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Record W3049744549 · doi:10.5539/jas.v12n9p149

Effects of Extrusion Conditions on Physicochemical Properties of Finger Millet (Gramineae Setaria)

2020· article· en· W3049744549 on OpenAlexvenueno aff
Peng Liu, Jianjun Cheng, Ming Li, Jing Li, Hongwei Zhu, Shirang Wang, Guoping Yu

Bibliographic record

VenueJournal of Agricultural Science · 2020
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
FundersNational Key Research and Development Program of China
KeywordsExtrusionWater contentAbsorption of waterStarchFinger milletExpansion ratioMaterials scienceAgronomyBulk densityMoistureEleusineFood scienceComposite materialChemistrySoil waterBiologySoil scienceEnvironmental science

Abstract

fetched live from OpenAlex

In this study, the effects of different extrusion parameters (extrusion temperature: 100, 130, and 160 °C; moisture content: 22%, 26%, and 30%; screw speed: 180 rpm, 270 rpm, and 360 rpm) on physicochemical properties of finger millet were reviewed. High extrusion temperature produced extrudates with high radial expansion index (REI) and starch digestibility and low bulk density (BD). High moisture content and low screw speed increased BD and total starch content (TSC) while decreasing REI and water solubility index (WSI). WSI and starch digestibility first increased and then decreased with increase in extrusion temperature and moisture content, which reached a maximum at 130 °C nd 26%, respectively. However, water absorption index (WAI) was affected by the interactions among various conditions. The extrudates were darker and yellower than native millet. Based on these extrusion conditions, various millet and millet-based products can be produced.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.019
GPT teacher head0.234
Teacher spread0.215 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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