Evidence map›Paper›PMID 40077523›Full record

ArticleFoods (Basel, Switzerland)2025

Forging Prawn and Salmon Flavours with Non-Animal-Based Ingredients.

Jiaqiang Luo, Damian Frank, Jayashree Arcot

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jiaqiang LuoFood and Health Group, School of Chemical Engineering, Faculty of Engineering, UNSW Sydney, Kensington, NSW 2052, Australia.
Damian FrankAll G, Waterloo, NSW 2017, Australia.
Jayashree ArcotFood and Health Group, School of Chemical Engineering, Faculty of Engineering, UNSW Sydney, Kensington, NSW 2052, Australia.ORCID 0000-0002-4254-7288

Funding

Good Food Institute 22-PB-AU-FCC-1-361
6 · The paper itself

Abstract

The development of plant-based seafood alternatives with authentic flavour profiles remains a significant challenge, limiting their appeal to seafood consumers. This study hypothesised that incorporation of flavour precursors including free amino acids, betaine, and long chain omega-3 fatty acids would enhance the flavour resemblance of plant-based prawn and salmon prototypes to their authentic seafood counterparts. Prototypes were analysed using headspace solid-phase microextraction gas chromatography-mass spectrometry and evaluated by a semi-trained sensory panel. Volatile analysis revealed 64 compounds across prototypes, with significant variations attributed to precursor combinations and thermal treatments. Frying enhanced volatile profiles, particularly in plant-based prawn prototypes fortified with all three flavour precursors, producing key prawn odourants, including pyrazines and trimethylamine. Notably, betaine pyrolysis under moderate cooking conditions was demonstrated as a potential pathway for trimethylamine formation, contributing to fish-like odours. Sensory evaluation showed that the final plant-based prawn prototype exhibited strong cooked crustacean and grilled notes, aligning with the observed volatile profile. While the salmon prototype displayed key salmon odourants, its cooked salmon odour was less pronounced, suggesting a need for a more robust flavouring strategy. This study highlights the potential of targeted flavour precursor formulations to improve the flavour quality of plant-based seafood alternatives, paving the way for their wider acceptance.

Indexed as

alternative proteinflavourformulationodourvolatile

Identifiers

PMID40077523
PMCPMC11898523

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.