A. L. Amaral

Quantification of the CBD-FITC conjugates surface coating on cellulose fibres

BackgroundCellulose Binding Domains (CBD) were conjugated with fluorescein isothiocyanate (FITC). The surface concentration of the Binding Domains adsorbed on cellulose fibres was determined by fluorescence image analysis.ResultsFor a CBD-FITC concentration of 60 mg/L, a coating fraction of 78% and 110% was estimated for Portucel and Whatman fibres, respectively. For a saturating CBD concentration, using Whatman CF11 fibres, a surface concentration of 25.2 × 10-13 mol/mm2 was estimated, the equivalent to 4 protein monolayers. This result does not imply the existence of several adsorbed protein layers.ConclusionIt was verified that CBDs were able to penetrate the fibres, according to confocal microscopy and TEM-immunolabelling analysis. The surface concentration of adsorbed CBDs was greater on amorphous fibres (phosphoric acid swollen) than on more crystalline ones (Whatman CF11 and Sigmacell 20).

Correlation between sludge settling ability and image analysis information using partial least squares

In the last years there has been an increase on the research of the activated sludge processes, and mainly on the solid-liquid separation stage, considered of critical importance, due to the different problems that may arise affecting the compaction and the settling of the sludge. Furthermore, image analysis procedures are, nowadays considered to be an adequate method to characterize both aggregated and filamentous bacteria, and increasingly used to monitor bulking events in pilot plants. As a result of that, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments. Moreover, the large amount of activated sludge data collected with the image analysis implementation can be subsequently treated by multivariate statistical procedures such as PLS. In the current work the implementation of image analysis and PLS techniques has shown to provide important information for better understanding the behavior of activated sludge processes, and to predict, at some extent, the sludge volume index. As a matter of fact, the obtained results allowed explaining the strong relationships between the sludge settling properties and the free filamentous bacteria contents, aggregates size and aggregates morphology, establishing relevant relationships between macroscopic and microscopic properties of the biological system.

Identifying different types of bulking in an activated sludge system through quantitative image analysis

The present study proposes an image analysis methodology for the identification of different types of disturbances in wastewater treatment activated sludge systems. Up to date, most reported image analysis methodologies have been used in activated sludge processes with the aim of filamentous bulking detection, however, other disturbances could be foreseen in wastewater treatment plants. Such disturbances can lead to fluctuations in the biomass contents, affecting the mixed liquor suspended solids (MLSS), and in the sludge settling ability, affecting the sludge volume index (SVI). Therefore, this work focuses on predicting the MLSS and SVI parameters for different types of disturbances affecting an activated sludge system. Four experiments were conducted simulating filamentous bulking, zoogleal or viscous bulking, pinpoint floc formation, and normal operating conditions. Alongside the MLSS and SVI determination, the aggregated and filamentous biomass contents and morphology were studied as well as the biomass Gram and viability status, by means of image analysis.

Monitoring of activated sludge settling ability through image analysis: validation on full-scale wastewater treatment plants

In recent years, a great deal of attention has been focused on the research of activated sludge processes, where the solid–liquid separation phase is frequently considered of critical importance, due to the different problems that severely affect the compaction and the settling of the sludge. Bearing that in mind, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in eight different wastewater treatment plants, for a combined period of 2 years. The monitoring of the activated sludge contents allowed for the detection of bulking events proving that the developed image analysis methodology is adequate for a continuous examination of the morphological changes in microbial aggregates and subsequent estimation of the sludge volume index. In fact, the obtained results proved that the developed image analysis methodology is a feasible method for the continuous monitoring of activated sludge systems and identification of disturbances.

Semi-automated recognition of protozoa by image analysis

A programme was created to semi-automatically analyse protozoal digitised images. Principal Component Analysis technique was used for species identification. After data collection and mathematical treatment, a three-dimensional representation was generated and several protozoa (Opercularia, Colpidium, Tetrahymena, Prorodon, Glaucoma and Trachelophyllum) species could be positively identified.

Automatic identification of activated sludge disturbances and assessment of operational parameters

Activated sludge systems are prone to be affected by changes in operating conditions leading to problems such as pinpoint flocs formation, filamentous bulking, dispersed growth, and viscous bulking. These problems are often related with the floc structure and filamentous bacteria contents. In this work, a lab-scale activated sludge system was operated sequentially obtaining filamentous bulking, pinpoint floc formation, viscous bulking and normal conditions. Image processing and analysis techniques were used to characterize the contents and structure of aggregated biomass and the contents of filamentous bacteria. Further principal component and decision trees analyses permitted the identification of different conditions from the collected morphological data. Furthermore, a partial least squares analysis allowed to estimate the sludge volume index and suspended solids key parameters. The obtained results show the potential of image analysis procedures, associated with chemometric techniques, in activated sludge systems monitoring.

Characterization of activated sludge abnormalities by image analysis and chemometric techniques

This work focuses on the use of chemometric techniques for identifying activated sludge process abnormalities. Chemometric methods combined with image analysis can improve activated sludge systems monitoring and minimize the need of analytical measurements. For that purpose data was collected from aggregated and filamentous biomass, biomass composition on Gram-positive/Gram-negative bacteria and viable/damaged bacteria, and operational parameters. Principal component analysis (PCA) was subsequently applied to identify activated sludge abnormalities, allowing the identification of several disturbances, namely filamentous bulking, pinpoint flocs formation, and zoogleal bulking as well as normal conditions by grouping the collected samples in corresponding clusters.

Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment : a review

Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.

The study of protozoa population in wastewater treatment plants by image analysis

Protozoa are important microorganisms for the ecosystem balance in wastewater treatment plants. A procedure for their semi-automated identification and counting based on image analysis is proposed. The main difficulty is segmentation of the protozoa as most of them are in contact with the sludge. The protozoa are characterized by the size of their silhouette (area and length) and three shape factors (elongation, circularity and eccentricity). They are identified after projecting the resulting 5D space into a 3D space of principal components. The rate of automated identification is actually higher than 50% for some of the species commonly found in activated sludge.

Development of a Method Using Image Analysis for the Measurement of Cellulose-Binding Domains Adsorbed onto Cellulose Fibers

The surface concentration of CBD‐FITC conjugates, adsorbed on cellulose fibers, was determined by image analysis. The program consists of two scripts, the first dedicated to the elaboration of the calibration curve. The emission of fluorescent light, detected by image analysis, is correlated with the concentration of CBD solutions. This calibration is then used (second script) to determine the concentration of CBDs adsorbed on cellulosic fibers. This method allows the direct estimation of the surface concentration of adsorbed CBDs, which usually is not accurately calculated from depletion studies, since the surface area is hardly known. By observing different spots in the surface of the fibers, site‐specific information is obtained. It was verified that the physically heterogeneous fibers exhibit different amounts of adsorbed CBDs.