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Record W1971522552 · doi:10.1021/jf703739k

Alginate and Chitosan Functionalization for Micronutrient Encapsulation

2008· article· en· W1971522552 on OpenAlexaff
Jaejoon Han, Anne-Sophie Guenier, Stéphane Salmieri, Monique Lacroix

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMicroencapsulation and Drying Processes
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsChitosanPolymerSurface modificationFourier transform infrared spectroscopyChemistryChemical engineeringPolymer chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A new method for encapsulation of micronutrients was successfully developed. The encapsulation matrix consisted of two polymers (alginate and chitosan), which were functionalized by acylation with palmitoyl chloride. The structural modifications of polymers were confirmed by Fourier transform infrared (FTIR) spectroscopy. Beads were formed by ionic gelation, and their mechanical and physical characteristics (puncture strength and deformation, viscoelasticity, water vapor permeability, and rate of gel swelling) were evaluated using beads or films made of bead-forming solutions. Functionalization increased elasticity and water impermeability of polymer films. Stability of selected encapsulated micronutrients (ferrous fumarate, ascorbic acid, and beta-carotene) was also evaluated under two levels of temperature (23 and 45 degrees C) and relative humidity (56 and 100%) for 6 months. Encapsulation strongly increased the stability of micronutrients. No difference was observed in the encapsulated micronutrients' stability between nonfunctionalized and functionalized beads. Finally, a release study in gastrointestinal media was conducted. Results showed that beads were not susceptible to enzymatic and acidic attacks during stomach transit. This research demonstrates the potential of a new encapsulation method to protect bioactive molecules from temperature, moisture, and acidic conditions.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.188
Teacher spread0.173 · 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

Citations100
Published2008
Admission routes1
Has abstractyes

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