114 results about "Nutrition management" patented technology

The invention relates to the field of nutrition and health management, and discloses a nutrition evaluation and prediction method and system based on big data, and the method comprises the following steps: firstly collecting the physiological data, diet record and activity data of a user, and carrying out the preprocessing of the data, and guaranteeing the data quality; dimensionality reduction is carried out through feature extraction and principal component analysis, and key features are extracted; the method comprises the following steps: evaluating daily nutritional requirements of a user by using a multivariable linear regression model, a Bayesian network and causal inference, predicting a nutritional requirement change trend of the user in a future period of time based on a long-short-term memory network, and optimizing daily diet selection of the user by using a Markov decision process; and finally, generating a personalized nutrition scheme by adopting linear programming and a genetic algorithm, and ensuring that the nutritional requirements and health targets of the user are met. According to the method, personalized and scientific diet suggestions can be provided, and the quality and effectiveness of individual nutrition management are improved.

The invention provides a method for increasing the growth rate of a citrus breeding material, and relates to the field of agricultural science. The method for improving the growth rate of the citrus breeding material comprises the following steps: selecting high-quality seedlings, and selecting citrus seedlings with excellent hereditary characteristics as the breeding material; the soil environment is optimized, the soil structure is improved, and the soil organic matter content is increased; nutrition management: formulating a scientific fertilization scheme including the proportion and the application amount of nitrogen, phosphorus, potassium and trace elements; according to the application of the growth regulator, the plant growth regulator is used for promoting cell division and elongation; disease and pest control: combining biological control and chemical control to control the occurrence of diseases and pests, and regularly monitoring the disease and pest conditions; environment regulation and control: temperature, humidity and illumination conditions are controlled, and a suitable growth environment is created. A scientific fertilization scheme is formulated according to the soil nutrient condition and the nutritional requirements of the citrus, and sufficient nutrients are ensured to be obtained in each growth stage, so that the growth rate is remarkably increased.

The invention relates to the field of intelligent management, and particularly discloses a nutrition management system and method for a patient in a hepatobiliary and pancreatic surgery in a perioperative period, which uses a data analysis and coding technology based on deep learning to perform data arrangement and multi-dimensional time sequence association on vital sign data, and performs semantic embedding and association on a current test result at the same time. And then, fine-grained cross-modal coding is performed on the vital sign multi-dimensional time sequence association features and the test item semantic association features, so that a nutrition management scheme is intelligently generated based on semantic cross-modal coding representation and operation type labels. In this way, the physiological status and inspection characteristics of each patient can be comprehensively captured, and then an exclusive nutrition treatment scheme is made for the patient in a tailored mode. In addition, real-time monitoring and flexible adjustment of patient conditions are supported, and it is ensured that appropriate intervention measures are taken at critical moments.

The invention relates to the field of health management and intelligent terminals, and discloses a nutrition management method and system, a terminal and a storage medium, and the nutrition management method comprises the following steps: an integrated voice recognition module is used for capturing a voice instruction of a user and analyzing a user demand; deploying an augmented reality engine, generating a virtual food model according to a user demand, and displaying a visual effect of the food combination in real time; and establishing a personalized diet database, comprehensively analyzing health data and living habits of the user, and generating a dynamic diet plan. According to the invention, a multi-modal fusion voice recognition and augmented reality scheme is adopted, and a personalized diet database and a sensor network are combined, so that real-time diet management and plan adjustment are realized. The diet health influence is dynamically displayed through an augmented reality simulation tool, flexible intervention is provided through an intelligent reminding system, and the problems that in the prior art, the feedback mode is single, and behavior guidance is not in place are solved.

The invention relates to the technical field of medical health management, in particular to a chronic kidney disease and diabetes collaborative nutrition monitoring and early warning method and system.The method comprises the steps that multi-dimensional physiological indexes, nutrition intake and sleep data of a patient are obtained, and a dynamically-coupled metabolic state topological space is constructed; based on the space, constructing a dual-disease metabolism coupling matrix, analyzing stability characteristics of a metabolism state trajectory, identifying stable and unstable attractors, and calculating a multi-dimensional risk score; a sleep-metabolism synchronism risk prediction model is introduced, and a personalized early warning threshold value is dynamically adjusted; when the risk score exceeds a threshold value, early warning is triggered, and intervention suggestions are generated, the interactive influence of protein metabolism and glycometabolism is quantitatively described from the metabolic mechanism level, and the contradiction of chronic kidney disease and diabetic patients in nutrition management is solved; limitation of a static threshold is broken through, and dynamic risk assessment is realized; sleep factors are creatively integrated, and a new way for improving the metabolic state is provided.

