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Record W4411965423 · doi:10.1016/j.afres.2025.101128

Gelatin from red tilapia (Oreochromis spp.) scales: Optimization of its extraction and detailed characterization of its chemical and viscoelastic properties

2025· article· en· W4411965423 on OpenAlexfundno aff
Jairo Andrés Camaño Echavarría, Amine Nekkaa, Philippe Arnoux, Christelle Mathé, Céline Cakir‐Kiefer, Loïc Stefan, Cédric Paris, Katalin Selmeczi, José E. Zapata, Laetitia Canabady‐Rochelle

Bibliographic record

VenueApplied Food Research · 2025
Typearticle
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsnot available
FundersAgence Nationale de la RechercheProvidence Health CareMinistère de l'Enseignement Supérieur et de la RechercheUniversité de Lorraine
KeywordsTilapiaViscoelasticityGelatinExtraction (chemistry)Characterization (materials science)OreochromisBiological systemBiologyChemistryFish <Actinopterygii>Materials scienceFisheryChromatographyNanotechnologyComposite materialBiochemistry

Abstract

fetched live from OpenAlex

Gelatin is widely used in food and pharmaceutical industries for its functional and bioactive properties. When extracted from fish by-products, the environmental impacts of these former waste are reduced. This study aimed to optimize the gelatin extraction from red tilapia scales using a fractional factorial design and evaluate its physicochemical and viscoelastic properties. The effects of solvent-to-solid ratio (2-10 mL/g), extraction time (1-3 h), temperature (65-85 °C) and ultrasound (0-60 min) were investigated on the crude protein content (CPC), the free amino groups (FAG) and the protein extraction yield (PEY). The CPC extracted (95.4-99.2 %) was in agreement with protein isolates (>85 %) and the extraction time and temperature had a significant positive effect on FAG and PEY. Extraction conditions after optimization were: 10 mL/g solvent-to-solid ratio, 3 h, 85°C, and without ultrasounds. Gelatin obtained under optimal condition improved highly the protein extraction and exhibited the best molecular weight distribution profile (α1/α2 chain ratios: 1.7) to offer suitable viscoelastic properties in term of gelling (18 °C) and melting capacities (25.8 °C). This finding highlights the important potential of such natural protein source as a tailored gel for food or cosmetic formulations. Abbreviations: AA, Amino acid; Adeq precision, Adequate precision; AAA, Aromatic amino acids; ANOVA, Analysis of variance; BCAA, Branched chain amino acids; CD, Circular dichroism spectroscopy; CPC, Crude protein content; EAA, Essential amino acids; FAG, Free amino group; FFD, Fractional factorial design; FTIR, Fourier-transform infrared spectroscopy; G′, Storage modulus, G′′, Loss modulus; HAA, Hydrophobic amino acids; LMWA, Low molecular weight aggregates; M, Protein marker, NCAA, Negatively charged amino acids; PCAA, Positively charged amino acids; PEY, Protein extraction yield; OPA, o -phthalaldehyde; SDS-PAGE, Sodium dodecyl sulfate polyacrylamide gel electrophoresis; TSF, tilapia scale flour; TSG, tilapia scale gelatin.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.291
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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