Analytica Chimica Acta 642 (2009) 94–101 Contents lists available at ScienceDirect Analytica Chimica Acta journal homepage: www.elsevier.com/locate/aca Correlation between sludge settling ability and image analysis information using partial least squares D.P. Mesquita a , O. Dias a , A.M.A. Dias a , A.L. Amaral a,b , E.C. Ferreira a,∗ a IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057 Braga, Portugal b Instituto Superior de Engenharia de Coimbra, Instituto Politécnico de Coimbra, Rua Pedro Nunes, Quinta da Nora, 3030-199 Coimbra, Portugal article info Article history: Received 10 September 2008 Received in revised form 1 November 2008 Accepted 19 March 2009 Available online 24 March 2009 Keywords: Activated sludge Image analysis Sludge volume index Partial least squares abstract 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 bac- teria, 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 filamen- tous bacteria contents, aggregates size and aggregates morphology, establishing relevant relationships between macroscopic and microscopic properties of the biological system. © 2009 Elsevier B.V. All rights reserved. 1. Introduction In activated sludge systems, an adequate balance between the different types of bacteria is necessary to ensure an efficient pol- lution removal, good sludge settling abilities and low suspended solid levels in the final effluent. After the oxidation of the organic matter in the aerated tank, the flocculated biomass is separated from the treated effluent by means of their settling ability in the settling tank. The settling phase is considered a critical stage of the process in which filamentous bulking and deflocculation processes are the most common problems, causing the decrease of the sludge settling ability and effluent quality deterioration [1]. Poor settling biomass is normally attained by an improper aggregate’s formation and filamentous bacteria proliferation, resulting in lower clarifier efficiency. Usually, some malfunctions may occur within the acti- vated sludge system such as pin-point flocs bulking, filamentous bulking, dispersed growth and zoogleal growth [2]. Image analysis procedures, based on microscopic observations, are nowadays considered to be a feasible method to characterize quantitatively aggregates and filamentous bacteria, and subse- quently used to monitor bulking events in pilot and full plants [3,4], ∗ Corresponding author. Tel.: +351 253 604 407; fax: +351 253 678 986. E-mail address: ecferreira@deb.uminho.pt (E.C. Ferreira). exceeding the initial manual quantification of filamentous bacteria proposed by Jenkins et al. [5]. Bulking can be caused by both fila- mentous and non-filamentous factors, affecting in different ways the sludge settling ability which can be detected by image analy- sis methodologies [4,6–12]. The combination of settling properties and the parameters obtained from image analysis may offer power- ful information enabling immediate interventions on the biological system. In fact, the study developed by Sezgin [13] established that the sludge volume index (SVI) is strongly influenced by floc size and filamentous bacteria contents. Other authors [14–16] used auto- mated image analysis to relate the microorganism’s morphology in biological systems with the sludge settling properties. The settling ability can be subsequently related with the microscopic parame- ters using multivariable statistical technique, such as partial least squares (PLS) regression and principal component analysis (PCA) [4,6]. A close correlation between the filamentous bacteria per sus- pended solids ratio and the SVI was indeed achieved by Amaral and Ferreira [4] during filamentous bulking events. Encouraged by the success of image analysis procedures over the last years in a broad range of different areas, the present work uses an automated image analysis method to characterize the activated sludge structure, focusing on the prediction ability of sludge settling properties, in both good settling and filamentous bulking periods. In this sense, the collected images were treated in order to char- acterize the aggregated and filamentous bacteria, thus originating 0003-2670/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.aca.2009.03.023