# Large-Scale Permanent Slide Imaging and Image Analysis for Diatom Morphometrics
## 4 Discussion
In SHERPA, one can either use stricter quality settings to speed up or completely skip manual processing and to reduce the number of non-diatom objects detected at the price of perhaps missing more valves of interest; or use more permissive quality criteria potentially allowing a higher yield at the price of more false positives (requiring more processing time to remove these manually). If it is critical not to miss any valves lying in the slide area of interest, there is a possibility for manual interaction with the virtual slide once object positions and outlines detected by SHERPA have been imported into it. At this stage, the virtual slide can be scanned visually and diatom objects missed by SHERPA can be marked manually in addition so that they are also imaged at high resolution in the next step. Finally, to improve segmentation results in the case of individual problematic valves (e.g., ones overlapping with other objects), a manual correction of outlines is possible at the stage of SHERPA analysis of high-resolution images. The morphometric features, as well as quality scores and ranking of the object, are updated immediately after such manual corrections, and the fact that a manual correction was applied to the object is recorded in the results table exported by SHERPA for further processing. Again, a decision as to whether a manual processing at this step is sensible and how much time to invest in it can be decided case by case based on the purpose of the investigation. **Practical example:** To give a simple demonstration of the workflow introduced, we presented a basic morphometric characterization of _Fragiliaropsis kerguelensis_, one of the most common diatom species in Southern Ocean sediments from the late Pleistocene on to present days [24]. The fact that we can substantially extend on the hitherto reported size range of the species (see Figure 9) seems to simply reflect a substantial increase in sample size. Although qualitatively, we see many of the longest valves in samples from MIS5, a Kolmogorov-Smirnov test did not support a significant difference in apical length distributions of this sample from more recent sediment layers. Whereas taxonomic descriptions circulating in the literature might be based on measuring dozens, perhaps up to a few hundred valves [16; 18], using the partially automated workflow presented, we could measure about 12,000 valves. Ca. 0.54% (in total 64) of the _F. kerguelensis_ valves analysed had an apical axis length longer than the maximum of 83 \(\upmu\)m reported before by [16; 17; 18]. The longest valve with 118.9 \(\upmu\)m apical axis length (see Table 1 and Figure 6) is ca. 45% longer than the maximum reported before. The shortest valve with 11.1 \(\upmu\)m apical axis length is smaller than the minimum sizes reported by [18] and [17], but larger than the 10 \(\upmu\)m reported by [16]. The transapical axis length ranges from 3.7 to 14.2 \(\upmu\)m, compared to 4.5 to 12 \(\upmu\)m reported by [17], where 3.66% (in total 434) valves were larger, and 0.08% (in total nine) valves were smaller with regard to this axis than reported before. Whilst the distribution of apical valve axis lengths is right-skewed (see Figure 7 top), as can be expected based on size reduction accompanying vegetative divisions, the symmetric distribution of transapical valve axis lengths (see Figure 7 bottom) shows that the size reduction somehow is relaxed along this axis for _F. kerguelensis_. Whereas it could be suspected, based on this symmetric distribution, that transapical valve width might remain constant with size decrease, this is not the case. The observed pattern is rather a roughly linear relationship of transapical width with apical length up to length of around 50 \(\upmu\)m, and a constant or slightly decreasing transapical width with increasing length above that. This relation between apical and transapical valve length can be described by a third-order polynomial that explains ca. 50% of the observed variance (see Figure A3).