现代农业解决方案政策动态

Industry Pain Points

Reliance on manual experience

Production sites rely heavily on manual inspection and expert experience. Pest, disease, epidemic, and abnormal environmental risks are detected late, affecting yield and quality stability.

Production data is fragmented

Production, environment, equipment, input, and cost data is fragmented, making unified production judgment and operating analysis difficult.

Prediction and optimization are difficult

Yield, quality, and resource input are hard to predict and optimize accurately, causing volatility, waste, and difficulty replicating management experience in scaled operations.

Solution

Build a business fact base

Integrate growth status, environment, equipment, inputs, yield, quality, cost, and other multi-source data, and use agricultural ontology to form unified business understanding.

Deploy an agricultural multi-agent system

Include Agents for pest and biosecurity alerts, environmental control, production management, and input optimization, supporting risk identification, root-cause analysis, and trend simulation.

Connect the agricultural production decision loop Integrate IoT, agricultural machinery, robotics, and business systems to form a perception-judgment-execution-feedback loop for agricultural production decisions.

Expected Outcomes

Earlier Risk Detection

Pest, disease, epidemic, and abnormal environmental risks are identified earlier, making production more stable.

Better Resource Allocation

Inputs are used more precisely and resource waste is reduced.

Experience Codification and Reuse

Management experience can be codified and reused, continuously improving scaled operations.

Improved Automation Capability

The perception, judgment, execution, and feedback loop is progressively improved, strengthening automated production capability.