Characterization of water quality using IoT (Internet of Things), plankton and expression of virus-like particles in vannamei shrimp ponds of different constructions

This study aimed to analyze the effect of pond construction on physical and chemical water quality, plankton community, bacterial density and virus-like particles (VLPs) intensity. The approach for measuring water quality was done by using Internet of Things (IoT), while for identifying the presence of VLPs a confocal laser scanning microscope was used. Both methods were expected to accelerate the detection of the physical, chemical and biological water quality. This study was conducted in six ponds (three concrete ponds and three plastic liner ponds) in Situbondo Regency, East Java, Indonesia, from July to September 2020. The water was sampled in the middle of the pond and replicated four times. Four water quality parameters, consisting of temperature, DO, pH and salinity, were measured using IoT. Other quality parameters consisted of water level, hardness, alkalinity, NH4+, NO2, total organic matter (TOM) and total bacteria were measured manually using a standard equipment. Plankton collection was performed eight times by sampling pond water. The pond built with concrete had higher water levels, NH4+, TOM, total bacteria and VPLs, but lower plankton abundance and taxa richness. In contrast, the plastic liner ponds had a higher temperature, brightness, DO, pH, salinity, hardness, NO2, and alkalinity. The TOM and total bacteria had a strong correlation with temperature and water levels. Chlorophyceae dominated the plankton sample, followed by Cyanobacteria and Chryotophyceae. The yields of shrimp production in concrete ponds were higher than those in the plastic liner pond. The application of IoT to measure water quality and of the confocal laser scanning microscopy to identify the presence of VLPs can characterize the aquatic environments faster.