Selenium Biofortification and Interaction With Other Elements in Plants: A Review
Bibliographic record
Abstract
Selenium (Se) is an essential element for humans and animals and its deficiency in the diet is a global problem. Crop plants are the main source of Se for consumers. Therefore, there is much interest in understanding the factors that govern the accumulation and distribution of Se in the tissues of crop plants and the mechanisms of interaction of Se absorption and accumulation with other elements, especially with a view toward optimizing Se biofortification. An ideal crop for human consumption is rich in essential nutrient elements such as Se, while showing reduced accumulation of toxic elements in its edible parts. This review focuses on (a) summarizing the nutritional functions of Se and the current understanding of Se uptake by plant roots, translocation of Se from roots to shoots, and accumulation of Se in grains; and (b) discussing the influence of nitrogen (N), phosphorus (P), and sulfur (S) on the biofortification of Se. In addition, we discuss interactions of Se with major toxicant metals (Hg, As, and Cd) frequently present in soil. We highlight key challenges in the quest to improve Se biofortification, with a focus on both agronomic practice and human health.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".