Effect of Silicon Sources on Sugarcane Orange Rust, Ring Spot and Red Rot in Brazil
Bibliographic record
Abstract
Brazil is the world’s largest producer of sugarcane (Saccharum officinarum), but the occurrence and severity of diseases such as orange rust (Puccinia kuehnii), ring spot (Leptosphaeria sacchari), and red rot (Colletotrichum falcatum) could be part of several factors limiting its production and is the reason for replacing cultivars. It is important to use other forms of disease control depending on the time required to obtain new resistant varieties. The use of silicon (Si) can provide more resistance to the plant making its less vulnerable to diseases. A study was conducted under greenhouse and field conditions. The greenhouse study had 13 treatments (control, fungicide, foliar solution I and II, K silicate, silicic acid at 20, 40 and 60 mg ha-1, wollastonite, agrosilicio, wollastonite + fungicide, wollastonite + K silicate; agrosilicio + fungicide; and agrosilicio + K silicate) with four replications. The field study had nine treatments (control, fungicide, foliar solution I and II, K silicate, silicic acid at 100 and 300 g ha-1 and phosphite at 0.5 and 1 L ha-1) and with three replications. Both studies used a randomized block design. The greenhouse study showed an increase in dry mass of pre-sprouted sugarcane seedling and Si uptake with foliar treatments, especially with silicic acid. K silicate and silicic acid showed lower severity of orange rust than the control and fungicide. On the field study silicic acid at 100 g ha-1 and 300 g ha-1 was more efficient in reducing the area under the disease progress curve (AUDPC) of ring spot compared to the control and K silicate. Fungicide was also more efficient in reducing AUDPC compared to the control as well.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".