Isolation, selection, and characterization of beneficial rhizobacteria from pea, lentil, and chickpea grown in western Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of beneficial soil microorganisms as agricultural inputs for improved crop production requires selection of rhizosphere-competent microorganisms with plant growth-promoting attributes. A collection of 563 bacteria originating from the roots of pea, lentil, and chickpea grown in Saskatchewan was screened for several plant growth-promoting traits, for suppression of legume fungal pathogens, and for plant growth promotion. Siderophore production was detected in 427 isolates (76%), amino-cyclopropane-1-carboxylic acid (ACC) deaminase activity in 29 isolates (5%), and indole production in 38 isolates (7%). Twenty-six isolates (5%) suppressed the growth of Pythium sp. strain p88-p3, 40 isolates (7%) suppressed the growth of Fusarium avenaceum, and 53 isolates (9%) suppressed the growth of Rhizoctonia solani CKP7. Seventeen isolates (3%) promoted canola root elongation in a growth pouch assay, and of these, 4 isolates promoted the growth of lentil and one isolate promoted the growth of pea. Fatty acid profile analysis and 16S rRNA sequencing of smaller subsets of the isolates that were positive for the plant growth-promotion traits tested showed that 39%-42% were members of the Pseudomonadaceae and 36%-42% of the Enterobacteriaceae families. Several of these isolates may have potential for development as biofertilizers or biopesticides for western Canadian legume crops.
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.
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) | 0.000 | 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 it