Machine Learning Quantifies Fine-Scale Hairiness in Shore Flies (Diptera: Ephydridae).

ABSTRACT: Morphological analysis of fine structures on small insects is often labor intensive, scale-limited, and biased by sampling or organismal life history. We used a pixel classification machine-learning workflow with the open source programs Ilastik and Fiji to identify and quantify microtrichia in semiaquatic shore flies (Ephydridae). This methodology semi-automates quantification of hairs by counting objects or groups of class-assigned pixels and determining their percent coverage at a given magnification using scanning electron micrographs. Our results are consistent with manual counts, with Paracoenia species that tolerate hot springs having more hairs than less aquatic Parydra. However, Paracoenia hairs tend to be shorter, and the percent coverage of microtrichia per unit surface area did

SUBMITTER: Abraham SM 

PROVIDER: S-EPMC12519760 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature