Plant seedlings of peas, tomatoes, and cucumbers exude compounds that are needed for growth and chemoattraction of <i>Rhizobium leguminosarum</i> bv. <i>viciae</i> 3841 and <i>Azospirillum brasilense</i> Sp7
Bibliographic record
Abstract
This study characterizes seedling exudates of peas, tomatoes, and cucumbers at the level of chemical composition and functionality. A plant experiment confirmed that Rhizobium leguminosarum bv. viciae 3841 enhanced growth of pea shoots, while Azospirillum brasilense Sp7 supported growth of pea, tomato, and cucumber roots. Chemical analysis of exudates after 1 day of seedling incubation in water yielded differences between the exudates of the three plants. Most remarkably, cucumber seedling exudate did not contain detectable sugars. All exudates contained amino acids, nucleobases/nucleosides, and organic acids, among other compounds. Cucumber seedling exudate contained reduced glutathione. Migration on semi solid agar plates containing individual exudate compounds as putative chemoattractants revealed that R. leguminosarum bv. viciae was more selective than A. brasilense, which migrated towards any of the compounds tested. Migration on semi solid agar plates containing 1:1 dilutions of seedling exudate was observed for each of the combinations of bacteria and exudates tested. Likewise, R. leguminosarum bv. viciae and A. brasilense grew on each of the three seedling exudates, though at varying growth rates. We conclude that the seedling exudates of peas, tomatoes, and cucumbers contain everything that is needed for their symbiotic bacteria to migrate and grow on.
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) | 0.001 | 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".