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Determination of Sugar Content in Commercial Fruit Juices by Refractometric, Volumetric and Chromatographic Methods

2016· article· en· W2531542982 on OpenAlexvenueno aff
Francesca Buiarelli, Patrizia Di Filippo, Donatella Pomata, Carmela Riccardi, Daniela Rago

Bibliographic record

VenueJournal of Nutritional Therapeutics · 2016
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsnot available
Fundersnot available
KeywordsSugarChromatographyChemistryFruit juiceFood science

Abstract

fetched live from OpenAlex

In this paper several approaches are discussed for the direct analysis of the main sugars in different fruit juices. Refractometry, thin layer chromatography, volumetric analysis and high performance liquid chromatography with refractive index detector were tested and the results compared, discussing the advantages and disadvantages of each of them. Whereas the first method gives generically indications on the whole content of sugar and it doesn’t require any prior manipulation of the sample, thin layer chromatography is useful only for qualitative purpose, on the other hand the third method, after removal of interferences, makes possible the determination of the reducing and not reducing sugar, and the last one allows the qualitative and quantitative determination of the saccharides singularly. It’s very important to have not only knowledge about the chemical analysis of carbohydrates and their physicochemical properties, but especially how the methods can be used in product development for benefit of the public.

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 score0.344
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.063
GPT teacher head0.355
Teacher spread0.292 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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