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Record W2020216570 · doi:10.1094/cchem-08-13-0155-r

Physical and Molecular Characterization of Millet Starches

2014· article· en· W2020216570 on OpenAlexaffabout
George A. Annor, Massimo F. Marcone, Eric Bertoft, Koushik Seetharaman

Bibliographic record

VenueCereal Chemistry · 2014
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAmyloseChemistryStarchFoxtailFood scienceEnthalpyBotany

Abstract

fetched live from OpenAlex

ABSTRACT This study investigated the physical and molecular starch characteristics of four Canadian‐grown millet species: pearl, foxtail, proso, and finger millet. The millet starch granules ranged from about 2.5 to 24 μm in size and were mainly polygonal with a few spherical ones. Their amylose contents ranged from 28.6 to 33.9%, with finger and pearl millets having much more of long amylose chains than short amylose chains compared with foxtail and proso millets. Starches also differed in the molecular structure of their branched amylose, with finger and pearl millets having longer glucan chains between branch points. The enthalpy of gelatinization of starch granules ranged from 11.8 to 13.2 J/g, and the enthalpy of melting of the retrograded starches ranged from 2.2 to 5.9 J/g. The onset temperature of gelatinization (To) of the starches ranged from 62.8 to 70.6°C. Addition of iodine vapor to the granular starches showed significant (P < 0.05) differences in the ratio of the absorbance to scattering coefficient (K/S) values, indicating differences in the rigidity of the glucan chains present in the granules. Starches with short amylose chains exhibited higher K/S values. Iodine vapor addition resulted in altered X‐ray diffractogram peak intensities. The study suggested differences in the structure and granular architecture of the millet starches.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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

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 head0.008
GPT teacher head0.218
Teacher spread0.209 · 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 designObservational
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

Citations112
Published2014
Admission routes2
Has abstractyes

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