Effects of some salts and sodicity on the growth of a <i>Rhizobium leguminosarum</i> bv. <i>viceae</i> strain isolated from a salt-affected soil
Bibliographic record
Abstract
The effects of sodium (Na+), calcium (Ca2+), magnesium (Mg2+), and boron (B) concentrations and sodicity, as measured by the sodium adsorption ratio (SAR), on the growth of a Rhizobium leguminosarum bv. viceae strain isolated from a salt-affected soil were studied. The rate of growth was measured in a yeast extract-mannitol broth, amended with salts having electrical conductivity (EC) of 4, 8, and 16 dS x m(-1). Each salinity level was prepared to achieve SAR values of 10, 20, and 30 with or without graded B concentrations of 0.5, 1, 3, and 5 mg x L(-1). We found that salinity levels equal to or more than 8 dS x m(-1) had negative effects on Rhizobium growth during the first days of incubation, but the effects became less pronounced after 1 week. Na+ concentrations of more than 1.1 g x L(-1) retarded growth, especially at high SAR values (i.e., at low Ca2+ concentrations). The retardation of growth increased with increases in EC up to 16 dS x m(-1), at all sodicity levels. Mg2+ added together with Na+ or with Ca2+ + Na+ affected growth more negatively than Ca2+ + Na+ alone. The effect of Mg2+ became more pronounced with increased salinities and sodicities. It was concluded that EC of more than 4 dS x m(-1) retarded growth of Rhizobium, but only at high sodicity levels. The relative specific ion effect on growth was in the order Na+ < Ca2+ < Mg2+. The harmful effect of Mg2+ on this strain was accentuated by adding Ca2+ to the cultural medium. When SAR increased from 10 to 30, Na+ had no clear effect on growth, irrespective of the accompanied cations, i.e, Ca2+, Mg2+, or Ca2+ + Mg2+. Growth was reduced by B concentrations as low as 0.5 mg x L(-1), and the B effect was enhanced by increased salinity.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".