Stem rot management by nitrogen and potassium fertilization and effect on grain yield and quality of rice in Uruguay
Bibliographic record
Abstract
Stem rot (Nakataea oryzae) limits rice (Oryza sativa) production in Uruguay when there are high inoculum levels in the soil. This disease is particularly damaging in potassium (K)-deficient soils that receive excessive nitrogen (N) fertilization. Nevertheless, no data exist for the response to stem rot in modern rice cultivars with respect to the interaction between balanced N and K fertilization. The aim of this work was to evaluate the combined effect of K and N fertilization and a foliar phosphite (Phi) in reducing stem rot severity in rice to prevent significant yield losses. A 3-year field study was conducted in a rice-producing region of Uruguay to investigate the effects of: (1) K fertilization rate, 0 or based on the Mg:K ratio; (2) N fertilization rate, 0 or 140 kg ha–1 N; and (3) Phi treatment, with or without foliar Phi (1.775 kg ha–1 of K Phi, 71%), at growth stage R2-R3. While the experiment was conducted in a soil with sufficient potassium, K fertilization reduced the severity and percentage of rice tillers that were severely affected by stem rot, resulting in a mean yield increment of 2% to 18% depending on the year (mean 7.5%). Nitrogen fertilization increased stem rot severity in only 1 year, but resulted in a mean yield increment of 10% over the 3 years of the experiment. Foliar Phi applied at the late boot to panicle exertion stage did not reduce disease incidence or severity and failed to increase the total rice grain and milling yield.
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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 | 0.000 | 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) | 0.000 | 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".