mix the microcapsules with corn starch at a mass ratio of 3:1 and add 0.3% by mass of polyvinylpyrrolidone as a dispersant to produce the final slow-release tobacco sprout inhibitor product; (8) Optimize the production process using a parameter adaptive adjustment function to achieve a final product encapsulation rate of 92.6% and a microcapsule particle size uniformity coefficient of 0.89.

[0126] To verify the influence of the preparation process on the physicochemical properties of the microcapsules, key process parameters were tested and analyzed, and the results are shown in Table 1:

[0127] Table 1. Effects of different process parameters on microcapsule properties

[0128]

[0129] As shown in Table 1, the microcapsules prepared at a reaction temperature of 75℃ and a stirring speed of 300r / min have the best overall performance, with an average particle size of 35.2μm, an encapsulation efficiency of 92.6%, a dispersion index of 0.89, and a sustained release time of 48.7 hours.

[0130] The microstructure of the microcapsules was observed using a scanning electron microscope, and the results are shown in Table 2:

[0131] Table 2. Morphological characteristics analysis results of microcapsules

[0132]

[0133] As shown in Table 2, the microcapsules prepared in the experimental group were regular spherical with smooth and dense surfaces and good morphological uniformity, with a breakage rate of only 2.3%, while the control group consisted of only amorphous droplets with no clear morphological characteristics.

[0134] Methods for testing the bud inhibition effect: Thirty-five days after the removal of the top bud of the tobacco plant, the axillary bud growth points were treated. In the control group, a brush was used to apply a solution of eugenol mixture directly to the axillary bud growth points, with approximately 0.5 ml per plant. In the experimental group, the prepared microcapsule bud inhibition agent was formulated into a 0.5% aqueous dispersion and sprayed evenly onto the axillary bud growth points using a sprayer, with the spraying amount being the same as the effective component amount of the eugenol mixture in the control group. Axillary bud growth was observed and recorded at 24h, 48h, 72h, and 96h after treatment, and the bud inhibition rate and duration of effect were measured. The bud inhibition rate was calculated using the formula: Bud inhibition rate = (Number of inhibited buds / Total number of buds) × 100%. The experimental results are shown in Table 3.

[0135] Table 3 Comparison of Tobacco Sprout Inhibition Effects of Different Treatments

[0136]

[0137] As shown in Table 3, the bud inhibition rate of the control group was 95.2% 1 day after treatment, but the bud inhibition effect decreased significantly with the extension of time, dropping to 58.3% by 30 days, with an average duration of effect of 19 days. The experimental group maintained a high bud inhibition rate throughout the treatment process, and even after 30 days, it remained at a high level of 85.6%, with an average duration of effect of 26 days, which was significantly better than the control group.

[0138] To more intuitively compare the differences between the two treatment methods, the growth of tobacco axillary buds was photographed and recorded. Figure 2 (The effect of applying the simple eugenol mixture 14 days after application) shows that some axillary buds of the tobacco plants in the control group have begun to sprout, especially the axillary buds in the middle and lower parts of the plant have grown more obviously. Figure 3 (The effect picture 14 days after the application of the bud inhibitor) shows that almost all the axillary buds of the tobacco plants in the experimental group were inhibited, and no obvious bud growth was observed.

[0139] In addition, the environmental stability of the two treatment methods was tested, and the results are shown in Table 4:

[0140] Table 4 Comparison of environmental stability of different treatment methods

[0141]

[0142] As shown in Table 4, the experimental group outperformed the control group in all environmental stability tests. Specifically, the stability under light conditions improved by 17.3%, the efficiency after rainwater washing improved by 17.1%, the stability under high temperature conditions improved by 16.8%, and the stability under low humidity conditions improved by 17.3%.

[0143] The release curves of the active ingredients in the microcapsules were obtained through in vitro simulated environment testing, as shown in Table 5:

[0144] Table 5. Release characteristics of active ingredients in microcapsules

[0145]

[0146] As shown in Table 5, the control group released 75.3% of the active ingredients within 12 hours, 92.1% within 24 hours, and almost all of them were released after 48 hours. In contrast, the experimental group exhibited a significant slow-release characteristic, releasing only 23.5% within 12 hours, 72.3% within 48 hours, and nearly all of it was released after 120 hours. This slow-release characteristic is the key factor for the experimental group to maintain a long-lasting bud-suppressing effect.

[0147] The bud-inhibiting mechanism of eugenol mixture solutions is to rapidly inhibit bud growth through high concentrations of eugenol mixtures. However, due to the lack of a protective mechanism, eugenol mixtures are easily degraded by light, high temperature, and oxygen, leading to a rapid decline in the bud-inhibiting effect. This invention successfully solves the problem of easy volatility and degradation of eugenol mixtures in traditional technologies by using β-cyclodextrin inclusion complexation, polyelectrolyte composite wall material encapsulation, and microencapsulation treatment, significantly extending the bud-inhibiting effect time and improving environmental adaptability. In particular, the microemulsification process optimized by the nano-agglomeration kinetic equation and the spray drying technology controlled by the parameter adaptive adjustment function result in a more uniform particle size distribution of microcapsules, higher encapsulation efficiency, and more controllable release.

[0148] The following is a specific embodiment 3 of the present invention concerning the reduction and enhancement of chemical reagents through the mixture of eugenol and terbufotalin: A technical team was tasked with reducing the amount of the chemical sprout inhibitor terbufotalin used while maintaining its sprout-inhibiting effect, thereby reducing environmental burden and residue risks. The technical team decided to adopt the eugenol-based tobacco sprout inhibitor preparation and its compounding method for reducing and enhancing efficacy according to the present invention. By using eugenol and terbufotalin in combination, the goal of reducing and enhancing the efficacy of the chemical sprout inhibitor is achieved.

[0149] The technical team first analyzed the usage of traditional butylated arbutin as a sprout inhibitor. While butylated arbutin, as a chemical sprout inhibitor, has a significant sprout-inhibiting effect, it suffers from long-lasting environmental residue and some impact on soil microorganisms. Through literature review, the team found that eugenol, as a natural plant-derived sprout inhibitor, possesses good biological activity and environmental compatibility, but its stability is poor, its volatility is high, and its effective period is short when used alone. Therefore, the team proposed a technical solution using the technology of this invention to prepare eugenol into a microcapsule sustained-release formulation, which is then used in combination with butylated arbutin.

[0150] The technical team prepared eugenol microcapsule bud inhibitors according to the technical solution of this invention. First, eugenol was mixed with... Cyclodextrin was mixed at a mass ratio of 1:5 and stirred at 75°C for 180 minutes to form an inclusion complex. The inclusion complex was then mixed with gelatin and gum arabic at a mass ratio of 2:1:1, and deionized water was added to prepare a 15% aqueous solution. Next, 0.5% chitosan was added to the aqueous solution, and the mixture was stirred at 300 rpm for 90 minutes to form an emulsion. The emulsion was then treated with microemulsification technology at 50°C for 30 minutes to control the particle size to below 50 μm. 0.8% UV absorber and 0.5% antioxidant were added to the microemulsion, and stirring was continued for 60 minutes. The microemulsion was then spray-dried into microcapsules at an inlet temperature of 180°C and an outlet temperature of 85°C. Finally, the microcapsules were mixed with corn starch at a mass ratio of 3:1, and 0.3% dispersant was added to prepare the final sustained-release eugenol sprout inhibitor product.

