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Record W4415629620 · doi:10.1051/e3sconf/202565503003

Development of Bioactive Agar-Based Bioplastics Enriched with Cocoa Pod Husk Extract: Structural, Barrie, and Antioxidant Properties

2025· article· fr· W4415629620 on OpenAlexaboutno aff
Aulia Firda Salsabila, Yuni Kusumastuti, Maulana Gilar Nugraha

Bibliographic record

VenueE3S Web of Conferences · 2025
Typearticle
Languagefr
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsnot available
FundersUniversitas Gadjah Mada
KeywordsBioplasticHuskAntioxidantDPPHGlycerolActive packagingFood packagingPoint of deliveryHydrogen peroxide

Abstract

fetched live from OpenAlex

The growing demand for eco-friendly food packaging has driven the development of biodegradable active films. This study developed novel agar-based films incorporating phenolic-rich cocoa pod husk (CPH) extract (10 - 25% w/w) and glycerol (30–50% w/w) using green deep eutectic solvent (DES) extraction. The optimal formulation (25% w/w CPH, 40% glycerol) demonstrated exceptional functionality. The antioxidant activity of bioplastics added with phenolic compounds of cocoa pod husk extract at 10, 15, and 25% w/w, analysed by the DPPH method, obtained results of 45.72 ± 0.27, 47.45 ± 0.06, and 56.85 ± 0.06, respectively, and the water vapour permeability was 907.26 g/m 2 day. The hydrogen bonding interaction among the components of the blend films led to enhanced structural, barrier, thermal stability, miscibility, antioxidant properties, and smooth surface morphology of the blend films. Characterization showed hydrogen bonds such as -OH between agar, glycerol, and phenolic CPH, C=O ester groups (FTIR), and homogeneous microstructure (SEM). DES extraction preserved bioactivity better than conventional methods. This study demonstrates the potential of agar/CPH films as sustainable active packaging for perishable foods, combining antioxidant/antimicrobial properties with mechanical strength, while addressing both food preservation and environmental sustainability challenges through circular economy principles.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.250
Teacher spread0.230 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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