Physical and Physiological Quality of Safflower Seed Stored in Different Packages and Temperatures
Bibliographic record
Abstract
Seed storage is one of the oldest techniques that, besides protecting against attacks of microorganisms and insects, has as main goal to preserve the product, with minimum losses, ensuring vigor and viability of the seeds. Safflower (Carthamus tinctorium L.) is a crop with great agricultural potential due to the high content of oil in its seed and can be a viable alternative in the production of biofuel. The goal of this study was to evaluate the effects of packaging and storage temperatures on the physical and physiological quality of safflower seeds. The experiment was conducted in the soil and plant production and bromatology laboratories of the Institute of Agrarian and Technological Sciences, Federal University of Mato Grosso Campus of Rondonópolis, in the period of July to September 2014. The experiment was a completely randomized design in a 5 × 2 factorial scheme, corresponding to five temperatures (10, 15, 20, 25 and 30 °C) and two packages (cotton and paper) with five replicates. The physical quality parameters (water content in the seed, mass of one thousand seeds, hectolitre weight) and physiological parameters (percent germination, Seed viability (Tetrazolium), accelerated aging and electric conductivity) of the seeds were evaluated. The physical quality of the safflower seed was not influenced by, the types of packaging and storage temperature. The physiological parameters of safflower seeds were significantly altered by the the type of containers and storage temperatures conditions. The paper packaging, at temperatures of 20 and 25 °C, provided greater conservation of the seed.
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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 | 0.000 | 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".