18 results about "Optimal nutrition" patented technology

The invention relates to a multi-objective collaborative optimization hydroponic lettuce nutrient solution concentration time sequence dynamic regulation and control method. Compared with the prior art, the defect that an optimal nutrient solution concentration scheme needed by hydroponic crop time sequence dynamic growth interacting with the environment is difficult to determine is overcome. The method comprises the following steps: constructing a time sequence group photosynthetic rate prediction model and a time sequence group moisture utilization efficiency prediction model; constructing a multi-objective optimization model; solving a Pareto solution set of the multi-objective optimization model; constructing a nutrient solution concentration time sequence regulation and control model; dynamically regulating the concentration of the hydroponic lettuce nutrient solution in a time sequence. According to the method, a non-dominated sorting multi-target genetic algorithm is adopted to solve the multi-target problem of a time sequence group photosynthetic rate prediction model and a time sequence group water utilization efficiency prediction model, and an optimal balance regulation target value is obtained by combining a uniformly distributed population strategy, non-dominated sorting, crowding degree calculation, an elitist strategy and a population updating mechanism. The problem of dynamic regulation and control of the nutrient solution concentration for plant time sequence growth is effectively solved.

The present invention discloses a semi-artificial diet for Tuta absoluta larvae, a preparation method thereof and an application thereof. In the present invention, 1000 mL of water is boiled, and after it is stable, 0.5 - 1 g of sorbic acid, 0.5 - 1 g of sodium p-hydroxybenzoate and 0.1 - 0.2 g of thiabendazole are added, and quickly stirred and melted. Subsequently, compound vitamins are added, and after stirring evenly, 500 - 550 g of malt embryos are added and stirred into a dough. When the temperature drops below 30 °C, 150 - 200 g of tomato leaf powder is added and stirred and mixed evenly to obtain the semi-artificial diet for Tuta absoluta larvae. The components of the semi-artificial diet of the present invention can not only meet the nutritional requirements of test insects, but also have an optimal compound ratio of different components, and particularly give the best nutritional ratio. At this ratio, the survival rate, pupation rate and emergence rate from larvae to pupae are high, and the deformity rate of pupae is low.

The invention relates to a precise nutrition decision-making system and method based on offline reinforcement learning, and belongs to the field of medical informatization. According to the method, patient medical record data are collected and preprocessed, and patient nutrition state indexes, a nutrition intervention scheme and nutrition state benefits after nutrition intervention are defined as a state space, an action space and a reward function respectively. And then, constructing a model by using an offline reinforcement learning algorithm, so that the intelligent agent learns to select an optimal nutrition intervention strategy under different nutrition conditions. And finally, evaluating the performance of the model in a test data set, and comparing the influence of different intervention schemes on the nutrition state of the patient. According to the invention, the nutrition intervention effect of the inpatient can be effectively improved, the reasonable distribution of medical resources is promoted, and the application value is high.

The invention discloses a method for intelligently regulating and controlling the carbon nitrogen ratio of straw and livestock and poultry manure and efficiently decomposing the straw and the livestock and poultry manure, and belongs to the technical field of agricultural waste resourceful treatment technology and environmental engineering, and the method comprises the following steps: S1, carrying out online component detection on input straw and livestock and poultry manure, automatically mixing the materials to a preset initial carbon-nitrogen ratio based on a detection result, and inoculating a microbial agent; meanwhile, on the basis of the initial material component data, a personalized digital twinborn body of the batch of materials is constructed; the in-situ spectrum technology is used for monitoring the change of the carbon-nitrogen ratio in the pile body in real time, the unbalance trend of the pile body is predicted in combination with the digital twinborn model, the execution unit is driven to carry out local and trace material supplement adjustment, and the lag mode of traditional static matching and off-line sampling inspection is fundamentally changed. The dynamic closed-loop regulation and control can accurately control the fluctuation range of the carbon-nitrogen ratio in the whole decomposition period within + / -5, and a continuous and stable optimal nutrition environment is created for microorganisms.

The present application relates to the technical field of insect feeding, in particular to a feeding method for feeding Spodoptera exigua larvae with switchgrass. The method comprises the following steps: placing 2nd instar larvae in a culture container, placing one larva in each culture container, putting 1-4 pieces of switchgrass leaf segments into the culture container every day, sealing the gap between the upper cover and the lower bottom of the culture container and leaving a ventilation opening, putting 2-4 pieces of switchgrass leaf segments into the culture container every day when the larvae grow to 3rd instar-4th instar, keeping the gap between the upper cover and the lower bottom of the culture container, putting 2-5 pieces of switchgrass leaf segments into the culture container every day when the larvae grow to 5th instar-6th instar, keeping the gap between the upper cover and the lower bottom of the culture container, and feeding the larvae until they pupate. The present application feeds Spodoptera exigua larvae individually, feeds the larvae with a specific amount of switchgrass leaf segments at different instars and controls the contact amount with air, thereby providing highly suitable food and optimal nutrition and feeding environment for the larvae and improving the survival rate of the larvae.

