Relative Growth Rate of Six Soybean Genotypes Under Iron Toxicity Condition
Bibliographic record
Abstract
The objective of the research was to study relative growth rate of six soybean genotypes under iron toxicity condition. The design was factorial design, with two factors; arranged in completely randomized design with three replications. The first factor was Fe concentration, consisted of two levels, i.e. (1) 0 ppm Fe and (2) 375 ppm Fe where after 7 days the acidity was not maintain at pH 3.5. The second factor was genotype, consisted of 6 genotypes, i.e. two tolerant genotypes (MLGG 0799 and MLGG 0492), three susceptible genotypes (MLGG 0915, MLGG 0768 and MLGG 0169) and one check swampland tolerant-variety (Lawit). The results showed that genotypes of MLGG 0799 and MLGG 0768 had higher rhizosphere pH levels than other genotypes. MLGG 0492 had potency to self recovery better than other genotypes based on relative growth rate (RGR) of root dry weight, plant height and plant dry weight. MLGG 0492 may have different mechanism than others because this genotype remained to have higher RGR, although it was unable to increase the rhizosphere pH. Under control and Fe treatment conditions, Lawit had no significant difference of RGR of plant dry weight to other susceptible genotypes.
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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) | 0.000 | 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 | 0.001 |
| 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".