The invention discloses a risk early warning system based on enteral nutrition management of a patient, and belongs to the technical field of medical technology and biomedicine. A risk early warning system based on enteral nutrition management of a patient comprises a patient monitoring module, a score calculation module, a nutrition control module, an early warning notification module, a nutrition scheme adjustment module and a continuous observation and feedback module. The problems that in the prior art, symptoms of critical patients with the acute respiratory distress syndrome are not monitored in time, the regulation efficiency of enteral nutrition supply is low, errors are prone to occurring, and an early warning mechanism is incomplete are solved. By introducing a real-time monitoring and intelligent quantitative evaluation tool, an automatic regulation and control mechanism and multi-level early warning notification and detailed guidance, main problems existing in enteral nutrition management of the severe patient with the acute respiratory distress syndrome at present are effectively solved, and the rehabilitation process and the treatment effect of the patient are remarkably improved.

The invention relates to the technical field of data processing, and provides an AI-based healthy diet nutrition management method and system, and the method comprises the steps: collecting basic health data of a user, carrying out the analysis, obtaining the basal metabolic rate of the user and the daily required calorie, carrying out the matching, obtaining a recommended diet scheme, carrying out the health evaluation of the basal metabolic rate, and carrying out the management of the basic metabolic rate. The method comprises the steps of obtaining a nutrition matching suggestion, matching the nutrition matching suggestion with daily required heat, obtaining a daily diet suggestion, screening recommended diet schemes, obtaining an initial diet suggestion, and adjusting the initial diet suggestion in real time based on the blood glucose level, the blood pressure level and the heart rate level of a user to obtain a target diet suggestion. By collecting the basic health data of the user, generating the diet scheme and monitoring the physical condition of the user in real time, daily diet suggestions are adjusted, and the problems that a traditional method depends on consciousness and accurate recording of the user, and data accuracy and real-time performance are insufficient are solved.

The invention discloses a nutrition recipe intelligent generation system and method, and belongs to the technical field of nutrition information processing and intelligent recommendation. The system is suitable for individual nutrition management of individuals of all ages, and particularly, optimization design is carried out for infant stages of 0-72 months. The system intelligently generates a personalized nutrition recipe based on individual basic information, growth indexes, nutrition standards, available food materials, user preferences and feedback and other multi-dimensional data, and supports nutrition intake evaluation and dynamic optimization. The system comprises core modules of data input, nutritional requirement calculation, recipe generation, nutrition analysis and interactive display and the like, and expands and supports functions of sensitization screening, regional and seasonal adaptation, work and rest linkage, family sharing and the like. Through fusion of individual growth data and environmental conditions, the system realizes scientific and high-adaptability nutrition recommendation, improves feeding convenience and intervention accuracy, and has a wide application prospect.

The invention discloses a fruit and vegetable nutrition dynamic monitoring and intelligent fertilizer supplementing system, belongs to the field of fruit and vegetable planting management systems, replaces a traditional manual observation or regular soil sampling detection mode, effectively avoids subjectivity and hysteresis of manual judgment, can reflect the current nutrition state of crops in real time, provides accurate data support for dynamic nutrition management, and improves the management efficiency. The problem that in the prior art, real-time management is difficult to achieve according to the current nutrition state of crops is solved, meanwhile, accurate matching of the fertilizer type, concentration and dosage with the crop growth stage and environmental conditions is achieved in the fertilizer supplementing process, a traditional one-step nutrition supply mode is avoided, the nutrient absorption efficiency is remarkably improved, and healthy growth of the crops is promoted.

The invention relates to the technical field of postoperative rehabilitation. The spine postoperative intelligent nutrition management method comprises the steps of performing multi-modal data fusion processing based on preoperative sign data, intraoperative blood loss and fluid loss amount and postoperative biochemical indexes of a patient to generate personalized nutrition requirement parameters; performing real-time monitoring and comparison processing on the postoperative diet intake of the patient through intelligent tableware provided with a weight sensor and an image recognition module according to the personalized nutritional requirement parameters, and generating a nutritional intake dynamic map; performing dynamic deviation analysis processing on detection data of the bioelectrical impedance analysis equipment and the saliva biomarker sensor to generate nutrition metabolism feedback data; and fusing the nutrition intake dynamic spectrum and the nutrition metabolism feedback data, carrying out nutrition intervention scheme optimization processing through a reinforcement learning model, generating a dynamic adjustment instruction, and pushing the instruction to a terminal, so as to achieve the technical effects of adapting to individualized requirements, tracking a metabolism state in real time and balancing nutrition intervention accuracy and safety.

