Desorption and Sorption Isotherms of Different Varieties of Hemp Seeds with Different Percentages of Dockage under Different Temperatures and Different Relative Humidities
Bibliographic record
Abstract
Hemp cultivation faces challenges due to the adoption of dioecious cultivars, which suffer from biomass loss and fibre heterogeneity. In contrast, monoecious cultivars offer simultaneous fibre and seed production, albeit with lower fibre quality. Understanding the drying characteristics and storage requirements of hemp seeds is crucial for effective post-harvest management. This study explored the moisture sorption and desorption isotherms of two common Canadian hemp seed varieties, Altair (dioecious) and CanMa (monoecious), by using both saturated salt solution (SSS) and thin-layer drying methods. Their isotherms were also compared with the published isotherm of Finola—a common dioecious variety in Europe. The thin-layer drying method yielded higher EMC values than the SSS method due to incomplete equilibrium attainment. Larger EMC differences existed between different seed types (dioecious vs. monoecious), and this difference was small between the same seed types (dioecious vs. dioecious). The GAB equation provided the most accurate prediction of equilibrium moisture contents for both varieties.
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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".