Morphological and genetic characterization of Fusarium oxysporum and its management using weed extracts in cotton
Bibliographic record
Abstract
Fusarium oxysporum, a fungal plant pathogen, causes severe wilting and heavy losses in cotton. Present research was planned to appraise the weed extracts of Parthenium hysterophorus, Chenopodium album, Canada thistle and Phalaris minor against F. oxysporum. Morphological identification of F. oxysporum was done by observing white cottony mycelium with dark-purple undersurface on growth media and oval to ellipsoid/kidney shaped oval tapering and three septate spores. Molecular characterization was done by amplifying internal transcribed spacer region using the ITS universal primers, ITS1 and ITS4. The weed extract with concentrations of 5%, 10%, 15% and 20% were applied by using food poison techniques under complete randomized design. Data was taken 3, 5 and 7 days after inoculation of F. oxysporum on potato dextrose agar (PDA). P. hysterophorus showed maximum antifungal response (97%) against F. oxysporum whereas other treatments effectively inhibited the pathogen growth on PDA media. Tebuconazole, a fungicide, was used as positive control. Trichoderma harzianum showed 98% inhibition of F. oxysporum on PDA. Consortium of Trichoderma harzianum + weed extracts was applied in infected roots of cotton grown in pots under complete randomized design. No disease was observed in treatment P. hysterophorus + T. harzianum whereas maximum disease was calculated (50%) in other treatments as compared to control (100%).
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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".