Quality of Castor the Seeds Stored in Different Environments and Type of Packaging
Bibliographic record
Abstract
One of the ways to offer high quality seeds to the market is to work on better storage conditions to keep the physiological quality of the seeds high. Thus, this work aimed to evaluate the physiological quality of hybrid castor seeds during storage in different environments and packaging in the Cerrado conditions. A completely randomized design with plots subdivided over time was used, with four replications. In the plots the factorial 2x3x7 was designated, being: 2 environments (cold chamber and laboratory environment) and 3 packages (kraft paper, plastic bag and PET bottle) and in the subplots the 7 storage times (0, 2, 4, 6, 8, 10 and 12 months). The castor seeds used were from the hybrid cultivar AG IMA 110204 and were stored in the laboratory of the State University of Goiás, Câmpus Anápolis. The following tests were carried out: water content, germination test, first count, electrical conductivity, length, seedling dry mass and seedling dry mass density. The data were submitted to analysis of variance, the qualitative treatments when significant were compared by the Tukey test, while the quantitative treatments were submitted to the regression analysis. It is recommended to use both a plastic bag and a PET bottle to package AG IMA 110204 hybrid castor seeds during twelve-month storage, both in cold storage and in a laboratory environment.
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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 | 0.001 | 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".