Effect of storage conditions on deterioration of rye and canola
Bibliographic record
Abstract
Canada produces about 0.32 million tonnes of rye and 6.9 million tonnes of canola annually. Moisture content and storage temperature are the two major factors that influence the deterioration of grain during storage. The objective of this work was to determine the safe storage period of canola and rye at various moisture and temperature conditions. Canola and rye with different initial moisture contents (10, 12.5, 15, and 17.5% (wb) for rye and 7.5, 10, 12.5 and 15% (wb) for canola) were stored at four different temperatures (10, 20, 30 and 40oC) for 16 weeks. Germination, moisture content and appearance of visible mould were measured every week and invisible moulds were identified once every four weeks. Moisture content, temperature and storage period had significant effects on germination rate (a=0.05). Germination rate of the 17.5% moisture content rye samples and 15% moisture content canola samples reached 0% during fifth and fourth week, respectively. But it remained above 80% for the samples stored at low moisture and low temperature even during the 16th week. Moisture content of the samples stored at 10oC did not change significantly. But that of the samples stored at 30oC reached 5-7% (canola) and 10-13% (rye) during the 16th week and at 40oC, it decreased to 2-4% (canola) and 5-6% (rye) during the last week of storage. High moisture samples lost moisture with increased storage temperature and time. The visible mould started appearing during the first week of storage in the high moisture samples stored at 40oC. Appearance of visible mould increased with increasing moisture content and storage temperature. Aspergillus and Penicillium species occurred predominantly in both the grains. Safe storage period decreased with increasing temperature and moisture content.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".