<i>Fusarium</i> <i>verticillioides</i> induction of maize seed rot and its control
Bibliographic record
Abstract
Experimental evidence is lacking to demonstrate whether Fusarium verticillioides (synonym = Fusarium moniliforme J. Sheld.; teleomorph = Gibberella fujikuroi (Sawada) Ito in Ito & K. Kimura, mating population A) functions as a causative agent or an opportunistic invader in seed (caryopsis) rot of maize (Zea mays L.). Previous researchers have isolated this fungus, along with many other microorganisms, from seed collected in the field long after rot commenced. The current investigations used an isolate of F. verticillioides transformed with a selectable marker and a reporter gene to inoculate previously disinfected maize seed. Seed rot developed, and F. verticillioides containing the introduced genes was isolated from inoculated, but not noninoculated, seed. Efficacy of Plantpro-45, an agent with an iodine-based active ingredient (a.i.), was analyzed for controlling growth of F. verticillioides from conidia and inoculated maize seed. A solution containing <10 µg a.i./mL inhibited growth of conidia suspended for <30 s. Furthermore, seed rot was controlled without diminishing seedling survival at 10 mg a.i./kg maize seed. Thus, F. verticillioides can function as the causative agent of maize seed rot and can be suppressed and (or) controlled at the postinfection stage with Plantpro-45.Key words: mycotoxin, reporter gene, germination, iodine.
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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 | 0.000 |
| 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) | 0.001 | 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".