The invention provides a CKD nutrition management visual monitoring method and system based on big data, and relates to the technical field of data processing, and the method comprises the steps: carrying out the data preprocessing according to real-time health data, and obtaining a standardized health data set; according to the standardized health data set, evaluating nutritional requirements of the patient, and combining disease progression, individual differences and diet preferences of the patient to generate a personalized nutrition management scheme, the personalized nutrition management scheme including recommended diet, a nutrition supplement scheme and an intake behavior adjustment scheme; according to the personalized nutrition management scheme, a visual display interface is generated, and the visual display interface displays the nutrition state, diet suggestions, potential health risks and predicted effects of the patient; adjusting a personalized nutrition management scheme in real time according to feedback data and health state changes provided by the patient in the use process, and presenting an updated scheme through a visual display interface; the autonomy and accuracy of nutrition management are improved.

The embodiment of the invention discloses a dietary nutrition balance matching generation method and system based on individualized difference requirements, electronic equipment and a storage medium, and relates to the technical field of clinical nutriology. Comprising the following steps: calculating the basal metabolic rate of a user by using a human basal metabolic rate formula according to the age, gender, weight and height of the user; calculating daily required total energy consumption of the user according to the basal metabolic rate and the daily activity state; preliminarily determining intake proportions of carbohydrates, proteins, fats, vitamins and minerals of the user according to national or international nutrition standards on the basis of daily required total energy consumption; the intake proportion is adjusted according to the health condition and the allergy history of the user, and the target intake proportion of carbohydrate, protein and fat is determined; and obtaining nutritional ingredient information of the food materials based on the target intake ratio, and generating an optimal dietary nutrition collocation combination by using a genetic algorithm. The method is suitable for hospital clinical nutrition departments and ward patient nutrition management scenes.

The invention discloses an evaluation method for nutrition management of a large language model. The method comprises the following steps: constructing an evaluation data set; submitting problems in the assessment data set to a to-be-assessed large language model; collecting answers of the big language model for the question, and classifying the answers according to the content of the answers; calculating the answer accuracy of the large language model according to the classification; the method relates to the technical field of big language model evaluation, reduces the influence of human factors and improves the objectivity and reliability of an evaluation result by constructing an evaluation data set and setting a clear evaluation standard, covers a plurality of aspects of nutriology, and has the advantages that the evaluation data set is established, the evaluation standard is set, the evaluation accuracy is improved, and the evaluation efficiency is improved. Comprising multiple dimensions of food and nutriology, individual and group nutrition management, public nutrition and nutrition education, diet management and the like, and the comprehensive ability of the large language model in the field of nutriology can be comprehensively evaluated.

The invention relates to the technical field of medical health, and discloses a pregnancy nutrition management method, device and equipment and a readable storage medium, and the method comprises the steps: obtaining pregnancy portrait data of a target user; generating an individualized nutrition intake target based on the pregnancy portrait data; generating a matched structured diet scheme according to the nutrition intake target and the diet taboo information; receiving an actual diet image uploaded by the user, and performing nutrition intake analysis on the actual diet image to obtain actual nutrition intake data; and dynamically adjusting the structured diet scheme according to the actual nutrition intake data. According to the method, personalized evaluation, intelligent catering and dynamic optimization of pregnancy nutrition management are realized, the scientificity, compliance and continuity of intervention are improved, pregnancy complications can be prevented, and the health of mothers and infants is promoted.

The invention relates to the technical field of intelligent medical treatment and clinical nutrition, and discloses a multi-dimensional sign sensing personalized enteral nutrition infusion regulation and control device which comprises a multi-parameter sign sensing module, an intelligent analysis control module, an adjustable infusion execution module and a man-machine interaction and early warning module. The intelligent nutrition management platform is in communication connection with the modules; the intelligent nutrition management platform is composed of a nutrition screening and evaluation unit and a statistical analysis unit. According to the method, a full link from nutrition risk automatic screening, individualized scheme intelligent generation, bedside safety execution and self-adaptive regulation and control to whole-process data statistical analysis is formed; information integration and initial decision making are automatically completed, manual operation links and cognitive loads are reduced, scientificity and normalization of a treatment scheme based on newest clinical guidelines and patient data are ensured, and medical workers are liberated from tedious transactional work and focus on higher-value clinical judgment.

