Pre-harvest Desiccation: Productivity and Physical and Physiological Inferences on Soybean Seeds During Storage
Bibliographic record
Abstract
The objective of this research is to define which soybean phenological stage is adequate to promote pre-harvest desiccation and to measure the effects of this procedure on the physical and physiological attributes of soybean seeds throughout storage. The experiment was carried out at Fazenda Santa Bárbara da Boa Vista located in the municipality of Cabeceiras, Goiás, Brazil. The experimental design was the randomized blocks arranged in a factorial scheme being five phenological stages of soybean development where desiccant was applied (R5.5, R6.0, R7.1, R7.3 and R8.3) × five post-harvest storage times (0, 40, 80, 120, 160 days), arranged in four replicates. The measured characters were: Productivity, Mass of one thousand seeds, Retention of sieves 5.5 mm, 6.0 mm and 6.5 mm, Germination, Accelerated aging and Field emergence. The application of the Paraquat molecule in soybean plants in the phenological stages R5.5 and R6.0 compromises the physical attributes, mass of a thousand seeds and productivity. The germination and vigor of the soybean seeds are adversely affected due to the early desiccation of the plants, and these effects are potentiated throughout the seed storage.
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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".