Abstract
Fish scale analysis is widely used in fisheries science to assess age, growth, and life-history patterns. However, many existing workflows still rely heavily on manual interpretation and observer-dependent measurements, limiting standardization, reproducibility, and scalability across monitoring programs and experimental studies.
Here, we present a standardized digital workflow for automated fish scale analysis integrating digital sampling, image acquisition, metadata linkage, and quantitative extraction of structural scale features. The workflow combines a custom-built digital measuring system for field and laboratory data collection with automated image-based analysis of scale morphology and circuli patterns.
To evaluate whether scale structures contain biologically meaningful information related to growth conditions, the workflow was applied to an experimental feeding study using tilapia (Oreochromis sp.) maintained in experimental recirculating aquaculture systems. During a 12-week grow-out period, two different feeding regimes were applied (7 feeding days per week vs. 5 feeding days per week). In addition, the applicability of the workflow was demonstrated using historical scale material from wild coregonid populations collected over multiple decades.
Fish subjected to continuous feeding developed significantly higher circuli numbers, larger scale dimensions, and altered circuli spacing compared to intermittently fed individuals. Structural differences between feeding groups became increasingly pronounced over the course of the experiment. Application of the workflow to historical coregonid material enabled retrospective reconstruction of age-related growth patterns across multiple decades.
The results demonstrate that fish scales contain quantifiable structural information reflecting growth and feeding history and highlight the potential of standardized digital workflows for scalable fisheries monitoring, aquaculture research, and retrospective ecological analyses. The presented workflow further illustrates the potential of fish scale analysis as a reproducible and scalable tool for documenting fish growth and management history under both experimental and natural conditions.