The present invention includes techniques for food image processing and particularly relates to a method and system for personalized nutrition management with food image recognition models using deep learning. The method comprises: a user side obtains an food image to be taken by a user, and the food image is input into a trained food image recognition models using deep learning to obtain different types of food sub-images; computing the amount of nutrients contained in the food sub-images, and accumulating the nutrients in all the food to obtain the total nutrients intake of the user; setting intake thresholds of various nutrients, and comparing the total intake of various nutrients with corresponding nutrient intake thresholds to obtain a comparison result; according to the comparison result, type and quantity of taken food are adjusted, and nutrition management is completed. The invention associates the food intake information uploaded by the user with other data sets (e.g., recommendations from their nutritional physician) through the server to determine whether the obtained energy and nutrient ratio are appropriate, and finally, the analyzed data is feedbacked to the user, thereby prompting the user to improve the diet plan.

The invention relates to the technical field of data processing, in particular to an intelligent data processing method and system based on surgical nursing, and the method comprises the steps: firstly obtaining food intake and physiological indexes of a patient within a preset time, comparing the food intake and physiological indexes with a standard food intake set, and generating a food intake standard score; in conjunction with the physiological metric, the system determines a real-time feeding score and a total feeding score. By comparing the real-time and total feeding scores at different time points, the system finally generates a feeding balance score of the patient. According to the method, food intake and physiological data are effectively integrated, a scientific and quantitative food intake evaluation tool is provided for surgical nursing, nutrition management of a patient is optimized, nursing quality is improved, the absolute value of the food intake is considered in the evaluation, the relevance between time distribution of food intake and physiological indexes is concerned, and the evaluation accuracy is improved. Therefore, more comprehensive and in-depth patient state information is provided for nursing personnel. Especially, due to the introduction of a feeding balance degree score, an important basis is provided for formulating a more reasonable nutrition intervention scheme.

The invention discloses a nutrition management strategy recommendation method and system for an ICU survival stroke postoperative rehabilitation patient, and relates to the technical field of medical health and artificial intelligence, and the method comprises the steps: obtaining basic physiological indexes, existing examination data and medicine use records of the ICU survival stroke postoperative rehabilitation patient according to a medical record; after data preprocessing, obtaining corresponding character feature representation through a pre-training model, calling a domain knowledge graph to perform knowledge enhancement on the feature representation, and constructing multi-dimensional nutrition and health features; using a graph convolutional neural network to perform learning representation on the multi-dimensional nutrition and health feature corresponding graph structure, extracting a nutrition and health portrait of the patient, and performing nutrition and health state evaluation of the patient; and extracting a personalized nutrition management strategy for recommendation according to the evaluation result of the nutrition health state of the patient. According to the invention, accurate evaluation of the nutrition health state of the rehabilitation patient is realized by combining mass rehabilitation nutrition management knowledge according to existing inspection data, and an accurate and personalized nutrition management scheme is provided.

The invention relates to the field of health management, and discloses a comprehensive personalized nutrition management method, which comprises the following steps: acquiring multi-dimensional health data of a user through user side equipment, including gene information, living habits, exercise frequency and food intake information; analyzing the multi-dimensional health data by using an AI-driven health assessment model, and generating an assessment result of the health state of the user and potential risk factors; and generating a personalized diet plan by using a machine learning algorithm according to the health assessment result. Through multi-dimensional data acquisition and dynamic analysis, the health state of the user is comprehensively monitored, the diet plan is adjusted in real time, and the problem of insufficient static property in the prior art is solved; gene information and living habits are integrated, and a highly personalized effect is achieved; the diet recommendation accuracy is improved through data closed-loop optimization, and the defect that an existing scheme is insufficient in optimization capability is overcome; tLS encryption and distributed storage are adopted, data security is guaranteed, and user trust is enhanced.

