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Record W4221130737 · doi:10.3390/molecules27061976

Effect of Ozone-Treated or Untreated Saskatoon Fruits (Amelanchier alnifolia Nutt.) Applied as an Additive on the Quality and Antioxidant Activity of Fruit Beers

2022· article· en· W4221130737 on OpenAlexaboutno aff
Józef Gorzelany, Dorota Michałowska, S. Pluta, Ireneusz Kapusta, Justyna Belcar

Bibliographic record

VenueMolecules · 2022
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsnot available
Fundersnot available
KeywordsAntioxidantHorticultureBotanyOzoneBiologyTraditional medicineGeographyMedicineMeteorology

Abstract

fetched live from OpenAlex

Fruit of Saskatoon (Amelanchier alnifolia Nutt.) are a good source of bioactive compounds, such as polyphenols, including anthocyanins, as well as vitamins, macro- and microelements and fibre. By treating Saskatoon fruits with gaseous ozone, and adding the material as an enhancer to barley beers, it is possible to impact the contents of bioactive compounds in the produced fruit beers. Sensory tests showed that beers made from barley with addition of Saskatoon fruit of the ‘Smoky’ cultivar were characterised by the most balanced taste and aroma. Physicochemical analyses of fruit beers, produced with Saskatoon fruit pulp added on the seventh day of fermentation, showed that the beers enhanced with ozone-treated and untreated ‘Smoky’ Saskatoon fruits had the highest contents of alcohol, 5.51% v/v and 5.66% v/v, respectively, as well as total polyphenol contents of 395 mg GAE/L and 401 mg GAE/L, respectively, and higher antioxidant activity (assessed using DPPH•, FRAP and ABTS+• assays). It was demonstrated that the ozonation process led to a decrease in the contents of neochlorogenic acid, on average by 91.00%, and of caffeic acid by 20.62%, relative to the beers enhanced with ‘Smoky’ Saskatoon fruits not subjected to ozone treatment. The present study shows that Saskatoon fruits can be used in the production of beer, and the Canadian cultivar ‘Smoky’ is recommended for this purpose.

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)0.000
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 score0.065
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.301
Teacher spread0.283 · 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

Citations13
Published2022
Admission routes1
Has abstractyes

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