Sugar maple leaf extracts: A new tool to control bacterial canker of tomato caused by <i>Clavibacter michiganensis</i> subsp. <i>michiganensis</i>
Bibliographic record
Abstract
Abstract Bacterial canker caused by Clavibacter michiganensis subsp. michiganensis (Cmm) is a worldwide bacterial disease affecting tomato plants. Very few control methods exist and their efficacy is limited. In recent years, plant extracts were studied for their potential as a safe and eco‐friendly alternative to the use of chemical pesticides to control plant diseases. Recent work performed by our group revealed the antibacterial activity of an ethanolic sugar maple autumn‐shed leaf (SMASL) extract against bacterial plant pathogens. To further investigate the antibacterial and prophylactic potential of SMASL against bacterial canker, assays were performed (a) to determine the polyphenol content and the in vitro antibacterial activity of sugar maple leaf extracts against Cmm, (b) to evaluate the potential of SMASL extracts as a seed treatment against Cmm and (c) as a foliar application to control bacterial canker development in greenhouse‐ and field‐grown tomato plants. Variations in polyphenol content and antibacterial activity of sugar maple leaf extracts were studied monthly for a period of 2 years. Although polyphenol contents varied significantly, minimum inhibitory concentrations were constant between 1.56 and 3.13 mg/mL and minimum bactericidal concentrations between 12.5 and 25 mg/mL. SMASL extract at 25 mg/mL completely eliminated the pathogen from tomato seeds without negatively impacting on germination. SMASL extract foliar spray applications using concentrations of 6.25 and 12.5 mg/mL significantly repressed disease development under greenhouse and field conditions, showing better efficacy than copper octanoate. The antibacterial activity of SMASL extracts against Cmm shows great potential to control Cmm and bacterial canker in tomato.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".