Quality of Phytosanitary Application in Ricinus communis L. Cultivation
Bibliographic record
Abstract
One of the main challenges in castor bean (Ricinus communis L.) crop is controlling gray mold (A. ricini), a fungal disease. Most fungicides used are contact-based, and the plant’s architecture complicates application efficiency. The objective of this research was to evaluate droplet deposition and spectrum in different parts of the castor plant canopy using various spray tips and flow rates. The experiment was conducted at the Instituto Mato-Grossense do Algodão (IMA) in Rondonópolis, MT, using a New Holland TL 75 tractor and a Jacto Columbia Cross sprayer. The results were in percentages and a 3-factor factor analysis was performed, where A (Tip) = 2 levels, B (Volume) = 3 levels and C (Position) = 3 levels ith four replications, using Scott-Knott test and software Assistat. Treatments involved two hydraulic nozzles (JAC 80015 and JAC 8002), three flow rates (120, 150, and 180 L per ha⁻¹), and three plant positions (lower, middle, upper third). Data were analyzed using the “F” test and compared by the Scott-Knott test at a 5% significance level. The results showed that spray tips influenced VMD, NMD, and product concentration, with greater deposition and coverage observed in the upper third of the plant.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".