Study on Drying of Black Rice (Oryza sativa L.) Grains: Physical-Chemical and Bioactive Quality
Bibliographic record
Abstract
The present study aimed to assess the drying kinetics of black rice and fit different mathematical models (empirical and diffusive) to the experimental data, and evaluate the effect of drying air temperature on the physical-chemical and bioactive compounds quality of black rice. Drying air temperatures ranged from 40 to 80 ºC and the drying air speed was 1.5 m/s. Physical-chemical characterization of the product was based on the following parameters: moisture, water activity, ashes, total protein content, pH, total acidity, lipids, total carbohydrates, total anthocyanins, flavonoids, total phenolic compounds and antioxidant activity. Among the empirical models, Page showed the lowest mean squared deviations (MSD) and highest coefficients of determination (R2). For the diffusion model, the values of effective mass diffusivity and convective heat transfer coefficient increased with increasing drying air temperature, and the Biot number indicated that the first-type boundary condition would also describe well the drying process. Physical-chemical parameters and bioactive compounds differed between the temperatures used, and the temperature of 60 ºC led to the best relationship between drying time and preservation of product characteristics.
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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) | 0.000 | 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".