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Record W4405506483 · doi:10.1016/j.scenv.2024.100192

Thermo-mechanical decolourization process for shrimp chitin (Pandalus borealis)

2024· article· en· W4405506483 on OpenAlexaff
Julia Pohling, Kelly Hawboldt, Deepika Dave

Bibliographic record

VenueSustainable Chemistry for the Environment · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsChitinShrimpFisheryChitosanBiologyChemical engineeringEngineering

Abstract

fetched live from OpenAlex

Pandalus borealis is a thin-shelled shrimp species with medium pigmentation. The polysaccharide chitin, which makes up approximately 20 % of the shell, can be extracted and used in many different industries. The main extraction steps are deproteination and demineralization, followed by an assessment of the colour. White, off-white, or beige chitin is desired for most industrial applications. If required, residual pigmentation is typically removed in a decolourization step (DC) using oxidizing reagents or solvents. Disadvantages include safety and environmental concerns, unspecific oxidation reactions and high volatility of reagents. To date, a green process alternative is not documented. P. borealis chitin, deproteinated in alkali solution, does not require further DC. Enzymatic deproteination is nowadays preferred in the interest of sustainable processing, but it produces chitin with inferior colour quality. Based on the known thermal instability of the shrimp pigments and the porosity of chitin particles, the present study hypothesizes that the colour quality of enzymatically purified chitin can be enhanced by a washing process using high-shear and hot water. We develop a novel, chemical-free alternative for decolourization and assess its effectiveness compared to solvent and oxidizing reagents. Chitin properties are assessed by colorimetry, XRD, NMR, TGA, bulk density, and fat/water-binding capacities (FBC/WBC). Our findings suggest that the innovative thermo-mechanical DC process can produce a colour quality comparable to solvent DC without resulting in deacetylation, changes in crystallinity, or thermal stability. Thermo-mechanical DC enhanced WBC/FBC of chitin, which is an important property in hydrogel and drug delivery applications. • Acid-base methods produce chitin with lighter colour than green enzymatic methods. • Traditional bleaching methods enhance colour but damage chitin structure. • A green process alternative for chitin decolourization is presented. • Pigments are removed or degraded by high-shear, heat, and low-level chlorination. • New process enhanced water- and fat binding capacity of chitin.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.174
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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 teacher head, 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

Citations4
Published2024
Admission routes1
Has abstractyes

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