Both spectral and time-resolved fluorometry have important potential applications in on-line microbial monitoring for chemical and biological life support systems. Spectral fluorometers operating with remote fiber-optic probes have demonstrated their potential for detecting, identifying and quantifying bacteria and fungi in recirculated plant nutrient solutions. This same spectral fluorometry can play a similar role in detecting and identifying pathogenic bacteria in water supplies. Time-resolved fluorometers, also operating in the on-line fiber-optic mode, have exceptional sensitivity and are capable of detecting extremely low bacterial population densities in both air and water in life support applications.Fluorometric data, both spectral and time-resolved, are characterized by background luminescence and interfering, overlapping spectra from various living and non-living fluorometric sources. Sophisticated pattern recognition techniques are required to identify and quantify microbial species of interest in this complex measurement environment. Advanced pattern recognition methods employing neural networks supervised by genetic algorithms have been quite successful in identifying and quantifying bacteria and fungi in continuous on-line monitoring applications.