Isotopic Analysis as a Potential Tool to Verify Feed Protein Sources for Aquacultured Species

This study identified δ15N stable isotope ratios as a robust tracer for fishmeal inclusion in aquaculture feeds. δ15N and δ13C values from fish muscle samples derived from feeding trials with seven species (n = 3–5 fish per diet group) were evaluated (+/−0.1‰ for both δ15N and δ13C; ~1% relative to % N and % C) to verify whether the presence or absence of fishmeal (FM) in feeds could be detected. C and N isotopic data were also analyzed for feed in two of the trials. δ13C signatures did not differ consistently across diet groups for each species examined, with mean δ13C values for all species investigated being −20.2‰ ± 1.3. In contrast, a strong δ15N distinction was discerned between FM- and non-FM-fed fish for both muscle and feed samples, with FM-fed groups presenting higher values (p < 0.01) than non-FM-fed groups (range 0.8 to 9.5‰). Dietary ingredients other than FM (e.g., fish oil and algal oil) did not impact the δ15N isotopic fingerprint, although the addition of poultry byproduct meal to plant-based salmon diets caused an average 0.3‰ difference in δ15N values. The findings are not absolute as CN isotopes can be used to detect large but not small differences in feed components. Additional research on threshold levels, ingredient sourcing, and species differences is warranted to refine the method to enhance industry transparency and seafood consumer confidence.

Authors

Institutions

Publication Details

Journal
Fishes
Published
2026-06-17
DOI
https://doi.org/10.3390/fishes11060363
Primary Topic
Isotope Analysis in Ecology
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Isotopic Analysis as a Potential Tool to Verify Feed Protein Sources for Aquacultured Species

M Tlusty, Frederic T. Barrows, Kelly Brandeau Campbell
Fishes
Isotope Analysis in Ecology
article

Isotopic Analysis as a Potential Tool to Verify Feed Protein Sources for Aquacultured Species

M Tlusty, Frederic T. Barrows, Kelly Brandeau Campbell
article en

Abstract

This study identified δ15N stable isotope ratios as a robust tracer for fishmeal inclusion in aquaculture feeds. δ15N and δ13C values from fish muscle samples derived from feeding trials with seven species (n = 3–5 fish per diet group) were evaluated (+/−0.1‰ for both δ15N and δ13C; ~1% relative to % N and % C) to verify whether the presence or absence of fishmeal (FM) in feeds could be detected. C and N isotopic data were also analyzed for feed in two of the trials. δ13C signatures did not differ consistently across diet groups for each species examined, with mean δ13C values for all species investigated being −20.2‰ ± 1.3. In contrast, a strong δ15N distinction was discerned between FM- and non-FM-fed fish for both muscle and feed samples, with FM-fed groups presenting higher values (p < 0.01) than non-FM-fed groups (range 0.8 to 9.5‰). Dietary ingredients other than FM (e.g., fish oil and algal oil) did not impact the δ15N isotopic fingerprint, although the addition of poultry byproduct meal to plant-based salmon diets caused an average 0.3‰ difference in δ15N values. The findings are not absolute as CN isotopes can be used to detect large but not small differences in feed components. Additional research on threshold levels, ingredient sourcing, and species differences is warranted to refine the method to enhance industry transparency and seafood consumer confidence.

FishesVol. 11(6)
University of Massachusetts Boston (US), Aquatic Systems (United States) (US), Palo Alto Institute (US)
Anthropocene Institute
Openalex Percentile: Top 7%
Isotope Analysis in Ecology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.