Antifungal activity of some common weed extracts against phytopathogenic fungi Alternaria spp.
Bibliographic record
Abstract
Herbal fungicides are mostly using to control plant disease of fungi because of their ecofriendly nature and their cost effectiveness. The present investigation focuses on the antifungal activity of solvent based extracts extracted from some common weeds Achyranthes aspera, Parthenium hysterophorus, Cannabis sativa, Calotropis gigantean, Chenopodium album, Canada thistle, Phalaris minor, Cynoden dactylon, Argemone maxicana, Ageratum conyzoides, and Lantana camera were screened against seed-borne phytopathogenic fungus Alternaria SPP. by modified food poison method. The acetone, methanol, benzene, ethyl acetate and chloroform extracts of different parts of plants were evaluated for this study; the antifungal activity was more effect in extracts of \nAgeratum conyzoides and Parthenium hysterophorus, against phytopathogenic fungus Alternaria SPP. The present study \nsuggests that chloroform and methnol extracts of Ageratum \nconyzoides and methanol extract of Parthenium hysterophorus, can form the basis for the development of novel broad spectrum herbal fungicidal formulations. We conclude from this that these extracts exhibit amazing fungicidal properties that support the notion that plant extracts may be used as herbal fungicides.
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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) | 0.002 | 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".