Effect of pre-harvest treatments on equilibrium moisture contents and safe storage of canola
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For safe storage of canola seeds, the effect of different pre-harvest treatments on seed storability should be determined. Safe storage times of canola seeds (Bayer L233P) with the following five pre-harvest treatments were evaluated: swathed, Glyphosate application + straight cut, Heat and Glyphosate application + straight cut, Reglone application + straight cut, and natural ripening + straight cut. The pre-harvest treated seeds were stored at 20, 25, 30, or 35oC and 52, 63, 75, or 93% relative humidity (RH). The following parameters were measured to estimate the safe storage time: seed equilibrium moisture content (EMC), germination, fatty acid value (FAV), yellow seed count, and invisible mould. The measured EMCs were compared with the EMCs predicted by the equations recommended by the ASABE standard. Different pre-harvest treatments resulted in different desorption properties of canola. None of the ASABE equations was able to predict the measured EMCs correctly. Different pre-harvest treatments had different initial fungal infections. However, these differences did not affect the fungal infection, FAV, germination, and yellow seed counts, with some exceptions for swathed canola in the storage period. The yellow seed count decreased under safe storage conditions (lower than 75% RH and 25oC), but increased at 93% RH and 25oC except for the swathed canola. Therefore, canola seeds with different pre-harvest treatments had a similar storability at below 75% RH or below 30oC. However, the spoilage rates of canola with different pre-harvest treatments at storage conditions of high temperatures (≥30oC) and high RHs (≥75%) were different.
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.
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 it