[0151] The technical team designed five experimental groups and one control group to verify the synergistic effect of the reduced dosage of the compound formulation. The control group used conventional butylated arbutin as a sprout inhibitor at the recommended concentration. Experimental group 1 used a compound formulation of 75% butylated arbutin + 25% eugenol microcapsules. Experimental group 2 used a compound formulation of 50% butylated arbutin + 50% eugenol microcapsules. Experimental group 3 used a compound formulation of 25% butylated arbutin + 75% eugenol microcapsules. Experimental group 4 used a compound formulation of 10% butylated arbutin + 90% eugenol microcapsules. Experimental group 5 used only eugenol microcapsule sprout inhibitor. The total effective ingredient dosage was kept consistent across all treatments to ensure fairness in the comparison.

[0152] The technical team selected the Yunyan 87 variety as the experimental subject and conducted experiments under the same field conditions. The experimental field soil type was red soil, with a pH of 6.8, an organic matter content of 24.6 g / kg, available nitrogen of 126 mg / kg, available phosphorus of 18.9 mg / kg, and available potassium of 198 mg / kg. The bud-suppressing agent was applied 35 days after the terminal bud was removed from the tobacco plants, at which point the axillary buds were just beginning to sprout, which was the optimal time for bud suppression treatment.

[0153] The technical team used a spray application method, employing a backpack sprayer to precisely spray the axillary bud growth points of tobacco plants. In the control group, terbufotalin was diluted to the recommended concentration and sprayed directly. In each experimental group, terbufotalin and eugenol microcapsules were mixed at a predetermined ratio to prepare an aqueous dispersion for spraying. The spray volume per tobacco plant was controlled at 2.5 mL to ensure that the axillary bud growth points were fully covered by the solution.

[0154] The technical team regularly observed and recorded the bud-suppressing effect after application, calculating the bud-suppressing rate for each treatment on days 1, 3, 7, 14, 21, and 30 post-treatment. The bud-suppressing rate was calculated as the percentage of suppressed axillary buds to the total number of axillary buds. The time for axillary bud re-germination was also recorded to assess the duration of effectiveness of different treatments.

[0155] As shown in Table 6:

[0156] Table 6 Comparison of sprout-suppressing effects of different compound ratios

[0157]

[0158] As shown in Table 6, experimental group 2 (50% butylated arbutin + 50% eugenol) exhibited the best bud-suppressing effect, maintaining a bud-suppressing rate of 83.6% on day 30, with an effective period of 35 days, significantly better than the control group. Experimental groups 1 and 3 also showed good results, both superior to the control group and experimental group 5, which used eugenol alone.

[0159] The technical team further analyzed the impact of different treatments on the soil environment. Rhizosphere soil samples were collected 30 days after application to detect changes in soil microbial community structure, enzyme activity, and physicochemical properties. (See Table 7 for details.)

[0160] Table 7. Environmental Impact Assessment of Different Treatments on Soil

[0161]

[0162] Table 7 shows that with the increase of the proportion of eugenol microcapsules, the soil microbial diversity index and enzyme activity both improved, and the negative change in soil pH gradually decreased or even turned positive. This indicates that eugenol microcapsules have a milder impact on the soil environment and are conducive to maintaining soil ecological balance.

[0163] The technical team also tested the residues of sprout inhibitors in tobacco leaves. Samples were collected at the time of tobacco harvest, and the residues of sec-butylamine were detected by high performance liquid chromatography (HPLC), while the residues of eugenol were detected by gas chromatography-mass spectrometry (GC-MS). See Table 8 for details.

[0164] Table 8 Results of Detection of Sprouting Agent Residues in Tobacco Leaves

[0165]

[0166] The results in Table 8 show that the combined use significantly reduced the total residue of bud inhibitors in tobacco leaves, especially the residue of terbufotoxin. The total residue in experimental group 2 was reduced by 33.7% compared with the control group, while the bud inhibitory effect was still better than that of the control group.

[0167] The technical team further evaluated the impact of the compound bud-inhibiting agent on tobacco leaf quality. Mature tobacco leaf samples were collected, and the content of major chemical components and sensory quality indicators were tested. See Table 9 for details.