The invention relates to the technical field of nutrition management, in particular to a newborn nutrition management method and system based on data analysis, and the method comprises the following steps: collecting newborn heartbeat, respiratory rate and body temperature physiological data, uploading the data to a central processing unit, checking the data with newborn age and historical growth data, correcting the change of physiological indexes, and obtaining a newborn nutrition management result. Preliminary physiological index data are obtained. According to the method, the preliminary physiological index data is deeply analyzed through time sequence analysis, the physiological change trend and nutritional requirements of newborns are accurately grasped, potential nutritional requirement modes can be recognized in real time and compared with existing nutritional plans, key nutritional insufficiency areas are quickly recognized, and the accuracy of the nutritional requirements of the newborns is improved. According to the method, a more personalized nutrition supplement scheme is provided for the newborns, the adaptability and effectiveness of the nutrition scheme are improved, the actual effect of the nutrition adjustment scheme can be effectively detected by monitoring and analyzing the adjusted physiological data difference, and it is ensured that the newborns obtain the optimal nutrition support in the key growth period.

To provide real-time personalized nutrition management and training support by combining individual healthcare data with meal image analysis.SOLUTION: A system comprises: means for collecting individual healthcare data, performing meal image analysis and providing personalized nutrition management; means for supporting individual training; and means for proposing a correction plan on the basis of the individual's capabilities and goals.SELECTED DRAWING: Figure 1

The invention discloses a thick-stem high-yield caulis spatholobi germplasm screening and breeding method suitable for an under-forest habitat. According to the method, a standardized under-forest cultivation system is constructed, spiral winding induction synergistically mediated by plant morphology and plant hormones is implemented, lignification development of stems is enhanced by applying mild mechanical stress with specific parameters, rhizosphere microorganism regulation and systematic nutrition management are synchronously combined, and the yield of the stems is increased. And finally, a multi-dimensional comprehensive evaluation system covering the stem shape, the wood density, the active ingredient content and the under-forest weak light adaptability is established, so that an integrated technical scheme for efficiently and accurately breeding the excellent caulis spatholobi germplasm with thick stem phenotype, high flavone accumulation and strong under-forest weak light tolerance from a large number of candidate germplasm is realized.

The invention discloses an infant nutrition demand prediction method based on machine learning, and belongs to the technical field of machine learning and nutrition demand prediction. Infant body characteristic data and nutrition demand indexes corresponding to the infant body characteristic data determined by a professional physician are acquired; then training a machine learning model by adopting an intelligent optimization algorithm according to the infant body characteristic data and the corresponding nutritional requirement indexes to obtain an infant nutritional requirement prediction model, and finally obtaining to-be-recognized infant body characteristic data input by a user. And dispatching the infant nutrition demand prediction model of the cloud computing center to identify the to-be-identified infant body feature data to obtain an infant nutrition demand prediction result, thereby effectively providing higher nutrition suggestions, assisting common users to realize infant nutrition management, and ensuring healthy growth of infants.

1. The name of this design product: Graphical user interface for a clinical nutrition management module for inpatients of an electronic device. 2. Purpose of this design product: Used for integrated nutrition management of hospitalized patients in doctor's workstations, for an electronic device. 3. The key design point of this design product lies in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: main view. 5. Purpose of the graphical user interface: Used for integrated nutrition management of hospitalized patients in the doctor's workstation: used for nutrition screening, evaluation, nutrition prescription issuance, consultation and other operations for hospitalized patients, as well as preview of the patient's overall nutritional status and visual monitoring of indicators. 6. Human-computer interaction method of the graphical user interface: 1) Click the "Nutrition Order" icon button in the upper right corner of the main view to enter the interface change state diagram 1; 2) Click the "Yes" icon button in the interface change state diagram 1 to enter the interface change state diagram 2; 3) Click the "Not Required" icon button in the main interface change state diagram 2 and enter the relevant options to enter the interface change state diagram 3; 4) Enter a number in the "Gap Percentage" in the interface change state diagram 3 and press the Enter key to enter the interface change state diagram 4; 5) In the interface change state diagram 4, click the "Whole Hospital" button, check the "Serial Number" on the left, click the "Calculate" icon button on the right to enter the interface change state diagram 5; 6) Click the "EN Order" icon button in the interface change state diagram 5 to enter the interface change state diagram 6, enter a number in the "Gap Percentage" in the interface change state diagram 6 and press the Enter key, check the medicine on the left, and click Calculate on the right to refresh the interface to display the calculated value. 7) Click the "Value" button in the NRS2002 score "input box" in the interface change state diagram 6 to enter the interface change state diagram 7.

