Feeding method and device capable of accurately regulating and controlling feed intake of sows

By using a dynamic feedback regulation mechanism based on individual physiological state and an intelligent feeding device, the problem of low precision in controlling sow feed intake has been solved, achieving precise and adaptive fully automated control throughout the entire process, thereby improving breeding efficiency and sow reproductive performance.

CN121464981APending Publication Date: 2026-02-06TIANJIN DAHONG HENGXIANG MASCH CO LTD
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Patent Information

Application Number
CN202511824804.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-05
Publication Date
2026-02-06

AI Technical Summary

Technical Problem

Existing technologies have low precision in controlling sow feed intake, resulting in low breeding efficiency, high costs, difficulty in achieving standardized operations, and risks of feed waste and health problems.

Method used

By constructing a dynamic feedback regulation mechanism with individual physiological state as the core variable, and integrating multi-source heterogeneous data acquisition, adaptive feeding curve calling and interactive feed control, the sow's feed intake can be precisely regulated. The intelligent feeding device adopts a data acquisition module, a curve management module, a feed control module and a data analysis module.

Benefits of technology

It achieves precise, adaptive, and fully automated control of sow feeding behavior, improving breeding efficiency, reducing reliance on human experience, reducing feed waste and health risks, and improving piglet survival rate and sow reproductive performance.

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Abstract

The embodiment of the invention discloses a feeding method and device capable of accurately regulating and controlling the feed intake of sows. The method comprises the following steps: identifying an individual identity through an electronic ear tag, and collecting backfat thickness, body condition score and weight data by using an inspection robot; dynamically calling a standard feeding curve based on the fetus number and the body condition score, and finely adjusting the target feed intake in combination with the body weight change trend; a quantitative or interactive feeding mode is adopted in the gestation period, feeding is carried out with different meals of wet mixed feed in the lactation period, and the feed-water ratio is dynamically adjusted; meanwhile, a data closed loop is constructed, a feeding strategy is optimized through big data analysis, and abnormal individuals are visualized. According to the scheme, precise self-adaptive regulation and control of the feeding behavior of the sow in the whole breeding cycle are achieved, and the feed efficiency and the breeding performance are remarkably improved.
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