[0168] Table 9 Effects of different treatments on tobacco leaf quality

[0169]

[0170] Table 9 shows that with the increase of the proportion of eugenol microcapsules, the sugar content of tobacco leaves increased slightly, the nicotine content decreased, the potassium ion content increased, and the sensory scores generally improved. This indicates that eugenol microcapsule sprout inhibitors have a positive impact on tobacco leaf quality.

[0171] The technical team analyzed the cost-effectiveness of the compound sprout inhibitor. Although the preparation cost of eugenol microcapsules is slightly higher than that of terbufotalin, the dosage of terbufotalin can be reduced through compound use, while improving the sprout inhibitory effect, prolonging the duration of effect, and reducing the number of applications. Considering the raw material cost, preparation cost, application cost, and environmental benefits, the compound scheme in experimental group 2 has the best overall benefits.

[0172] The technical team summarized the technical advantages of the compound sprout inhibitor. Firstly, through... Cyclodextrin inclusion technology improves the stability of eugenol, solving the problems of volatility and degradation of natural sprout inhibitors. Secondly, microencapsulation sustained-release technology enables the slow and continuous release of eugenol, extending the sprout-inhibiting effect. Thirdly, polyelectrolyte composite wall materials and microemulsion technology ensure the stability and dispersibility of the microcapsules. Fourthly, the combined use achieves a synergistic effect between chemical and natural sprout inhibitors, significantly reducing the amount of chemical sprout inhibitor used while maintaining the sprout-inhibiting effect.

[0173] The technical team determined the optimal compound formulation to be 50% terbufotin + 50% eugenol microcapsules. This formulation, while maintaining excellent bud-suppressing effects, reduced the amount of terbufotin used by 50%, decreased the residue in tobacco leaves by 33.7%, extended the effective period by 10 days, significantly reduced the impact on the soil environment, and improved the quality of tobacco leaves.

[0174] This invention represents a significant technological advancement compared to traditional chemical sprout inhibitors. From a molecular perspective, Cyclodextrin inclusion technology encapsulates eugenol molecules within a hydrophobic cavity through host-guest interactions, forming a stable supramolecular structure that effectively blocks direct exposure to external oxygen and light, fundamentally solving the problem of poor stability of natural active ingredients. From a formulation perspective, the polyelectrolyte composite wall material forms a dense network structure through the electrostatic interaction of gelatin and gum arabic, combined with the reinforcing effect of chitosan, constructing multiple protective barriers and achieving precise encapsulation and controlled release of active ingredients. From a process perspective, microemulsion technology precisely controls particle size distribution through nano-agglomeration kinetics equations, while spray drying technology optimizes process parameters through an adaptive network model generated by microcapsule efficiency, ensuring consistent and controllable product quality. From an application perspective, compounding technology achieves synergistic effects between chemical and natural sprout inhibitors, amplifying the sprout-inhibiting effect through the superposition of different mechanisms of action, while sustained-release technology extends the duration of effect and reduces the frequency of application. From an environmental perspective, the introduction of natural ingredients and the reduction of chemical ingredients lower the environmental burden, and the biodegradability of the microcapsule carrier further reduces the risk of environmental residues. These technological advancements have improved the overall performance of sprout inhibitors from multiple dimensions, providing important technical support for achieving green agriculture and sustainable development.

[0175] It should be noted that the variables involved in this invention are explained in detail in Tables 10 and 11 below.

