Pasture operation optimization method and system based on dynamic data intelligent prediction

A dynamic data-driven approach integrates environmental sensors and real-time cow data to optimize pasture management, addressing inefficiencies in traditional methods by enhancing herd stability and reducing heat stress, improving productivity and financial resilience.

CN120318006APending Publication Date: 2025-07-15NINGXIA MUHEJIA AGRICULTURAL & ANIMAL HUSBANDRY TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202510443558.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-10
Publication Date
2025-07-15

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Abstract

The invention relates to the technical field of operation optimization, and discloses a pasture operation optimization method and system based on dynamic data intelligent prediction, and the method comprises the steps: reading a cattle ear tag in real time through RFID equipment, registering newborn calf information, dynamically calibrating a mother calf rate parameter, deploying temperature and humidity, calculating a heat stress index and an effective ammonia concentration through an ammonia gas sensor, and carrying out the intelligent prediction through the RFID equipment. And abnormal temperature, humidity and ammonia gas threshold data are filtered, real-time cattle herd data and biological parameters are coupled, a dynamic balance equation of cows and reserved cattle is constructed, the production rate is dynamically corrected in combination with the heat stress index and the ammonia gas concentration, and a reserved cattle on-fence constraint mechanism is strengthened. According to the method, the THI index of the cowshed is reduced through the fan strategy, the dry matter feed intake in the heat stress period is increased through the sodium bicarbonate supplement scheme, the breeding time is optimized, the survival rate of the calves is increased, environment-biology-finance multi-dimensional coupling is achieved, and the heat stress problem is converted into quantifiable and predictable decision parameters.
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