Reduced Asian Soybean Rust Control by Commercial Fungicides Co-formulations in the 2018-2019 Growing Season in Southern Brazil
Bibliographic record
Abstract
It has been a growers concen the reduction of Asian soybean rust (ASR) control by commercial fungicide co-formulations in the last growing seasons in southern Brazil. The objective of this work was to assess the ASR control efficacy by the most used co-formulations in the 2018/19 season. In a field experiment, 19 fungicides in commercial formulations to control soybean rust caused by Phakopsora pachyrhizi, were evaluated. Chemicals at their recommended doses were sprayed at four soybean growth stages. The first application was performed with 1.82% leaflet incidence and coinciding with R1 phenological stage. The others were performed at 14-18 days intervals. At stage R6, end of the epidemic and coinciding with half of the defoliation in the control plots, the leaf severity was appraised. The experiment was conducted with Ativa soybean cultivar, in 3 × 6 m plots, four replications and randomized block design. The harvest was made with a plot combine and the yield expressed in grains kg/ha. The means were compared by the Scott-Knott test. The disease control efficacy by 17 fungicide co-formulation showed control less than 57%, one with 78% and none with ≥ 80%. The unsprayed treatment severity was 81% and the greatest control of 78% resulted in 3,876 kg/ha yield. Therefore, the hypothesis raised in this work was accepted showing that the site-specific fungicides co-formulations are showing efficacy reduction season after season.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".