Phytotonic Effect of Fungicide Mixtures Applied at Different Periods in Sweet Corn
Bibliographic record
Abstract
The fungicides belonging to the chemical groups of strobilurins and triazoles have their contribution to increase the productivity of the crop by a phytotoxic effect. The objective of this study was to evaluate the effects of fungicides at different times on the quality and quality of the spikes. The experiment was conducted at the Universidade do Estado de Minas Gerais and the experimental design was in randomized blocks, with 4 replicates, factorial factorial 3 × 3 + 1, the first factor being composed of 3 combinations of fungicides and the 2 applications (49, 56 and 63 days after sowing-DAS) + 1 witness. The lot was composed of 4 rows spaced 0.45 m and the harvest was done manually at 83 DAS. The height of the plant, the height and the diameter of the glue in the first ear, total mass of ears with and without straw, grain mass per ear, length and diameter of the ears and productivity were evaluated. The data were analyzed by variance and as means compared by the Tukey test. The height of a plant was significantly affected throughout its life in the treatments at 63 days. The series were concentrated by the treatments are a non-spike mass, grain mass per spike and productivity, and pressure levels were loaded when they were performed at 63 DAS.
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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".