Influence of moisture content and sub-zero storage conditions on thermogram behaviour of canola seeds
Bibliographic record
Abstract
Wet, oil-rich seeds such as canola are especially prone to freeze-induced viability loss under sub-zero temperatures (<0 °C) during handling, processing, and storage. This study characterized the thermogram parameters of canola seeds with different moisture contents (MC, wet basis, 4.% - 30%) under low and sub-zero temperatures (5, -5, -15, and -25 °C). Both frozen canola seeds (20.1% MC stored at -25 °C for more than 20 wks before DSC test) and fresh seeds (different MC and not frozen before DSC test) were tested. Thermogram transitions were largely moisture dependant. Freezing events were not detected in canola seeds with <12% MC. This reflects the biological state of water that at low MC, water is predominantly bound and does not crystallize. Distinct exothermic freezing events occurred at ≥14% MC, signifying detectable freezable water and ice formation. Notably, cooling rate and cooling temperature did not influence the nucleation and freezing point temperature. The freezing point temperature of canola seeds with ≥ 14% MC was about -2.5 to -8 °C. Modulated differential scanning calorimetry showed canola oil components contributed freezing events at around -30 °C, involving significant enthalpy changes. A significant reduction in melting enthalpy was found in frozen seeds compared to fresh seeds, indicating cell structure damage. This study provides crucial mechanistic understanding, advancing cold-climate preservation strategies for canola and offering broader insights for other oilseeds and grains. • First thermal evidence of freeze thresholds in stored canola across wide MC range. • Ice nucleation initiated above 14% MC; critical for sub-zero seed storage. • MDSC revealed enthalpy loss at -25 °C, indicating structural collapse. • Seeds ≤12% MC showed no freezing, validating existence of critical MC threshold. • Reveals limited impact of cooling rate on ice nucleation in low MC canola seeds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".