8 results about "Growth parameter" patented technology

The invention discloses an Internet of Things supervision method and system applied to strawberry growth management, and relates to the technical field of smart agriculture, and the method comprises the steps: integrating historical strawberry growth full-cycle multi-dimensional data, constructing a strawberry growth knowledge graph, taking different growth stages as nodes, and obtaining the optimal growth interval of each node; tracking a dynamic evolution track of the soil saline-alkali parameters on the time sequence, and constructing a dynamic prediction model of the target soil saline-alkali parameters; based on a multi-dimensional sensor, monitoring growth parameters in real time, inputting a knowledge graph to judge the growth node of the strawberry in the time period, predicting the trend by integrating the growth parameters in the time period and soil saline-alkali parameters, calculating the deviation degree of the growth node in the time period and the optimal growth interval, and evaluating whether the growth parameters in the time period are in a safe range or not; if it is judged that the growth is in the abnormal growth risk period, a layered early warning mechanism is implemented, a case with the highest similarity in the knowledge graph is paired, and a solution is rapidly provided. The method has the beneficial effects that the yield and quality of strawberries are improved.

The invention discloses dsRNA for targeted regulation of a freshwater shrimp PKA-R1 gene and an obtaining method and application of the dsRNA, and belongs to the technical field of biology.Firstly, the freshwater shrimp PKA-R1 gene is obtained, then a gene segment with the sequence of SEQ ID NO: 3 is obtained through RNA interference and other technologies, dsPKA-R1 is synthesized through the gene segment, and after the synthesized dsPKA-R1 is injected into the pericardial cavity of a freshwater shrimp, it is proved that the dsPKA-R1 can slow down growth of the freshwater shrimp through growth parameter comparison.

The invention discloses a multi-crop growth synchronous monitoring system based on remote sensing, and relates to the technical field of agricultural remote sensing monitoring. Comprising a remote sensing data acquisition module, a primary perception and feature preliminary screening module, a depth feature extraction and coupling reasoning module, a primary cross check and uncertainty quantification module, an iterative optimization and secondary check feedback module and a result synthesis and decision output module. According to the multi-crop growth synchronous monitoring system based on remote sensing, synchronous parallel processing of crop identification and growth parameter inversion is realized by constructing a depth feature extraction and coupling reasoning module, and the problem of insufficient monitoring precision caused by similar spectral features under a multi-crop mixed planting condition is effectively solved. According to the system, a crop special model is automatically matched through a dynamic routing mechanism, and the accuracy and reliability of inversion results of growth parameters of different crops are improved in combination with multiple verification and an iterative optimization process.

The application provides an environment-driven edible mushroom growth prediction method and system, and belongs to the technical field of intelligent agriculture, and comprises the following steps: constructing an environment feature vector corresponding to each time according to environment data in a to-be-predicted period; inputting the environment feature vector into a dynamic parameter mapping model trained based on an actual growth parameter label to obtain a dynamic growth parameter corresponding to each time; calling a dynamic biological growth equation in which a static constant term is reconstructed into a dynamic variable parameter; and assigning the dynamic growth parameter to the dynamic biological growth equation to obtain a biomass growth prediction value at each time. The application fuses the flexibility of data driving and the interpretability of a mechanism model by constructing a mapping relationship between an environment and a mechanism parameter by using machine learning and driving a mechanism equation by using a dynamic parameter, so that high-precision prediction of the biomass of edible mushrooms under a complex dynamic environment is realized.

The utility model provides a device for measuring beef cattle growth parameters, and relates to the technical field of beef cattle growth measurement. The device for measuring the growth parameters of the beef cattle comprises a base, a weighing device is embedded in the top of the base, two fixing frames are fixedly connected to the top of the base, a measuring mechanism for measuring the width of the beef cattle is slidably connected to the fixing frames, and the measuring mechanism comprises a two-way screw rotationally arranged on the fixing frames. A bidirectional screw is driven to rotate, the two side faces of a cattle body are clamped under the action of a movable block, an extrusion rod and side transverse plates, the width of the cattle is measured under the action of an infrared distance measuring sensor and a reflecting plate, the weight of the cattle is weighed through a weighing device, and the left and right sides of the cattle are limited through the two side transverse plates; the head of the cattle penetrates through a circular through groove in the movable frame, the head of the cattle is fixed under the action of the fixing mechanism, and it is prevented that the head of the cattle shakes left and right, and measurement of workers is hindered.

The present application belongs to the technical field of broiler feeding monitoring, and particularly relates to a broiler feeding prediction system and method based on nutritional requirements. The present application realizes accurate prediction and management of broiler feeding by dynamically monitoring the growth parameters of broilers and combining historical successful breeding data. By comparing the growth differences between the breeding chicken group and the successfully bred chicken group, growth abnormalities can be found in time and corresponding measures can be taken, effectively reducing the uncertainty in the growth process of broilers. At the same time, by adjusting the feed formula, the best nutritional supply for broilers is ensured, further reducing the growth differences among broilers. After the feed is adjusted, the weight gain of the group to be improved can be tracked in real time to ensure the optimization effect of the feed formula. Through dynamic evaluation of the sub-section verification period, the improvement situation can be understood in time and accurately, so as to continuously optimize the feeding strategy and achieve the purpose of improving the overall breeding efficiency.

The embodiment of the specification provides a kind of agricultural product monitoring method, the method comprises: obtaining the variety information of agricultural product, planting area information and growth image;Based on variety information, planting area information and growth image, the growth parameter of agricultural product is predicted by vigor prediction model;Wherein, growth parameter includes one or more of the growth cycle, plant height, crown width and flower amount of agricultural product;Vigor prediction model includes feature extraction layer and vigor prediction layer, feature extraction layer is used to process growth image, and determine image feature;Vigor prediction layer is used to process image feature, variety information, planting area information, and determine growth parameter;When growth parameter does not satisfy preset condition, send early warning reminder to target terminal.

This application discloses an intelligent matching method and system for lamb feeding programs based on growth prediction, relating to the field of lamb feeding technology. The method includes: acquiring a set of growth parameters and a set of feeding behavior parameters for the target lamb; predicting growth status and acquiring feeding proficiency parameters and rumen development parameters; acquiring developmental synergy parameters to determine the lamb's developmental pattern; and intelligently matching a lamb feeding program based on the feeding proficiency parameters, rumen development parameters, and the lamb's developmental pattern. This solves the technical problems of traditional lamb feeding programs relying on experience-based judgment, which leads to strong subjectivity and significant lag, and the inability of standardized feeding patterns to meet the individualized needs of lambs.