Reinventing artisanal curry leaf paste: biochemical and sensory analysis of five distinct Sri Lankan cultivars.
Bibliographic record
Abstract
Five Distinct Sri Lankan Cultivars Spices and condiments bring unique flavors to food, with curry leaves being prominent condiment in Asian cuisines.In Sri Lanka, several Rutaceae family plants are referred to as "curry plants."This study examined the chemical, proximate, phytochemical, and sensory properties of selected curry plant cultivars.Buffalo curry plant (Clausena indica Oliv.) and Purple curry plant (putative variant of Murraya koenigii), demonstrated superior nutritional qualities, exhibiting significantly higher levels of polyphenol and antioxidant than Common curry plant [Murraya koenigii (L.) Spreng.].Leaf oil analysis identified shared compounds, including α-humulene, α-pinene, αselinene, β-elemene, β-caryophyllene, β-pinene, caryophyllene oxide, and 2, 3, 4, 6tetramethoxy-styrene.Exclusive sensory evaluation of C. indica and Purple curry leaves uncovered a preference for C. indica, likely due to its higher eucalyptol content (29.6%) contributing to a more appealing aroma compared to Purple curry leaves' predominant β-caryophyllene content (32.4%).These findings guide future food product development and potential nutraceutical applications.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".