Physiological Quality of Soybean Seeds Subjected to Industrial Treatment Before and After Storage
Bibliographic record
Abstract
This research work aimed to evaluate the physiological quality of soybean seeds subjected to different chemical treatments, before and after seed treatment, throughout conventional storage. A completely randomized design was adopted, with 4 replications, in which the treatments were arranged in a 2 × 7 × 6 factorial scheme (time of treatment (before and after) × industrial seed treatment (IST) × storage period (0, 15, 30, 45, 60 and 90 days). For each IST, the specific volume of slurry was 0, 700, 900, 1400, 900, 1100 and 1600 100 kg-1 of seeds, respectively. A total of 2.5 kg of seeds, cultivar BMX Alvo RR, were used. After being treated, the seeds were placed in kraft paper bags and stored at controlled temperature and humidity in a cold chamber. Their physiological quality was evaluated after each storage period using standard germination test, first germination count, emergence speed index, final emergence in sand substrate, accelerated aging, radicle length, shoot length, and whole seedling length. Their physiological quality was reduced in treatments with higher volumes of slurry. Deleterious effects on vigor were observed with increasing storage period, both before and after IST. After seed treatment, the mean of the analyzed variables was considered higher, compared to the time prior to seed treatment.
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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".