The effect of application of genistein to <i>Bradyrhizobium japonicum</i> culture and its rooting medium on soyabean growth nodulation and nitrogen assimilation in the presence of nitrate
Bibliographic record
Abstract
In the soyabean [Glycine max (L.) Merr.]–B. japonicum symbiosis, genistein has been identified as one of the major compounds in soyabean seed and root extracts responsible for inducing the expression of the B. japonicum nod genes. High combined nitrogen in the growth medium inhibits nodulation and nitrogen assimilation. Two experiments were conducted to test the possibility of overcoming this inhibition by adding genistein to the rooting medium and by incubation of B. japonicum cells with genistein. One soyabean cultivar was used in the first experiment, and two in the second experiment. The experiments were conducted in a glasshouse using a completely randomized design with three rooting medium nitrate concentrations (0, 5 and 10 mM) and four genistein treatments. The genistein treatments were 0 (control), incubation of B. japonicum cells with 5 μM genistein, and regular watering with 5 μM or 20 μM genistein. A two way interaction existed in the first experiment, and two and three way interactions existed in the second experiment. Root growth was inhibited by repeated watering with 20 μM genistein. Weight per nodule was greater at 5 mM than at 0 mM nitrate. At 10 mM nitrate watering with genistein resulted in significant increases in nodule dry weight per plant. Shoot nitrogen contents were significantly increased at 5 mM nitrate by genistein incubation and watering with 20 μM genistein. Watering with 5 μM genistein significantly increased nodule nitrogen concentrations at both 5 and 10 mM nitrate. The two soyabean cultivars responded differently to the genistein and nitrate treatments in terms of nodule number, nodule weight, leaf nitrogen concentration and nodule nitrogen content. Genistein could, at least partially, overcome the inhibition of soyabean nodulation and nitrogen assimilation by nitrate.
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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) | 0.001 | 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".