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Record W2927253569 · doi:10.5539/jfr.v8n3p35

A Comparison of the Polyphenolic and Free Radical Scavenging Activity of Cold Brew versus Hot Brew Black Tea (Camellia Sinensis, Theaceae)

2019· article· en· W2927253569 on OpenAlexvenueno aff
Chathuranga Manhari Magammana, Cheryl Rock, Long Wang, Virginia Gray

Bibliographic record

VenueJournal of Food Research · 2019
Typearticle
Languageen
FieldMedicine
TopicTea Polyphenols and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryDPPHGallic acidFood sciencePolyphenolCatechinFlavonoidBlack teaBrewingTheaflavinAntioxidantOrganic chemistryFermentation

Abstract

fetched live from OpenAlex

Recently, a new trend called cold brewing gained popularity in the tea and coffee beverage industry. Cold brew and hot brew black tea may have different sensory qualities and antioxidant levels because of their polyphenolic properties and brewing processes. The objectives of this study were to determine antioxidant properties and polyphenolic content of commercial brands of cold brew and hot brew black tea. The total phenolic content of the cold brew tea was determined to be 0.19 mg/mL gallic acid equivalents/100 g and hot brew tea was 0.43 mg/mL gallic acid equivalents/100 g when assayed by Folin-Ciocalteu’s reagent method. The total flavonoid content of the cold brew tea was 0.40 mg/mL catechin equivalents/100 g and hot brew was 1.01 mg/mL catechin equivalents/100 g. Moreover, antioxidant capacity of cold brew and hot brew black tea was analyzed where their ability to scavenge DPPH radicals was 86.3% and 88.1% respectively. There was a significant difference in total phenolic content between hot brew and cold brew (p = 0.004). Similarly, there was a significant difference in total flavonoid between cold brew and hot brew (p = 0.004). Additionally, there was a significant difference in DPPH scavenging activity between cold brew and hot brew (p = 0.016). Overall, it can be concluded that although cold brew tea contained a lower amount of phenolics and flavonoids as compared to hot brew tea, they both were able to scavenge DPPH radicals in nearly same capacity.

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)0.001
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 score0.207
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.087
GPT teacher head0.393
Teacher spread0.306 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

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