The invention provides an optimal design method for a vegetation recovery nutritional agent formula of a power grid project slash in a high-altitude region, and the method comprises the steps: collecting growth data and landform data of pioneer plants in a target region, and constructing a vegetation growth demand model of the target region based on the growth data and the landform data; acquiring a nutrient element detection result of the multi-region soil sample of the target region, and inputting the nutrient element detection result into the vegetation growth demand model for plant growth nutrition supply simulation; and according to the plant growth nutrition supply simulation result, respectively determining an optimal nutritional agent component proportion corresponding to each region in the power grid project slash, and generating a corresponding nutritional agent formula and sending the nutritional agent formula to a display end. According to the method, accurate optimization of a nutritional agent formula in the vegetation recovery process of the high-altitude region is realized, so that the survival rate and the growth speed of vegetation recovery of the high-altitude region are effectively improved, and ecological restoration of a power grid project slash of the high-altitude region is promoted.

The present invention relates generally to the field of myo-inositol-containing compositions for use in the prevention of premature rupture of membranes (PROM) and related disorders and / or conditions. The composition may be a nutritional composition, for example, a maternal nutrition composition. The composition may be specifically designed to provide optimal nutrition to a woman who wishes to become pregnant or to a pregnant woman.

The present invention discloses a nutritional composition and method of using and making the nutritional composition. The nutritional composition is a hydrolyzed pea protein based nutrient composition for use in both enteral and oral feeding, and provides a non-allergenic diet for providing optimal nutrition to users. The nutritional composition is made from organic and plant-based ingredients. The nutritional composition has pea protein hydrolysates, phytochemical extracts, fatty acids, organic ingredients free of the top eight allergens and corn, and prebiotic fiber. The nutritional composition is provided in liquid form for enteral and / or oral feeding.

The present invention discloses a nutritional composition and method of using and making the nutritional composition. The nutritional composition is an intact pea protein based nutrient composition for use in both enteral and oral feeding, and provides a non-allergenic diet for providing optimal nutrition to users. The nutritional composition is made from organic and plant-based ingredients. The nutritional composition has pea protein, phytochemical extracts, fatty acids, organic ingredients free of the top eight allergens and corn, and prebiotic fiber. The nutritional composition is provided in liquid form for enteral and / or oral feeding.

The invention relates to a preparation method of plukenetia volubilis linneo tea, which comprises the following steps: picking rattan fruits, rattan stems and rattan leaves in a proper growth period, drying, proportioning according to a certain proportion, considering nutrition, cost, taste and color during proportioning, preferably selecting the proportion of 1: (0.60-0.98) to enable the nutrition, the cost and the taste to be optimal, and finally mixing the three components for fermentation to obtain the plukenetia volubilis linneo tea. The plukenetia volubilis tea can bring nutrition and convenience to drinkers and is low in cost.

We provide the system. [Solution] A communication means for receiving animal health check information and intake history data, An analytical means that generates an optimal nutrition plan for an individual based on the information received by the aforementioned communication means, A display means for presenting the nutrition plan generated by the aforementioned analysis means, A management system for ordering food based on the aforementioned nutrition plan and automating its delivery, A learning method for receiving feedback on the animal's response and changes in health status and applying it to the next nutrition plan, A system that includes this.

An object of a system according to an embodiment is to analyze meal data, visualize health risks, and provide optimal nutrition advice.SOLUTION: A system includes a reception part, an analysis part, a visualization part, and a provision part. The reception unit inputs meal data. The analysis unit analyzes the meal data input by the reception unit. The visualization unit visualizes the risk on the basis of a result analyzed by the analysis unit. The providing unit provides optimal nutrition advice based on the risk visualized by the visualizing unit.SELECTED DRAWING: Figure 1

The application provides an egg laying hen feeding scheme adjustment method and system based on molting image recognition, and relates to the technical field of intelligent breeding, comprising: acquiring a plurality of multi-angle body surface image sequences of a plurality of individual egg laying hens in a target chicken population synchronously collected under natural light conditions; performing semantic segmentation according to the multi-angle body surface image sequences to obtain a feather contour segmentation atlas set; performing group feature joint extraction according to the feather contour segmentation atlas set to obtain a multi-dimensional feature tensor simultaneously representing individual characteristics and group distribution information; performing group state collaborative inference according to the multi-dimensional feature tensor to obtain a three-dimensional probability distribution vector; performing group nutrition demand mapping according to the three-dimensional probability distribution vector to obtain an optimal nutrition parameter combination suitable for the entire chicken population; and performing feeding scheme generation according to the optimal nutrition parameter combination to obtain a feeding instruction stream. The application effectively improves the accuracy and adaptability of nutrition regulation during the molting period.

