Early detection method of enterococci for water quality control with digital image processing techniques

Abstract

Enterococci are part of the normal intestinal flora of humans and animals. They have long been recognized as important human pathogens and are increasing. Enterococcus faecalis and Enterococcus faecium are the most prevalent species cultured from humans, accounting for more than 90 % of clinical isolates. Due to their ubiquity in human feces and persistence in the environment, enterococci have been adopted as indicators of human fecal pollution in water. One of the methods used in water quality control is the membrane filtration technique (Membrane Filtration — MF) (ISO7899-2). This method requires the cultivation of bacteria (enterococci), which is a great disadvantage because the time required to obtain the final result is between 24 and 48 hours. This work proposes a design of a system that detects, with optical sensors, the presence of simulated bacterial colonies in the early stages of the cultures (14–24 h). An image processing system (ZooMat) has been developed with Matlab to detect simulated colonies at early stages, which allows you to process the image before counting. To obtain detection and a count of bacterial colonies on each image, we integrate NICE (an open source, free software) to our system, to gather the results. The entire system allows detection of particles at about 60 μm.