Bacterial endophyte communities of two wheatgrass varieties following propagation in different growing media
Bibliographic record
Abstract
Bacterial endophyte communities of two wheatgrass varieties currently being used in the revegetation of military training ranges were studied. Culturable and direct 16S rDNA PCR amplification techniques were used to describe bacterial communities present in Siberian and slender wheatgrass seeds, leaf tissues, and root tissues following propagation in either sand or a peat-based growing mix. Our hypothesis was that the resulting plant endophytic communities would be distinct, showing not only the presence of endophytes originating from the seed but also the characteristics of growth in the two different growing media. Both culture and culture-independent assays showed the likely translocation of Actinobacteria, Firmicutes, and Gammaproteobacteria from seed to mature plant tissues as well as subsequent colonization by exogenous organisms. Statistical analysis of 16S terminal restriction fragment profiles identified growing media as having a greater significant effect on the formation of the endpoint endophytic communities than either plant tissue or wheatgrass variety. In silico digests of the ribosomal database produced putative identifications indicating an increase in overall species diversity and increased relative abundances of Firmicutes and Cyanobacteria following propagation in sand and Betaproteobacteria following propagation in the peat-based growing mix. Results indicated a substantial translocation of endophytes from seed to mature plant tissues for both growing media and that growing medium was a dominant determinant of the final taxonomy of the endpoint plant endophytic communities.
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 | 0.000 | 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) | 0.000 | 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".