An object of the system according to the embodiment is to monitor the behavior of a pet, detect a health problem, and take appropriate measures.SOLUTION: A system includes a Web camera, a behavior analysis part, a health detection part, a nutrition management part, and an emergency call part. The web camera monitors the behavior of the pet. The action analysis part analyzes video data acquired by the Web camera. The health detection unit detects a health problem based on the data analyzed by the behavior analysis unit. The nutrition management unit supports daily nutrition management based on the health problem detected by the health detection unit. The emergency call unit automatically transmits an emergency call in an emergency.SELECTED DRAWING: Figure 1

The invention relates to the field of health management and personalized nutrition guidance, and discloses an intelligent nutrition management method and system, an intelligent bracelet and a mobile terminal.The intelligent nutrition management method comprises the following steps that physiological parameters and behavior data of a user are collected in real time; according to the collected physiological parameters and behavior data, a dynamic physiological state model of the user is constructed, and the model describes the change of the physiological state of the user along with time; on the basis of the dynamic physiological state model of the user and a preset health target, personalized diet suggestions of the user are generated through an optimization algorithm; the diet suggestions generated through optimization are fed back to the user in a chart or character mode, the dynamic physiological state model and the diet suggestions are dynamically adjusted based on real-time feedback data of the user, and circulation optimization is achieved. According to the invention, dynamic monitoring and adjustment of the health state of the user can be realized, accurate and personalized diet suggestions are generated, and scientificity and real-time performance of health management are improved.

To accurately grasp individual nutrition states and make nutrition management efficient by inputting results of genetic screening and biological inspection related to metabolism in the body, determining deficient nutrients, and proposing improvement measures.SOLUTION: A system includes: means for inputting a result of genetic screening related to metabolism in the body and determining a deficient nutrient in the body at the point of time of the screening; means for inputting a result of detailed biological inspection such as blood inspection, urine analysis, etc.; and means for determining nutrients considered to be deficient and proposing improvement by meals and supplements.SELECTED DRAWING: Figure 1

The invention provides a systematic pet peaceful feeding method which covers health monitoring, environment regulation and control, nutrition management and ultimate care of pets in the whole life cycle. Physiological indexes (such as heart rate, body temperature and activity amount), behavior modes and environmental parameters (temperature, humidity and illumination) of a pet are monitored in real time by integrating an Internet of Things sensor, a biological data analysis algorithm and automatic equipment, and a feeding strategy is dynamically adjusted in combination with artificial intelligence. For the old and the terminal pets, a terminal management system of multi-mode analgesia, psychological pacification and family collaboration is provided. The method can significantly prolong the healthy life of the pet, reduce the incidence of chronic diseases, and ensure that the pet enjoys a digned and happy state at the end of life. The pet feeding ethics are redefined through technical innovation, balance is achieved between scientific life prolonging and natural law respecting, and a brand new normal form is provided for pet economy and emotional industries.

The invention discloses meal replacement biscuits and a preparation method thereof, and belongs to the technical field of food processing. The meal replacement biscuit is composed of coarse cereals, cereals, beans, functional plants and a nutrition enhancer according to specific weight percentages. The preparation method comprises the steps of raw material pretreatment, mixing, tempering, forming, gradient heating baking, cooling and packaging. Through scientific compounding and systematic nutrition enrichment of various natural coarse cereals, beans and functional plants, the defects that an existing meal replacement product is single in raw material and unbalanced in nutrition are overcome, and the obtained product is comprehensive in nutrition, good in taste, portable and easy to eat and suitable for various crowds needing nutrition management or convenient diet.

This invention discloses a six-stage precision feeding standard fresh food meal formula for dogs and its preparation method, belonging to the pet food field. Addressing the lack of precise, stage-specific nutritional management in existing canine fresh food, this invention proposes a six-stage feeding system based on the canine life cycle. The six stages include: puppyhood, adulthood, early seniority, middle seniority, advanced seniority, and special periods. This system provides a basic transitional formula and derives specialized formulas for each stage based on a set of dynamic nutritional adjustment rules. The puppy formula is further subdivided into four sub-stages. The preparation method includes standardized steps such as stage determination, ingredient processing, nutritional fortification, and texture adaptation. This invention achieves precise, safe, and easy-to-operate home fresh food feeding for dogs throughout their entire life cycle and under special conditions.