Validation of a new image analysis procedure for quantifying filamentous bacteria in activated sludge

2014 ◽  
Vol 70 (6) ◽  
pp. 955-963 ◽  
Author(s):  
Ewa Liwarska-Bizukojc ◽  
Marcin Bizukojc ◽  
Olga Andrzejczak
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Activated Sludge ◽  
Analysis Procedure ◽  
Automated Image Analysis ◽  
Filamentous Bacteria ◽  
Image Processing And Analysis ◽  
Manual Counting ◽  
Analysis Application ◽  
Activated Sludge Systems

Quantification of filamentous bacteria in activated sludge systems can be made by manual counting under a microscope or by the application of various automated image analysis procedures. The latter has been significantly developed in the last two decades. In this work a new method based upon automated image analysis techniques was elaborated and presented. It consisted of three stages: (a) Neisser staining, (b) grabbing of microscopic images, and (c) digital image processing and analysis. This automated image analysis procedure possessed the features of novelty. It simultaneously delivered data about aggregates and filaments in an individual calculation routine, which is seldom met in the procedures described in the literature so far. What is more important, the macroprogram performing image processing and calculation of morphological parameters was written in the same software which was used for grabbing of images. Previously published procedures required using two different types of software, one for image grabbing and another one for image processing and analysis. Application of this new procedure for the quantification of filamentous bacteria in the full-scale as well as laboratory activated sludge systems proved that it was simple, fast and delivered reliable results.

scholarly journals Author Correction: Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Julian Bär ◽  
Mathilde Boumasmoud ◽  
Roger D. Kouyos ◽  
Annelies S. Zinkernagel ◽  
Clément Vulin
Keyword(s):  
Image Analysis ◽  
Growth Dynamics ◽  
Colony Growth ◽  
Automated Image Analysis ◽  
Analysis Application

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Conditions Favoring Proliferation of Glycogen Accumulating Organisms for Excess Biological Carbon Removal in Treating Nutrient Deficient Wastewater

2017 ◽  
Vol 61 (3) ◽  
pp. 149 ◽  
Author(s):  
Andrea Jobbágy ◽  
Bernadett Kiss ◽  
Vince Bakos
Keyword(s):  
Activated Sludge ◽  
Continuous Flow ◽  
The Other ◽  
N Availability ◽  
Filamentous Bacteria ◽  
Severe Deficiency ◽  
And Performance ◽  
Experimental Stage ◽  
Activated Sludge Systems ◽  
P Sources

Impact of marginal availability and severe deficiency of nitrogen on the growth of glycogen accumulating organisms (GAOs) and performance of anaerobic/aerobic activated sludge systems treating nutrient deficient wastewater was investigated at marginal availability and severe deficiency of phosphorus. Two continuous-flow lab-scale systems were operated simultaneously fed by model winery wastewater, one with marginal availability and the other one at severe deficiency of nitrogen. In the second experimental stage, marginal availability of P was converted into severe deficiency by interrupting external dosing.Common practice of dosing N- and P-sources to marginal availability caused enhanced proliferation of filamentous bacteria leading to poor biomass settling and instable operation. At marginal N-availability accumulation of GAOs started when conditions became deficient for phosphorus. In severe lack of nitrogen GAOs overgrew filaments, and outcompeted phosphorous accumulating organisms (PAOs) initially present in the seed. Stable and good performance could be maintained even after withdrawal of phosphorous dosing.

scholarly journals Automated Image Analysis for Quantitative Fluorescence In Situ Hybridization with Environmental Samples

2007 ◽  
Vol 73 (9) ◽  
pp. 2956-2962 ◽  
Author(s):  
Zhi Zhou ◽  
Marie Noëlle Pons ◽  
Lutgarde Raskin ◽  
Julie L. Zilles
Keyword(s):  
Image Analysis ◽  
In Situ Hybridization ◽  
Fluorescence In Situ Hybridization ◽  
Soil Sample ◽  
Environmental Samples ◽  
Swine Manure ◽  
Automated Image Analysis ◽  
Cell Aggregates ◽  
Manual Counting

ABSTRACT When fluorescence in situ hybridization (FISH) analyses are performed with complex environmental samples, difficulties related to the presence of microbial cell aggregates and nonuniform background fluorescence are often encountered. The objective of this study was to develop a robust and automated quantitative FISH method for complex environmental samples, such as manure and soil. The method and duration of sample dispersion were optimized to reduce the interference of cell aggregates. An automated image analysis program that detects cells from 4′,6′-diamidino-2-phenylindole (DAPI) micrographs and extracts the maximum and mean fluorescence intensities for each cell from corresponding FISH images was developed with the software Visilog. Intensity thresholds were not consistent even for duplicate analyses, so alternative ways of classifying signals were investigated. In the resulting method, the intensity data were divided into clusters using fuzzy c-means clustering, and the resulting clusters were classified as target (positive) or nontarget (negative). A manual quality control confirmed this classification. With this method, 50.4, 72.1, and 64.9% of the cells in two swine manure samples and one soil sample, respectively, were positive as determined with a 16S rRNA-targeted bacterial probe (S-D-Bact-0338-a-A-18). Manual counting resulted in corresponding values of 52.3, 70.6, and 61.5%, respectively. In two swine manure samples and one soil sample 21.6, 12.3, and 2.5% of the cells were positive with an archaeal probe (S-D-Arch-0915-a-A-20), respectively. Manual counting resulted in corresponding values of 22.4, 14.0, and 2.9%, respectively. This automated method should facilitate quantitative analysis of FISH images for a variety of complex environmental samples.

