Antioxidant properties of sacha inchi (Plukenetia volubilis) shell extracts as affected by solvents used for prior decolorization
Bibliographic record
Abstract
Sacha inchi (Plukenetia volubilis) shell is a potential source of phenolics with an-tioxidative activity and its extract can be used to prevent lipid oxidation in some food matrices. However, the sacha inchi extract has been fully exploited due to the dark brown colour properties associated with pigments. Thus, de-colourization of sacha inchi shells before extraction using solvents could be a means to bring about the extract with a lighter colour, which could be applied in foods without constraints. The effects of different solvents used for decolour-ization in sacha inchi (Plukenetia volubilis) shell powder on antioxidant proper-ties were investigated. The solvents used were methanol, acetone, chloroform and propanol. The ethanolic extracts' total phenolic content (TPC) and total flavonoid content (TFC) decreased when solvents were employed for prior de-colourization. Among all solvents, the ethanolic extracts from sacha inchi shell powder decolourized using chloroform (CHE) showed the highest TPC (9.94 mg GAE/g dry extract) and TFC (7.20 mg CE/g dry extract). Also, extracts from chloroform decolourized shell powder had the highest antioxidant activities (2,410.01, 111.60 and 4.58 µmol TE/g dry extract for 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scaveng-ing activities, ferric reducing antioxidant power (FRAP), respectively, and 0.52 mmol EDTA /g dry extract for metal chelating assay) compared to other ex-tracts. Therefore, chloroform was the appropriate solvent for decolourization, and the resulting extract had higher antioxidant properties than others.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".