Phytochemicals, chlorophyll pigments, antioxidant activity, relative expansion ratio, and microstructure of dried okra pods: swell-drying by instant controlled pressure drop versus conventional shade drying
Bibliographic record
Abstract
This study is aimed at comparing swell drying versus conventional shade drying and optimizing the texturing by instant controlled pressure drop (DIC) of green okra pods. Differences in quality attributes such as content of flavonoids, carotenoids, and chlorophyll pigments, functional characteristics such as the antioxidant activity (AOA), microstructure and relative expansion ratio of dried okra pods were considered. The DIC processing parameters were the saturated steam pressure (0.2-0.6 MPa) and duration (40-60 s). A 2-parameter, 5-level central composite rotatable design was selected for establishing the experimental trials. They represent 8 factorial and star trials, and five repetitions of central/middle point of the square edges. Significant variations in total phenolic and flavonoid contents, carotenoids, antioxidant activity, and chlorophyll pigments were observed between swell-dried and conventional shadow dried okra pods. An increase of 25% and 99% was respectively observed for the relative expansion ratio and flavonoid content in swell dried okra pods compared with conventional shadow dried ones. The microstructure observations showed a significantly more porous open solid matrix of swell-dried okra pods compared to the compact/dense solid matrix of the conventional shadow dried okra pods. The optimum conditions of DIC-texturing were found to be 0.4 MPa for 50 s exhibiting the highest values of total phenolic content, flavonoids, antioxidant activity, and chlorophyll pigments with good preservation of the carotenoid content.
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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".