The impact of DO and salinity on microbial community in poly(butylene succinate) denitrification reactors for recirculating aquaculture system wastewater treatment.

The interactions between environmental factors and bacterial community shift in solid-phase denitrification are crucial for optimum operation of a reactor and to achieve maximum treatment efficiency. In this study, Illumina high-throughput sequencing was applied to reveal the effects of different operational conditions on bacterial community distribution of three continuous operated poly(butylene succinate) biological denitrification reactors used for recirculating aquaculture system (RAS) wastewater treatment. The results indicated that salinity decreased OTU numbers and diversity while dissolved oxygen (DO) had no obvious influence on OTU numbers. Significant microbial community composition differences were observed among and between three denitrification reactors under varied operation conditions. This result was also demonstrated by cluster analysis (CA) and detrended correspondence analysis (DCA). Hierarchical clustering and redundancy analysis (RDA) was performed to test the relationship between environmental factors and bacterial community compositions and result indicated that salinity, DO and hydraulic retention time (HRT) were the three key factors in microbial community formation. Besides, Simplicispira was detected under all operational conditions, which worth drawing more attention for nitrate removal. Moreover, the abundance of nosZ gene and 16S rRNA were analyzed by real-time PCR, which suggested that salinity decreased the proportion of denitrifiers among whole bacterial community while DO had little influence on marine reactors. This study provides an overview of microbial community shift dynamics in solid-phase denitrification reactors when operation parameters changed and proved the feasibility to apply interval aeration for denitrification process based on microbial level, which may shed light on improving the performance of RAS treatment units.

Simultaneous ammonia and nitrate removal in an airlift reactor using poly(butylene succinate) as carbon source and biofilm carrier.

In this study, an airlift inner-loop sequencing batch reactor using poly(butylene succinate) as the biofilm carrier and carbon source was operated under an alternant aerobic/anoxic strategy for nitrogen removal in recirculating aquaculture system. The average TAN and nitrate removal rates of 47.35±15.62gNH4-Nm(-3)d(-1) and 0.64±0.14kgNO3-Nm(-3)d(-1) were achieved with no obvious nitrite accumulation (0.70±0.76mg/L) and the dissolved organic carbon in effluents was maintained at 148.38±39.06mg/L. Besides, the activities of dissimilatory nitrate reduction to ammonium and sulfate reduction activities were successfully inhibited. The proteome KEGG analysis illustrated that ammonia might be removed through heterotrophic nitrification, while the activities of nitrate and nitrite reductases were enhanced through aeration treatment. The microbial community analysis revealed that denitrifiers of Azoarcus and Simplicispira occupied the dominate abundance which accounted for the high nitrate removal performance. Overall, this study broadened our understanding of simultaneous nitrification and denitrification using biodegradable material as biofilm carrier.

Biological denitrification using poly(butylene succinate) as carbon source and biofilm carrier for recirculating aquaculture system effluent treatment.

Nitrate removal is essential for the sustainable operation of recirculating aquaculture system (RAS). This study evaluated the heterotrophic denitrification using poly(butylene succinate) as carbon source and biofilm carrier for RAS wastewater treatment. The effect of varied operational conditions (influent type, salinity and nitrate loading) on reactor performance and microbial community was investigated. The high denitrification rates of 0.53 ± 0.19 kg NO3(-)-N m(-3) d(-1) (salinity, 0‰) and 0.66 ± 0.12 kg NO3(-)-Nm(-3) d(-1) (salinity, 25‰) were achieved, and nitrite concentration was maintained below 1mg/L. In addition, the existence of salinity exhibited more stable nitrate removal efficiency, but caused adverse effects such as excessive effluent dissolved organic carbon (DOC) and dissimilation nitrate reduce to ammonia (DNRA) activity. The degradation of PBS was further confirmed by SEM and FTIR analysis. Illumina sequencing revealed the abundance and species changes of functional denitrification and degradation microflora which might be the primary cause of varied reactor performance.

Prediction of shelled shrimp weight by machine vision.

The weight of shelled shrimp is an important parameter for grading process. The weight prediction of shelled shrimp by contour area is not accurate enough because of the ignorance of the shrimp thickness. In this paper, a multivariate prediction model containing area, perimeter, length, and width was established. A new calibration algorithm for extracting length of shelled shrimp was proposed, which contains binary image thinning, branch recognition and elimination, and length reconstruction, while its width was calculated during the process of length extracting. The model was further validated with another set of images from 30 shelled shrimps. For a comparison purpose, artificial neural network (ANN) was used for the shrimp weight predication. The ANN model resulted in a better prediction accuracy (with the average relative error at 2.67%), but took a tenfold increase in calculation time compared with the weight-area-perimeter (WAP) model (with the average relative error at 3.02%). We thus conclude that the WAP model is a better method for the prediction of the weight of shelled red shrimp.