[0176] Table 10 Variable Explanation Table (Part 1)

[0177]

[0178] Table 11 Variable Explanation Table (Part Two)

[0179]

[0180] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for preparing a tobacco sprout inhibitor based on eugenol, characterized in that, include: Eugenol mixtures and β-cyclodextrin were mixed at a mass ratio of 1:5 and stirred at 75°C for 180 minutes to form eugenol inclusion complexes. The eugenol inclusion complexes were then mixed with gelatin and gum arabic at a mass ratio of 2:1:1, and deionized water was added to prepare a 15% aqueous solution. Chitosan (0.5% by mass) was added to the aqueous solution, and the mixture was stirred at 300 rpm for 90 minutes to form an emulsion. The emulsion was then treated with microemulsification technology to control the particle size within a specified range; the microemulsification process followed the nanoagglomeration kinetics equation. Ultraviolet absorbers and antioxidants were added to the microemulsion. The microemulsion is stirred; the microemulsion is prepared into microcapsules by spray drying, and the spray parameters are optimized using a microcapsule efficiency generation adaptive network model; the microcapsules are mixed with corn starch, and a dispersant is added to prepare a slow-release tobacco sprout inhibitor product; the parameter adjustment factor is calculated using a parameter adaptive adjustment function to adjust the parameters in the microcapsule production process; the structure of the microcapsule efficiency generation adaptive network model is a hybrid architecture combining multilayer convolutional neural networks and recurrent neural networks, including convolutional layers to extract microemulsion features, bidirectional long short-term memory networks to capture the dynamic influence of temperature changes on the drying process, and fully connected layers to output spray parameters.

2. The preparation method according to claim 1, characterized in that, The step of treating the emulsion with microemulsification technology specifically involves treating the emulsion at 50°C for 30 minutes using microemulsification technology to control the particle size to below 50 μm.

3. The preparation method according to claim 2, characterized in that, The step of adding ultraviolet absorbers and antioxidants to the microemulsion and stirring is specifically to add 0.8% by mass of ultraviolet absorber and 0.5% by mass of antioxidant to the microemulsion and continue stirring for 60 minutes.

4. The preparation method according to claim 3, characterized in that, The step of preparing microcapsules from microemulsions by spray drying specifically involves preparing microcapsules from microemulsions by spray drying, with the drying inlet temperature at 180°C and the outlet temperature at 85°C.

5. The preparation method according to claim 4, characterized in that, The step of mixing microcapsules with corn starch and adding a dispersant to prepare a sustained-release tobacco bud inhibitor product specifically involves mixing the microcapsules with corn starch at a mass ratio of 3:1, adding a dispersant with a mass fraction of 0.3%, and preparing the final sustained-release tobacco bud inhibitor product.

6. The preparation method according to claim 5, characterized in that, The step of using a parameter adaptive adjustment function to calculate the parameter adjustment factor and adjust the parameters in the microcapsule production process specifically involves using a parameter adaptive adjustment function to calculate the parameter adjustment factor, and adjusting the feed rate parameter and atomizing airflow ratio parameter in the microcapsule production process according to the parameter adjustment factor.

7. A method for reducing dosage and enhancing efficacy of a compound tobacco bud inhibitor based on eugenol, characterized in that, include: Eugenol and β-cyclodextrin were mixed at a mass ratio of 1:5 and stirred at 75°C for 180 minutes to form an eugenol inclusion complex. The eugenol inclusion complex was then mixed with gelatin and gum arabic at a mass ratio of 2:1:1, and deionized water was added to prepare a 15% aqueous solution. Chitosan (0.5% by mass) was added to the aqueous solution, and the mixture was stirred at 300 rpm for 90 minutes to form an emulsion. The emulsion was then treated with microemulsification technology at 50°C for 30 minutes to control the particle size to below 50 μm. An ultraviolet absorber (0.8% by mass) and an antioxidant (0.5% by mass) were added to the microemulsion, and stirring continued for 60 minutes. The microemulsion was then spray-dried to form microcapsules at an inlet temperature of 180°C and an outlet temperature of 85°C. The microcapsules were mixed with corn starch at a mass ratio of 3:1, and a dispersant (0.3% by mass) was added to prepare an eugenol microcapsule sprout inhibitor. The eugenol microcapsule bud inhibitor was compounded with terbufotoxin at a mass ratio of 10%-90%:90%-10% to obtain a compound tobacco bud inhibitor.

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