PHYTOCHEMICAL INVESTIGATION AND IDENTIFICATION OF ACTIVE CONSTITUENTS FROM EXTRACT OF PINUS. SYLVESTRIS AND ITS EFFICACY AGAINST GRAPEVINE DOWNY MILDEW (PLASMOPARA VITICOLA)
Bibliographic record
Abstract
Downy mildew is a plant disease which is instigated by a distressing pathogen of grapevine called oomycete Plasmopara viticola. In the current study extracts of bark of Pinus Sylvestris was screened to find the activity against the pathogen and to identify the active constituents through phytochemical investigation. Extracts showed activity against P. viticola but Dichloromethane extracts showed most result and lead to the isolation of a rosin acid 7a, 15- hydroxyl dehydroabietic acid. The isolated compounds were fully characterized using spectroscopic analysis 1D and 2D NMR, IR, optical rotation and spectrometric analysis using GC-MS. Out of these 7a,15- hydroxyl dehydroabietic acid showed 90% 100% efficacy. The isolated secondary metabolite is obtained from renewable sources in large amounts at comparatively cheaper prices. Hence this active constituent is indeed strong candidate for the economical production of Natural plant derived Fungicide against a pathogen. This is a great opportunity for forest and agricultural industry for the conversion of low value by-products into more efficient high value added bioactive extracts
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".