MétaCan
Menu
Back to cohort
Record W4392291387 · doi:10.18280/ijdne.190105

Sensory Analysis of Butterfly Pea (Clitoria ternatea L.) Flower Tea Drink Using Central Composite Design

2024· article· en· W4392291387 on OpenAlexvenueno aff
Juanda Juanda, Sri Hartuti

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMedicinal Plant Research
Canadian institutionsnot available
Fundersnot available
KeywordsClitoria ternateaButterflyCentral composite designComposite numberHorticultureBiologyMathematicsStatisticsEcologyMedicineResponse surface methodology

Abstract

fetched live from OpenAlex

Butterfly pea (Clitoria ternatea L.) flower tea is a functional drink that is helpful in improving nutrition and health.The level of preference for the tea drink needs to be studied; thus, the accurate product formula can be obtained in its postharvest handling and processing.This research aimed to optimize the microwave-dried pea flower tea drink using the central composite design (CCD) method.The treatment factors studied were microwave power and drying time, with the treatment response as a sensory test of butterfly pea flower tea, including colour, aroma, taste, and aftertaste.The results of CCD analysis show that microwave power and drying time significantly affect the colour, aroma, and taste of butterfly pea tea but have no significant effect on the aftertaste.The optimum sensory formula was obtained at microwave power (X₁) of 180 watts and drying time (X₂) of 17 minutes, with a prediction of colour of 5.8 ≈ 6 (likes), aroma of 5.1 ≈ 5 (somewhat like), taste of 5 .03≈ 5 (somewhat like) and aftertaste of 4.05 ≈ 4 (neutral).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.292
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Design & Nature and EcodynamicsSame topicMedicinal Plant ResearchFrench-language works237,207