China's livestock equipment industry

2026-04-07 17:42:10

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The integration of China's livestock equipment industry and AI is accelerating t

The integration of China's livestock equipment industry and AI is accelerating the transition from automation to intelligence, forming a new breeding paradigm centered on the 'perception decision execution' loop. AI technology is deeply embedded in four core scenarios: feeding, environmental control, health monitoring, and individual recognition. Muyuan has deployed 1.56 million sets of intelligent feeding systems, combined with an average of 900 million pieces of data per day to achieve precise nutrition supply for each pig; Zhengda's 'Dr. Pig' AI environmental control algorithm dynamically regulates temperature and humidity, with an error controlled within ± 0.5 ℃; Wen Group has achieved a revolutionary upgrade of feed formula from experience to data through the construction of a native chicken nutrition database by Liu Songbai's team; The AI visual recognition system achieves 92% -96% non-contact individual identity locking in cattle and sheep farms, combined with sound monitoring and track inspection robots, with an accuracy rate of over 95% for disease warning. On the equipment side, TMR mixers, intelligent medicated bath machines, composite fecal leakage boards and other hardware are fully integrated into the Internet of Things. Yangxiang's 'Precision Feeding Workshop' system achieves full chain intelligent feeding of raw material scanning, cloud matching, and pipeline direct delivery, saving over 50 yuan in annual grain for a single pig. At the policy level, the National Action Plan for Smart Agriculture (2024-2028) sets a target of achieving an agricultural production informatization rate of 32% by 2028. The Ministry of Agriculture and Rural Affairs' special interest subsidy policy for 2026 will include smart livestock equipment in the key support list, promoting equipment updates and technology popularization. The industry is shifting from 'selling equipment' to 'outputting AI farming systems', building a full stack intelligent ecosystem covering data collection, algorithm optimization, and equipment linkage.


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