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This is an open access article under the terms of the Creat ive Commo ns Attri bution-NonCo mmercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Measuring spore size is a standard method for the description of fungal taxa, but in manual microscopic analyses the number of spores that can be measured and information on their morphological traits are typically limited. To overcome this weakness we present a method to analyze the size and shape of large numbers of spherical bodies, such as spores or pollen, by using inexpensive equipment. A spore suspension mounted on a slide is treated with a low-cost, high-vibration device to distribute spores uniformly in a single layer without overlap. Subsequently, 10,000 to 50,000 objects per slide are measured by automated image analysis. The workflow involves (1) slide preparation, (2) automated image acquisition by light microscopy, (3) filtering to separate high-density clusters, (4) image segmentation by applying a machine learning software, Waikato Environment for Knowledge Analysis (WEKA), and (5) statistical evaluation of the results. The technique produced consistent results and compared favorably with manual measurements in terms of precision. Moreover, measuring spore size distribution yields information not obtained by manual microscopic analyses, as shown for the myxomycete Physarum albescens. The exact size distribution of spores revealed irregularities in spore formation resulting from the influence of environmental conditions on spore maturation. A comparison of the spore size distribution within and between sporocarp colonies showed large environmental and likely genetic variation. In addition, the comparison identified specimens with spores roughly twice the normal size. The successful implementation of the presented method for analyzing myxomycete spores also suggests potential for other applications.

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