Study on the Role of Selenium in Enhancing Stress Resistance and Quality Improvement of Strawberries
Bibliographic record
Abstract
Strawberries are widely favored for their high nutritional value and economic benefits, but their yield and quality are often constrained by various environmental stresses. This study explores the mechanisms by which selenium alleviates salt stress, heavy metal pollution, and drought stress in strawberries, including enhancing antioxidant enzyme activity, optimizing water use efficiency, and maintaining cell membrane stability to improve stress tolerance. The results demonstrate that selenium application promotes strawberry growth and development under extreme conditions, enhances fruit quality, and boosts market competitiveness. Moreover, selenium biofortification effectively increases the content of functional compounds such as flavonoids and polyphenols in strawberry fruits, significantly improving sugar-acid balance and flavor characteristics. However, further research is needed to optimize selenium application, focusing on dosage, safety, and synergistic interactions with other nutrients for practical agricultural promotion. This study provides critical insights for the development of selenium-enriched strawberry varieties and sustainable agricultural practices.
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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".