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Record W2079895548 · doi:10.5539/jfr.v1n3p121

Microwave-assisted Extraction of Ochratoxin A from Roasted Coffee Beans: An Alternative Analytical Approach

2012· article· en· W2079895548 on OpenAlexvenueno aff
Giulia Graziani, Antonello Santini, Rosalia Ferracane, Alberto Ritieni

Bibliographic record

VenueJournal of Food Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsnot available
Fundersnot available
KeywordsOchratoxin AExtraction (chemistry)ChemistryChromatographyHigh-performance liquid chromatographyRoastingMycotoxinCoffee groundsFood science

Abstract

fetched live from OpenAlex

<p>Microwave-assisted extraction (MAE) followed by high performance liquid chromatography (HPLC) with a fluorescent detector (DAD) was used and developed for the quantitative analysis of the mycotoxin ochratoxin A (OTA) in commercial roasted coffee beans. This alternative approach has been compared with the conventional extraction that uses hydrogen carbonate aqueous solution followed by OchraTest immunoaffinity analysis. The effect of two experimental tunable MAE parameters (temperature and pressure) on the extraction efficiency of OTA have been investigated using coffee samples forti?ed at different contamination levels. The optimum extraction conditions were obtained using a temperature of 50 °C and a 500 W microwave power. OTA quantity extracted using MAE was similar to that obtained by conventional extraction from samples fortified at 5, 10, and 100 ng g<sup>-1</sup> levels. At a 20 ng g<sup>-1</sup> level, MAE was more effective than the conventional method. The MAE setting parameters have been optimized showing both extraction time and solvent consumption have been considerably reduced, retaining high OTA recovery values.</p>

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)0.002
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 score0.373
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.157
GPT teacher head0.364
Teacher spread0.207 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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