Kinetics and Quality of Quinoa Seeds After Drying and During Storage
Bibliographic record
Abstract
This study aimed to assess the effect of different drying forms, environments, and storage periods on germination and sanitary quality of quinoa seeds cv. BRS Syetetuba. Seeds were submitted to drying in forced air circulation chamber at 30, 40, and 50 °C and in a suspended tray, in full sun, until they reached ±12% of moisture content. The observed drying data were adjusted to 10 mathematical models. The storage for 360 days was continuous in three different environments. Seeds were evaluated at 0, 6, and 12 months for germination, first count of germination, moisture content, and sanity tests. The experimental design was completely randomized, in a split split-plot scheme with four replicates. Among the studied models, Midilli was efficient in describing the drying curves of quinoa seeds. The storage environment influenced the loss of seed quality more than the drying temperature. The increased storage period caused a decrease on fungal seed incidence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".