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Record W4411432927 · doi:10.1002/star.70061

Phosphorylated Starch‐Enhanced Controlled‐Release Formulations for Agricultural Applications

2025· article· en· W4411432927 on OpenAlexaff
Hind Wattati, Sana Azeroual, Hasna Befenzi, Rachid Jalal, Moha Taourirte, François Brouillette, Ahmed Belfkira

Bibliographic record

VenueStarch - Stärke · 2025
Typearticle
Languageen
FieldEngineering
TopicPolymer-Based Agricultural Enhancements
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPolyvinyl alcoholSalicylic acidStarchChemistryActive ingredientCoatingMembranePolyvinyl acetateEthanolControlled releaseChemical engineeringFood sciencePulp and paper industryMaterials scienceOrganic chemistryPolymerBiochemistryNanotechnologyPharmacologyBiology

Abstract

fetched live from OpenAlex

ABSTRACT This study aims to optimize slow‐release formulations for agricultural use by employing biodegradable materials. The tablet contains salicylic acid (100 mg) as the active ingredient, three excipients: phosphorylated starch (PS), polyvinyl alcohol (PVA), and polyvinyl acetate as a membrane to regulate the release. The findings demonstrate that PS significantly enhances water retention, with water uptake increasing from 253 to 384 mg as PS content rises from 0 to 50 mg per tablet, representing a 52% increase. Experiments conducted at different pH levels (1.64 and 7.1) and with varying numbers of coating layers (1–3) revealed a complex two‐step release mechanism that could not be fully described by traditional kinetic models (Higuchi and Korsmeyer–Peppas). This formulation shows strong potential for agricultural applications, such as slow‐release fertilizers and plant stimulants, offering prolonged activity, reduced environmental impact, and improved plant resistance to stress and pathogens.

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 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 score0.257
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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