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Multi-parameter monitoring system for water quality in fish ponds

Background

Our country is rich in water resources. Therefore, there are many reservoirs and fish ponds in many cities and regions. These reservoirs and fish ponds usually cover a relatively large area and are particularly suitable for ecological aquaculture. Water is the basic environment for all fish to survive, and good water quality will not only affect the life and health of fish. The body color and development of some fish will be affected. To do a good job in fish farming, we must start with the basic work of managing water well. Water quality multi-parameter monitoring system can be used for monitoring.

Water quality monitoring
Water quality monitoring
Water quality multi-parameter monitoring system

The key parameters that affect the water quality of fish ponds are mainly water temperature, light, dissolved oxygen, ammonia nitrogen, and nitrite. These factors are difficult to distinguish with the naked eye. Although there is often such a saying in fish pond farming that "the upper pond is green, the lower pond is yellow and green". That is, the water in the pond should be green in the morning, and the water in the pond should be yellow-green in the afternoon. But this is only a common breeding law, and it is difficult to be accurate and reliable. Can not guarantee the output.

The aquaculture water quality monitoring system adopts advanced intelligent water quality sensors, wireless transmission systems, wireless communications, early warning systems, intelligent management systems, etc. Can carry out all-round remote monitoring and management of water quality. A large amount of historical data can be stored and analyzed to guide production management. It can ensure the high yield and profit of aquaculture and avoid environmental problems caused by water pollution.

The online water quality monitoring technology can transmit the data collected at the monitoring point to the user end in a very short time to ensure the timeliness and validity of the data. Compared with traditional manual sampling and monitoring, it not only simplifies the cumbersome procedure, but also saves the monitoring time.

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