Toxicity and Translocation of Selenium in Phaseolus vulgaris L.
Bibliographic record
Abstract
Selenium (Se) is not considered an essential nutrient for plants, although trace amounts of this element can enhance the growth and yield of some plant species. The application of sodium selenate in staple foods has been proposed as an alternative to minimize Se deficiency in the human diet. However, the threshold between deficiency and toxicity for Se is very narrow. Different plant species vary considerably in the absorption and accumulation of Se in shoots and other edible parts, and also in the tolerance to high Se concentrations in the soil. Therefore, this study aimed to evaluate the Se toxicity in common bean plants grown under high doses of sodium selenate, and the Se translocation of contaminated bean seeds to next generation grains. The study was carried out on a field experiment with the application of four rates of sodium selenate (0, 50, 500 and 5000 g/ha) to the soil were common bean crop was grown. Following, greenhouse conditions were used to investigate the translocation of Se from enriched seeds to the grains. The common bean showed tolerance to sodium selenate rates up to 500 g/ha, with reduction of yield observed at rate of 5000 g/ha. Even with no symptoms of toxicity the application rates of 500 g/ha of sodium selenate to the soil produced grains with concentrations of Se that surpass the limit established by Brazilian food law. The seeds enriched with Se can translocate this nutrient to the next generation.
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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 | 0.000 |
| 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".