**Abstract**

It is well-known that photosynthetic cells of various microalgae species display distinct fluorescent properties. The efficiency of self-fluorescence excitation and emission at different wavelengths depends on the structure of photosynthetic system and particularly on the structure of antenna complex of specific strains. The peculiar structure of blue-green algae light-harvesting complex allows to discriminate and classify known and new cells up to species/strain level by means of microscopic spectroscopy. In this chapter, a novel fluorescent spectroscopic technique for microalgae species discrimination will be presented. This method is based on a special data processing of a set of fluorescent spectra, obtained from a single photosynthetic cell of microalgae, particularly from cyanobacterial cells. According to the presented technique, single-cell self-fluorescence spectra are recorded by means of confocal laser scanning microscopy (CLSM), and data processing is conducted via linear discriminant analysis (LDA) and artificial neural networks (ANN).

**Keywords:** microalgae, cyanobacteria, photosynthetic system, biological diversity, fluorescence, microscopic spectroscopy, artificial neural networks
