Subdoses of Dicamba Herbicide on Yield Componentes in Function of the Soybean Growth Stage
Bibliographic record
Abstract
Soybean cultivars without tolerance can suffer injury from exposure to tank herbicide residues. This study aimed at assessing the potential effects of the broad spectrum herbicide dicamba on sensitive soybean during its vegetative and reproductive stages. The trial was performed in a randomized complete block design with four replications. Six rates (1.4, 2.8, 5.6, 11.2, 16.8 and 28.0 g ae ha-1) of dicamba were applied at two soybean growth stages (V3 and R2). The soybeans were planted in Passo Fundo, Rio Grande do Sul state in 2015/16 agricultural year. The dicamba induced symptoms of soybean phytotoxicity showed a steady rise at all the assessment times. The soybean decreased in height as the subdose of the herbicide increased. Dicamba was observed to negatively affect the number of nodes alone, during the V3 and R2 stages. The grain yield was adversely affected at the 28.0 g ae ha-1 subdose, in the V3 application stage, and in response to the 16.8 and 28.0 g ae ha-1 subdoses in the R2 stage.
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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".