Functional selection of bacteria in an activated sludge reactor for application in saline wastewater treatment in Kerkennah, Tunisia

Boujelben, Ines; Sabri, Shabad; Pelt, Jos van; Makhlouf, Mohamed Ben; Gdoura, Radhouane; Khannous, Lamia

doi:10.1007/s13762-020-02928-1

Cited by 2 publications

(2 citation statements)

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“…The specific nature of the biological wastewater treatment plant operation does not guarantee complete degradation of carbon compounds (Letshwenyo et al, 2020). Consequently, this leads to migration of the pollutants present in wastewater to the aquatic environment (Arias et al, 2020;Boujelben et al, 2020). In addition to carbon compounds, the treated wastewater may also contain residual organic forms of nitrogen and ammonium nitrogen collectively described as TKN (Petrovski et al, 2020).…”

Section: Research Results and Discussionmentioning

confidence: 99%

Studia Quaternaria

Ofman

2022

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The aim of the statistical analyses carried out was to identify similarities and to point out differences between the various tributaries of the Narew River, to identify the factors and processes responsible for the transformations occurring in the aquatic environment and finally, to identify the main sources of pollution in the river catchment. For the purposes of statistical analysis, the results of studies conducted as part of diagnostic monitoring by the General Inspectorate for Environmental Protection in 2017–2018 were used. The studies included 8 measurement points located directly on the Narew River and 17 points located on its selected left and right tributaries. Analysis of the collected results indicates that the chemical condition of the water in the Narew catchment is assessed as being poor. This observation may be due to the fact that the Narew catchment is mainly used for agricultural purposes and, in addition, there is a relatively large number of potential anthropogenic sources. As part of the analysis, two potential sources of pollution affecting water quality in the Narew catchment were identified, which include surface run-off and treated wastewater inflow.

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Section: Research Results and Discussionmentioning

confidence: 99%

Studia Quaternaria

Ofman

2022

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“…2023, 13, 12406 2 of 14 activated sludge play a pivotal role in achieving treatment effects. Notably, the quantity and diversity of these microorganisms exhibit noticeable fluctuations with changes in process operational conditions [3]. Therefore, monitoring changes in microbial communities is significant when dealing with wastewater.…”

Section: Introductionmentioning

confidence: 99%

Microorganism Detection in Activated Sludge Microscopic Images Using Improved YOLO

Kong,

Shen

2023

Applied Sciences

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Wastewater has detrimental effects on the natural environment. The activated sludge method, a widely adopted approach for wastewater treatment, has proven highly effective. Within this process, microorganisms play a pivotal role, necessitating continuous monitoring of their quantity and diversity. Conventional methods, such as microscopic observation, are time-consuming. With the widespread integration of computer vision technologies into object detection, deep learning-based object detection algorithms, notably the You Only Look Once (YOLO) model, have garnered substantial interest for their speed and precision in detection tasks. In this research, we applied the YOLO model to detect microorganisms in microscopic images of activated sludge. Furthermore, addressing the irregular shapes of microorganisms, we developed an improved YOLO model by incorporating deformable convolutional networks and an attention mechanism to enhance its detection capabilities. We conducted training and testing using a custom dataset comprising five distinct objects. The performance evaluations used in this study utilized metrics such as the mean average precision at intersections over a union threshold of 0.5 (mAP@0.5), with the improved YOLO model achieving a mAP@0.5 value of 93.7%, signifying a 4.3% improvement over the YOLOv5 model. Comparative analysis of the improved YOLO model and other object detection algorithms on the same dataset revealed a higher accuracy for the improved YOLO model. These results demonstrate the superior performance of the improved YOLO model in the task of detecting microorganisms in activated sludge, providing an effective auxiliary method for wastewater treatment monitoring.

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Functional selection of bacteria in an activated sludge reactor for application in saline wastewater treatment in Kerkennah, Tunisia

Cited by 2 publications

References 32 publications

Studia Quaternaria

Studia Quaternaria

Microorganism Detection in Activated Sludge Microscopic Images Using Improved YOLO

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