Characterization of Water States in Canola Seeds With Varying Moisture Contents Using Differential Scanning Calorimetry
Bibliographic record
Abstract
Characterization of water status in grains is essential for grain drying, storage, and handling. A state diagram of canola seeds was developed incorporating the freezing curve, glass transition line, and critical moisture content (MC) at which freezable water first appears using differential scanning calorimetry. Cooling and heating rates of 1, 2, 5, 10, and 20°C/min were tested, and 1°C/min was used to determine the freezing and melting parameters such as peak temperature, onset temperature, and enthalpy. Below 17.8% MCs, the freezing point varied, and the minimum was about -26°C, whereas, beyond 17.8% MC, the freezing point increased to -6.72 ± 0.18°C at 35.8% MC. The critical MC was about 16%. Below this threshold, all remaining water exists as unfreezable water. Multiple glass transitions were observed across all tested MCs, with the first glass transition becoming undetectable above 6.2% MCs. As MC increased, the temperatures of the second and third glass transitions decreased, reaching 63.46 ± 0.39°C and 73.38 ± 0.98°C, respectively, at 35.8% MC. The developed state diagram will be useful for understanding effects of MC and temperature on the water state, and it will offer guidance for drying, handling, and storage strategies for canola seeds. PRACTICAL APPLICATIONS: The state diagram aims to elucidate changes in water state as a function of MC and temperature, ultimately informing the selection of suitable conditions for handling and storage of canola. In addition, the state diagram will be used to determine the material state and knowledge about the material state is necessary for selecting suitable drying conditions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".