To provide optimal nutrition management appropriate to individual users.SOLUTION: A nutrition management system using generative AI, includes means for analyzing a user's preferences, past eating habits, and nutritional needs to suggest optimal meal plans for each individual, means for the AI to create custom menus while taking into account balanced nutrients and calories based on information supervised by professional nutritionists, and means for users to make an order via an application or website and have nutrients delivered on a regular basis.SELECTED DRAWING: Figure 1

The present invention relates to a method for temporal dynamic regulation of the nutrient solution concentration of hydroponic lettuce for multi-objective collaborative optimization, which solves the defect that it is difficult to determine the optimal nutrient solution concentration scheme required for the temporal dynamic growth of hydroponic crops interacting with the environment compared with the prior art. The present invention includes the following steps: constructing a prediction model for the temporal population photosynthetic rate and a prediction model for the temporal population water use efficiency; constructing a multi-objective optimization model; solving the Pareto solution set of the multi-objective optimization model; constructing a temporal regulation model for the nutrient solution concentration; and temporally dynamically regulating the nutrient solution concentration of hydroponic lettuce. The present invention uses a non-dominated sorting multi-objective genetic algorithm to solve the multi-objective problems of the prediction model for the temporal population photosynthetic rate and the prediction model for the temporal population water use efficiency, and obtains the optimal balanced regulation target value by combining the uniform distribution population strategy, non-dominated sorting, crowding degree calculation, elite strategy, and population update mechanism, effectively solving the problem of dynamic regulation of the nutrient solution concentration for the temporal growth of plants.

The application discloses a fish-vegetable symbiotic system water planting vegetable nitrogen nutrition gain-loss identification method, equipment, medium and product, and relates to the field of aquaculture. The method comprises the following steps: taking water planting vegetables in a fish-vegetable symbiotic system as a production group, and setting water planting vegetables with the same climate conditions and the best nutrient supply as a control group; collecting crown layer image data of the production group and the control group by using a depth camera; determining the nitrogen nutrition condition indexes of the vegetables in the production group and the control group based on a lightweight instance segmentation model according to the crown layer image data of the production group and the control group; taking the nitrogen nutrition condition indexes of the vegetables in the control group as a nitrogen nutrition gain-loss identification reference value; and judging the nitrogen nutrition gain-loss condition of the vegetables in the production group according to the nitrogen nutrition gain-loss identification reference value and the nitrogen nutrition condition indexes of the vegetables in the production group. The application can realize accurate identification of the nitrogen nutrition gain-loss condition of the vegetables that adapts to climate change.

A device for enhanced growth of microbial cultures, comprising: a primary culture chamber configured to contain a microbial culture and a culture medium; a plurality of sensors arranged in the primary culture chamber for continuously measuring at least one of the following: temperature, pH, oxygen concentration and nutrient content in the culture medium; a control unit coupled to the plurality of sensors, the control unit configured to receive data from the sensors and automatically adjust environmental parameters within the culture chamber to maintain optimal conditions for microbial growth; a nutrient delivery system in fluid communication with the primary culture chamber, the nutrient delivery system configured to deliver nutrients to the culture medium based on the real-time requirements of the microbial culture; a stirring mechanism that ensures uniform mixing of the culture medium and even distribution of nutrients and gases throughout the culture medium; wherein the control unit is further configured to regulate the nutrient delivery system and the agitation mechanism to maintain optimal nutrient and gas concentrations based on sensor data.

The system according to this embodiment aims to evaluate individual health status and aging risk based on dietary data and to provide advice on optimal nutritional balance and dietary habits. [Solution] The system according to the embodiment comprises a reception unit, an analysis unit, an evaluation unit, and a provision unit. The reception unit receives input of meal data. The analysis unit analyzes the data received by the reception unit. The evaluation unit evaluates the risk of AGE accumulation based on the results obtained by the analysis unit. The provision unit provides optimal nutritional balance and dietary advice based on the results evaluated by the evaluation unit.