Bioactive dry extract production from <i>Hymenaea courbaril</i> L. bark via spouted bed drying
Bibliographic record
Abstract
Abstract The work aims to develop and optimize a powdered phytopharmaceutical product from the stem bark of Hymenaea courbaril L. (jatobá) by the spouted bed drying. The study commenced with the extraction of bioactive compounds present in the plant raw material by dynamic maceration using ethanol/water 70% (v/v) at a temperature of 50°C for 60 min, for the ratio stem bark: solvent mass of 1:10 (w/w). The extract quality was assessed by quantifying chemical markers via spectrophotometry (total polyphenols and tannins) and through antioxidant activity by 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) assay. The extractive solution was concentrated, added with drying adjuvant, and submitted to spouted bed drying. Product quality was evaluated by moisture content ( X p ), water activity (a W ), powder diameter, total polyphenols, and tannins content (P T and T T ), and antioxidant activity, expressed as the extract concentration needed to reduce 50% of the DDPH radical (IC 50 ). Spouted bed drying performance was evaluated through the drying yield ( R EC ), product accumulation (A c ), and thermal efficiency ( η ). The optimal processing conditions were: inlet gas temperature, T gi : 150°C, the ratio of the mass feed flow rate of the concentrated extract to the evaporation capacity of the dryer, W s / W max : 45%, and the drying gas flow rate relative to minimum spouting, Q / Q ms : 1.85. Under these conditions, it is predicted to obtain a dried extract with X p = 4.9% w/w, P T = 26.0% w/w, R EC = 77.7% w/w, η = 44.3%, and A c = 10% w/w, with adequate values of a W , T T , and high antioxidant activity.
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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 | 0.000 | 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".