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Record W2096615175 · doi:10.1016/j.lwt.2010.06.016

Microstructure and physico-chemical bases of textural quality of yam products

2010· article· en· W2096615175 on OpenAlexfundno aff
Noël Akissoé, Christian Mestres, Stephan Handschin, Olivier Gibert, Joseph D. Hounhouigan, Mathurin Coffi Nago

Bibliographic record

VenueLWT · 2010
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
FundersAgence Universitaire de la Francophonie
KeywordsMicrostructureQuality (philosophy)Texture (cosmology)Materials scienceBusinessChemistryMetallurgyComputer scienceArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

The texture of pounded yam is the main attribute of this traditional dish, one of the preferred ways of consuming yam in West Africa. We integrated functional properties and cell microstructure to describe or predict the textural quality of pounded yam. The firmness and adhesiveness of pounded yam prepared from six cultivars were measured. In parallel, the thermo-mechanical properties (DMA, DSC) and starch behaviour were also determined while the structure of raw, cooked and pounded yam was observed using Scanning Electron Microscopy, Light Microscopy and Confocal Laser Scanning Microscopy. No significant correlation was found linking DMA, DSC measurements with the textural quality of pounded yam (adhesiveness, firmness). Conversely, multiple regressions showed that 75% of the variation in firmness could be explained by the dry matter, soluble starch and amylose content of the pounded yam. In addition, CLSM revealed a thicker cell wall in Florido, a cultivar known for its bad pounding ability. We hypothesize that pectin, the major component of cell wall middle lamella, plays a role in the textural quality of pounded yam.

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 score0.010
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.278
Teacher spread0.258 · 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

Citations25
Published2010
Admission routes1
Has abstractyes

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