Sustainable Integrated Approach for Management of Fusarium Wilt of Tomato Caused by Fusarium oxysporum f. sp. lycopersici (Sacc.) Synder and Hansen
Bibliographic record
Abstract
Integration of different methods for sustainable management of Fusarium wilt of tomato revealed that all the treatments were able to significantly reduce the disease severity over control. Among the treatments, the minimum disease severity was recorded in the T3 treatment where treatment was given as seed treatment with T. harzianum + soil application of neem cake powder + foliar spray of carbendazim, representing the value 4.82, 8.23, 12.37 and 16.37 per cent against 10.75, 14.84, 20.00 and 25.75 per cent in case of control at 30, 45, 60 and 75 days age of plant, respectively. Integrated approach has also been able to increase shoot length as 27.00, 42.15, 54.98, and 65.07 cm at 30, 45, 60 and 75 days age of plant, respectively whereas in case of control it was 18.60, 25.70, 34.63 and 44.29. Similarly, fresh and dry shoot and root weight have also been found increased in case of integrated approaches. Biochemical analysis of the treated plants revealed that highest soluble protein and total phenol content is observed in T3 treatment (Seed treatment with T. harzianum + soil treatment with neem cake powder and foliar spray with carbendazim), showing 37.85, 36.78 and 35.76 mg/gm of fresh leave of protein and 2.40, 2.14 and 2.04 mg/gm of fresh leave of phenol at 30, 45 and 60 days age of plant. As per yield is concerned, it has found that the maximum yield was obtained per plant from the treatment given as seed treatment with T. harzianum + soil treatment with neem cake powder + foliar spray with carbendazim, showing the value of 500 g per plant which was followed by the treatment given as seed treatment with T. harzianum + soil treatment with neem cake powder + foliar spray with neem leaf extract showing 470 g per 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 | 0.000 |
| 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".