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.