Silver Maple (Acer saccharinum L.) Leaf: A Potential Source of Antibacterial Compounds to Control Phytopathogenic Bacteria in Horticulture Crops
Bibliographic record
Abstract
In this study, a crude ethanolic extract made of silver maple ( Acer saccharinum L.) leaves (SML) was evaluated for antibacterial activity against the phytopathogenic bacteria Clavibacter michiganensis subsp. michiganensis , Pseudomonas syringae pv. tomato , and Xanthomonas fragariae . The extract was shown to cause important inhibition zones against the three bacteria in the disc diffusion assays, revealing its antibacterial activity. The minimal inhibitory concentration (MIC) of the extract was determined thereafter for each bacterium. The extract showed the same MIC value (1.56 mg·mL −1 ) for the three bacteria. Using a semipreparative high-performance liquid chromatography system, crude ethanolic SML extract was divided in 15 fractions and each fraction was tested for antibacterial activity against X. fragariae with the disc diffusion assay. Among the six fractions causing an inhibition zone, fraction 10 caused the largest inhibition. Fraction 10 was further analyzed by ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry. According to quadrupole time-of-flight mass spectrometry, the main peak of fraction 10 was identified as a galloyl-bis-HHDP-glucose (C 41 H 28 O 26 , 936.6454 g·mol −1 ) isomer, an ellagitannin known for antibacterial activity and for stimulating plant natural defenses. The study opens new avenues of research on the valorization of SML and on the control of plant diseases caused by bacteria in organic and conventional production of horticultural crops.
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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".