Monitoring the plant epiphyte Methylobacterium extorquens DSM 21961 by real-time PCR and its influence on the strawberry flavor
Bibliographic record
Abstract
Besides its influence on plant growth and health, plant-associated bacteria exert an impact on fruit quality. Methylotrophic bacteria can enhance the biosynthesis of strawberry flavor compounds, especially the two furanoid compounds 2,5-dimethyl-4-hydroxy-2H-furanone (DMHF) and 2,5-dimethyl-4-methoxy-2H-furanone in vitro. Here, we report the selection and characterization of Methylobacterium extorquens DSM 21961, a strain that was able to enhance the furanone content ad planta under greenhouse conditions. For monitoring the colonization of strawberry plants, a strain-specific quantification system for M. extorquens DSM 21961 was developed. Specificity, linear range and quantitative limit of the system were shown, and successful application was demonstrated in a monitoring experiment of M. extorquens DSM 21961 on strawberry leaves under greenhouse conditions. Furthermore, the quantification of DMHF in strawberry fruits via GC indicated an increased biosynthesis of this compound in strawberry plants. The colonization behavior analyzed by confocal laser scanning microscopy using GFP-tagged cells revealed high colonization of the upper and the lower leaf surfaces, with a specific accumulation of bacterial cells on trichomes. The results support a biotechnological application of this promising flavor-stimulating agent.
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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) | 0.001 | 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 | 0.001 | 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".