scholarly journals Development of an image analysis procedure for identifying protozoa and metazoa typical of activated sludge system

2007 ◽  
Vol 41 (12) ◽  
pp. 2581-2589 ◽  
Author(s):  
Y.P. Ginoris ◽  
A.L. Amaral ◽  
A. Nicolau ◽  
M.A.Z. Coelho ◽  
E.C. Ferreira
Keyword(s):  
Image Analysis ◽  
Activated Sludge ◽  
Analysis Procedure ◽  
Activated Sludge System

Use of image analysis and rheological studies for the control of settleability of filamentous bacteria: application in SBR reactor

2001 ◽  
Vol 43 (3) ◽  
pp. 27-33 ◽  
Author(s):  
C. Dagot ◽  
M. N. Pons ◽  
M. Casellas ◽  
G. Guibaud ◽  
P. Dollet ◽  
...  
Keyword(s):  
Image Analysis ◽  
Sequencing Batch Reactor ◽  
Batch Reactor ◽  
Automated Image Analysis ◽  
Volume Index ◽  
Filamentous Bacteria ◽  
Sludge Volume Index ◽  
Floc Size ◽  
First Results

To monitor the ability of flocs to settle in Sequencing Batch Reactor sludge, two methods were tested during two operation cycles. Firstly, an automated image analysis procedure has been tested to quantify the floc size and the length and number of filaments. Secondly, rheological measurements (Bingham viscosity and shear stress) have been used to characterise the dispersion of the sludge which can reflect the cohesive strength of aggregates and so the influence of filamentous bacteria on rheological properties. These results were compared with settling parameters such as Sludge Volume Index or settling velocity. Correlations between the measured parameters with image analysis and parameters such as Sludge Volume Index have been obtained. If it is more difficult to analyze rheological results, it seems however that the thixotropy and the Bingham viscosity distinguish poor settlement owing to some filamentous bulking. The first results are promising, although they require confirmation in the long term.

Qualifying Glass Surfaces by Scratch Test with Integrated Image Processing

2009 ◽  
Vol 409 ◽  
pp. 267-274
Author(s):  
Maria Berkes Maros ◽  
Attila Fazekas ◽  
Péter Barkóczy ◽  
Szilvia Szeghalmy ◽  
Zsuzsanna Koncsik
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Residual Stresses ◽  
Information Content ◽  
Scratch Test ◽  
Analysis Procedure ◽  
Test Method ◽  
Current Paper ◽  
Optical Methods ◽  
Glass Surfaces

Residual stresses of production origin superimposed with the operational stresses influences the reliability of glass products. The most widely used procedures for their detection and qualification are optical methods that can not be utilized for testing of non-transparent glasses. A recently developed glass qualifying procedure based on scratch test with integrated image processing is applicable for evaluating the residual stresses in surface of both the transparent and non-transparent glasses. The reliability of the suggested test method is greatly dependent on the information content provided by the involved image analysis procedure. The current paper introduces the principle, and methodology of the test method, furthermore presents the latest results gained by applying an improved algorithm of the image processing.

scholarly journals Dilution and Magnification Effects on Image Analysis Applications in Activated Sludge Characterization

2010 ◽  
Vol 16 (5) ◽  
pp. 561-568 ◽  
Author(s):  
D.P. Mesquita ◽  
O. Dias ◽  
R.A.V. Elias ◽  
A.L. Amaral ◽  
E.C. Ferreira
Keyword(s):  
Image Analysis ◽  
Activated Sludge ◽  
Image Acquisition ◽  
Careful Consideration ◽  
High Biomass ◽  
Sludge Characterization ◽  
Bacterial Content ◽  
Selection Of ◽  
Activated Sludge Systems

AbstractThe properties of activated sludge systems can be characterized using image analysis procedures. When these systems operate with high biomass content, accurate sludge characterization requires samples to be diluted. Selection of the best image acquisition magnification is directly related to the amount of biomass screened. The aim of the present study was to survey the effects of dilution and magnification on the assessment of aggregated and filamentous bacterial content and structure using image analysis procedures. Assessments of biomass content and structure were affected by dilutions. Therefore, the correct operating dilution requires careful consideration. Moreover, the acquisition methodology comprising a 100× magnification allowed data on aggregated and filamentous biomass to be determined and smaller aggregates to be identified and characterized, without affecting the accuracy of lower magnifications regarding biomass representativeness.

Characterisation of activated sludge by automated image analysis

2001 ◽  
Vol 9 (3) ◽  
pp. 165-173 ◽  
Author(s):  
Mauricio da Motta ◽  
Marie-Noëlle Pons ◽  
Nicolas Roche ◽  
Hervé Vivier
Keyword(s):  
Image Analysis ◽  
Activated Sludge ◽  
Automated Image Analysis
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