Abstract

In this article we describe the technical aspects of digital in-line holographic microscopy to track multiple macrofouling Ulva linza zoospores simultaneously during their exploration of surfaces. Using an effective method of artefact suppression at the edges of holograms in combination with projection of volume reconstructions, a fast algorithm was developed which allows a reliable determination of a large number of subsequent spore positions. Thus, statistical analysis of swimming behaviour in the vicinity of surfaces becomes possible.

Using glass surfaces as example, velocity and diving direction distributions are calculated and the swimming behaviour is statistically analysed. Diving direction analysis provides a straightforward way to determine segments within traces with surface contact. The presented method of data analysis allows high throughput analysis of holographic microscopy data and sets the basis for different applications including biofouling.

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