Determination of the humidity of the leaf surface of greenhouse plants - Foliar humidity sensor

The cultivation of flowers, seedlings, and off-season vegetables in the greenhouse requires intelligent control so that the climate parameters can be in the best state of plant growth, so that the yield and quality can be greatly improved. But at present, there are not many intelligent control applications for agricultural greenhouses in China. On the one hand, it is because such equipment is expensive and not suitable for national conditions; on the other hand, a plant has different optimum climate requirements for different growth periods, and different plants are similar. The optimal climate requirements during the growing season are also different and even within the greenhouse can be automated. To this end, we have developed an automatic control system for agricultural greenhouses based on the growth needs of plants using electronic technology, biotechnology, and computer control technology. The determination of leaf surface humidity generally requires the use of a leaf surface humidity sensor for monitoring.

The collection of greenhouse environmental climate parameters is based on sensors, which mainly include soil moisture sensors, leaf surface humidity sensors, air temperature and humidity integration sensors, light intensity sensors, and CO2 sensors. These are the sources of information for the monitoring system and relate to the detection of the entire system. Reliability and accuracy of data analysis and control. The leaf surface humidity sensor is mainly used to control the surface humidity of the leaves of the plants in the greenhouse.

The measurement and analysis of the leaf surface humidity sensor found that the function of the expert decision-making system includes information collection, problem identification, problem solving, etc. It is based on the user's task requirements to analyze, judge, and use the knowledge provided by the expert knowledge base to solve problems. Judging from the decision-making environment of this system, on the one hand, it involves the rich knowledge factor of experts, on the other hand, the decision-making is based on real-time measurement. Under the networking control mode, the decision-making process is as follows: The user passes the human-machine interface, only By inputting the plant type and growth period of the designated number greenhouse into the expert management system, the host can automatically generate a reasonable control plan based on the best climate parameters recommended by the agronomist and the actual greenhouse climate data from the RS-485 communication line. Then through the communication line, the control command is sent to the climate controller in the numbered greenhouse, and intelligent control is implemented through the servo.

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