Aquaculture production is inherently intert wined with its environmental role as a habitat for organisms and the equilibrium of environmental parameters. Maintaining the balance of biogeochemical cycles in aquaculture environments is an adaptive appro ach that must be upheld from the preparation of the medium, through maintenance processes, to the management of generated waste. The nitrogen (N) and phosphorus (P) cycle are fundamental earth cycles and capable of serving as macro nutrients aquaculture environments that can transform into other compounds, thereby determining the fertility levels in aquaculture pond media. Nitrogen (N) transforms into ammonia, nitrite, and nitrate, while phosphorus transforms into phosphate. This analysis aims to evaluate the transformation status of nutrients within chlorophyll-a and planktonic bacteria in aquaculture environment. Data was analyzed using Canberra distance and Principal Component Analysis (PCA).
Nitrogen and phosph orus serve as limiting factors in aquatic environments due to their significant roles in bacterial and plankton stability. Balancing and controlling the N and P systems in vannamei shrimp aquaculture environment require maintenance primarily through bacterial and plankton remediation technologies. With this technology, it is possible to influence the abundance of nitrifying and denitrifying bacteria. Nitrifying bacteria was found in an abundance of 4.6 x 106 CFU/mL, while denitrifying bacteria was found in an abundance of 5.76 x 107 CFU/mL. These results showed that the nitrogen cycle is able in its maximum capacity.
The measurement of nitrogen (N) and phosphorus (P) levels from the initial stages within shrimp pond reservoirs is imperative in aquaculture. This is primarily due to their roles as fundamental nutrient sources for organisms such as chlorophyll a, bacteria, and phytoplankton. The results of the analysis showed that these elements had a significant correlation (strong positive) between other parameters, all of which are consistently grouped within quadrant IV during Principal Component Analysis (PCA) (Figure 1). The co-placement of three fishponds within this quadrant suggest shared characteristics in the terms of elemental composition and other analyzed parameters. Strategic emphasis on variables exhibiting low leverage excesses in PCA is essential for spotlighting those with substantial contributions to data patterns while minimizing irrelevant information.