Water-quality monitoring technology has been taken a great attention in aquaculture because of increasing aquatic products and impact of food safety vicious incidents. In order to meet the technology requirements of water-quality monitoring in multi-parameter, dynamic, and networked monitoring, a waterquality dynamic monitoring system was developed to monitor multi-parameter water-quality variables such as water temperature, pH, dissolved oxygen, electrical conductivity, oxidation reduction potential dynamically, and communicate with remote information servers in a high security. As result of a two-years testing experiment in a seawater aquiculture company, relative errors of each water-quality parameter measured by the instrument were less than 5%, data lost percentage of remote communication was less than 3%, and power energy consumption was less than 13W. Therefore, the water-quality dynamic monitoring system as a node infrastructure of wireless sensor networks can be used to achieve a distributed water-quality network monitoring system in a large-scale aquaculture farm, or to construct a distributed water-quality monitoring network system in multipoint of different cities for aquaculture farm and administration section.

Abstract. The low fertilizer utilization at growing season and environment pollution coursed by unreasonable fertilization are becoming global outstanding problems in agricultural production. Scientific and reasonable fertilization based on rapid and nondestructive plant nutrient detection will be a valuable solution for solving above problems. In this study, spectral transmittance in wavelength ranged from 300 to 1100 nm, chlorophyll content and nitrogen content of rice and cucumber leaves treated with culture solution in five different nitrogen levels were measured. According to the correlation analysis between them, 560, 650, and 720 nm as feature wavelengths and 940 nm as reference wavelength were determined for nitrogen detection. Correlation analysis between 21 spectral feature parameters composed by the transmittance at above wavelength, the leaf chlorophyll content and nitrogen content, and combined with their regression examination indicated that spectral feature parameters of (T940 -T560) / (T940 + T560), log (T940/T560) and log (T940/T650) are useful to conduct plant nutrient diagnosis with less than 8% relative error in rice and cucumber leaves. Therefore, the above spectral feature parameters as plant nitrogen indicators can be used to estimate the chlorophyll content and nitrogen content, furthermore support for non-destructive plant nutrient detection and fertilizer recommendation based on testing soil.

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