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the precise regulation technology of medicinal greenhouses helps upgrade the quality of cannabis while traditional greenhouses are facing transformation challenges-0

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The precise regulation technology of medicinal greenhouses helps upgrade the quality of cannabis, while traditional greenhouses are facing transformation challenges

Time : 2025-04-29

With the improvement of quality requirements in the medicinal cannabis cultivation industry, the traditional greenhouse cultivation model has problems such as inaccurate control of the internal environment and frequent occurrence of pests and diseases.

Recently, China Fengzhiyuan Agricultural Enterprise has launched the "Intelligent Greenhouse Solution for Medicinal Plants". Through innovations such as precise environmental control and customized cultivation techniques, it has significantly improved the quality and survival rate of cannabis, attracting industry attention.

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Dynamic temperature and humidity control system

The medicinal greenhouse is equipped with Internet of Things sensors to monitor the temperature (with an accuracy of ±0.5℃) and humidity (with an accuracy of ± 3%RH) in real time, and automatically adjust them in combination with the growth model of cannabis. The systematic error is controlled within 1℃/2%, while traditional greenhouses rely on manual experience, and the fluctuation range can reach ±3℃/10%

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Precise water and fertilizer integration

Drip irrigation or tidal irrigation is adopted, combined with soil moisture sensors (EC value monitoring), to maintain the substrate electrical conductivity of 1.2-1.8 mS/cm

The NPK ratio is dynamically adjusted according to the growth stage of the medicinal materials. For instance, during the growth period of Sanqi, a high-phosphorus and high-potassium formula is required, with a system error rate of less than 1%. Compared with traditional flooding irrigation and fertilization, it saves 30% of fertilizer and increases the content of the effective component saponin by 18%.

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Real-time monitoring of leaf surface lesions through image recognition can provide early warnings 72 hours in advance, reducing losses by more than 50%.❤

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