Enhancing selenium biofortification: strategies for improving soil-to-plant transfer
Bibliographic record
Abstract
Selenium (Se) is one of the essential trace elements for humans. Plants are the main source of Se for humans, while soil Se is the primary source of Se for plants. Biofortification, which involves the transfer of Se from soil to plants and animals, is currently recognized as the safest and most effective approach for Se supplementation for humans. However, Se in soil primarily exists in forms that plants cannot easily utilize, so enhancing Se transfer from soil to plants is crucial for optimal Se utilization. In this paper, we provided a comprehensive analysis of Se forms in soil. Then we summarized the strategies for enhancing Se transfer from soil to plants. These strategies include adjusting redox potential, managing soil moisture, modulating pH value, improving organic matter, optimizing ion competition, promoting beneficial microbes, and considering the synergy between plant rhizosphere and soil. Furthermore, we reviewed Se forms and metabolism after uptake into plants to better understand its role in human health. Finally, we came up with the challenges and perspectives, to provide new insights for further study in this area. This work also offers potential solutions for enhancing Se transformation from soil to plants and utilizing soil Se to produce naturally Se-rich products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".