ENHANCING THE GROWTH OF<i>VICIA FABA</i>PLANTS BY MICROBIAL INOCULATION TO IMPROVE THEIR PHYTOREMEDIATION POTENTIAL FOR OILY DESERT AREAS
Bibliographic record
Abstract
Two experiments were conducted to investigate the effect of inoculating Vicia faba plants (broad beens) raised in clean and oily sand with nodule-forming rhizobia and plant-growth-promoting rhizobacteria (PGPR) on growth of these plants in sand and to test whether this can improve the phytoremediation potential of this crop for oily desert areas. It was found that crude oil in sand at concentrations < 1.0% (w/w) enhanced the plant heights, their fresh and dry weights, the total nodule weights per plant, and the nitrogen contents of shoots and fruits. Similar enhancing effects were recorded when roots of the young plants were inoculated with nodule bacteria alone, PGPR alone, or a mixture of one strain of nodule bacteria and one of the PGPR. Such plant growth effects were associated with a better phytoremediation potential of V. faba plants for oily sand. The total numbers of oil-utilizing bacteria increased in the rhizosphere and more hydrocarbons were eliminated in sand close to the roots. The nodule bacteria tested were two strains of Rhizobium leguminosarum and the PGPR were Pseudomonas aeruginosa and Serratia liquefaciens. The four strains were found to use crude oil, n-octadecane, and phenanthrene as sole sources of carbon and energy. It was concluded that coinoculation of V. faba plant roots in oily sand with nodule bacteria and PGPR enhances the phytoremediation potential of this plant for oily desert sand through improving plant growth and nitrogen fixation.
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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 | 0.000 | 0.001 |
| 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".