An Investigation into the Sensory Properties of Luffa (Luffa cylindrica (L.)) Fruit Powder
Bibliographic record
Abstract
Luffa fruit is an underutilized and novel ingredient in North America. To increase the shelf life of luffa fruit, this study evaluated the creation of luffa fruit powder using three different drying temperatures (40 °C, 50 °C, and 60 °C). The objective of this study was to evaluate the sensory properties and acceptability of luffa fruit powder with unfamiliar consumers (those who do not regularly eat luffa fruit). Participants (n = 88) evaluated the luffa fruit powders mixed into couscous, as well as a control (couscous without luffa fruit powder) using check-all-that-apply and hedonic scales. Furthermore, the participants were asked how they felt about luffa fruit powder after evaluating the samples (comment question). The hedonic scores were not significantly affected by the addition of the luffa seed powders dried at different temperatures. However, the luffa seed powder was associated with a mild flavour, as well as being described as earthy and vegetal. The participants did indicate that the luffa seed powder added moistness to the couscous. As the drying temperature increased so did the intensity of the flavour. Furthermore, participants indicated they would be interested in luffa seed powder if it has nutritional benefits. Overall, this study investigated the sensory properties of a novel ingredient, luffa seed powder, and future studies should continue to explore its sensory properties and chemical components.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".