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Record W3111467957 · doi:10.1002/ffj.3644

A novel two‐step process to produce high‐quality basil flavoured chicken powder: Effect of ultrasonication followed by microwave vacuum and hot air drying

2020· article· en· W3111467957 on OpenAlexaff
Kejing Xu, Min Zhang, Arun S. Mujumdar, Yaping Liu

Bibliographic record

VenueFlavour and Fragrance Journal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsMcGill University
Fundersnot available
KeywordsFlavourChemistrySonicationEucalyptolFood scienceSpray dryingExtraction (chemistry)ChromatographyEssential oil

Abstract

fetched live from OpenAlex

Abstract The objective of this experimental investigation was to develop a novel two‐step process for production of high‐quality chicken powder infused with basil. The first step consists of ultrasonication of an aqueous chicken pieces mixed with chopped basil leaves to enhance extraction of basil flavour and also pretreat the chicken microstructure to intensify the drying kinetics in the second step. The drying was carried out using microwave vacuum followed by hot air. The results showed that the drying time of chicken was the shortest (110 minutes) after US 40 minutes. In terms of product quality, the best rehydration (136.18%), the lowest hygroscopicity (3.84%) and the best colour of basil chicken powder were obtained after US 40 minutes. In the aspect of flavour addition, the content of linalool, estragole and eucalyptol in the chicken powder treated by US 40 minutes was the highest, and these three compounds were the main flavour substances of basil. At the same time, the content of some substances with bad smell, such as benzaldehyde, was greatly reduced after adding basil flavour. The overall quality of chicken powder produced by this novel process was found to be superior to that of commercially available spray‐dried chicken powder.

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)0.001
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 score0.392
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.262
Teacher spread0.243 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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