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New System for Automated Detection of Pathogens in Water Samples

Texas AgriLife Research has developed a system for automatic detection of potential microscopic pathogens in water samples.

Dr. Suresh Pillai, Texas A&M University’s AgriLife Research scientist and professor of microbiology, informed that this system is more precise and faster as compared to using microscopes to detect ordinary pathogens in water.

Pillai and his research team has been focusing on this topic since 1996 when he suggested that scientists will have to evolve a method to use automated image analysis system that replaces humans, which will help to fine tune the quest for pathogens. Pillai revealed that by 2000 his team demonstrated that it was possible to develop this system. His team searched for a commercial partner during the next nine years for using this technology for market applications.

Ultimately Pillai selected Houston-based Smart Imaging Technology for commercializing this technology and both of them solicited more funds from the Texas Emerging Technology Fund for making this process practically viable. Pillai explained that Smart Imaging Technology is in its final stage to render this detection system online.

Pillai further elaborated that initially a slide is placed under a microscope, it will scan the microscope automatically and mark potential items of interest, then the software developed by the project team will focus on each potential item and examine it to check if it is the correct image that is based on various parameters created to detect the pathogens.

This automated system was created particularly to find giardia and cryptosporidium, which are pathogens transmitted through water and cause severe diarrhea in persons whose immune systems are compromised. These pathogens spread out globally through drinking water that is contaminated.

This technology will find many applications, according to Pillai. These applications include fee-based service to detect pathogens, teaching tool for graduate and under graduate students, employees’ training tools, as an aid to researchers focusing on protozoan pathogens, and so on. Pillai added that the automatic microscopic pathogen detection capability can also be provided through the Web. Such automation capability would make available a computerized system for global round the clock pathogen detection applications.

Source: http://agriliferesearch.tamu.edu

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