Comparación de métodos de inoculación de Fusarium oxysporum f. sp. lycopersici (Sacc.) Snyder & Hansen, causante del marchitamiento vascular del tomate
Bibliographic record
Abstract
Tomato (Solanum Lycopersicum L.), the most important vegetable in Colombia and worldwide, is attacked by numerous diseases, among them, the vascular wilting caused by Fusarium oxysporum f. sp. lycopersici. The disease can cause losses between 21 and 47% in full exposure and under cover crops. The objective of this work was to compare four inoculation methods of this fungus in seedlings of the Sweet Million cultivar obtained from seeds and planted in sterilized Canadian peat and in MS medium and maintained under controlled conditions at the Laboratory of Tissue Culture and thermotherapy room of the Universidad de Caldas where 25 seedlings were selected per method of inoculation. The treatments were: Injection in the crown root (T1), immersion of the roots (T2), agar disc in the crown root (T3), and inoculation in vitro (T4). The final disease incidence and the comparative tests of Duncan showed highly significant differences (p≤0.001) among the different methods of inoculation. The only method that induced a 100% incidence of the vascular wilt in the shortest period of incubation was the in vitro method. The highest rate of disease development (r) was obtained with the in vitro inoculation method (r=0.92) followed by agar discs, immersion, and injection. The in vitro inoculation method can be useful for the massive selection of tomato materials promising against vascular wilt. © 2019. Acad. Colomb. Cienc. Ex. Fis. Nat.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".