Selenium distribution and nitrate metabolism in hydroponic lettuce (Lactuca sativa L.): Effects of selenium forms and light spectra
Bibliographic record
Abstract
A deficiency in selenium (Se) in the human diet is a worldwide problem. The intake of Se-rich vegetables can be a safe way to combat Se deficiency for humans. However, most leafy vegetables can accumulate a high content of nitrates, which poses a potential threat to human health. Light is an important environmental factor that regulates the uptake and distribution of mineral elements and nitrogen metabolism in plants. However, the effects of Se forms and light conditions, especially light spectra, on the uptake and translocation of Se and on nitrate reduction are poorly understood. In this study, lettuce (Lactuca sativa L.) was treated with exogenous Se applied as selenate (10 mmol L−1) and selenite (0.5 mmol L−1) and grown under five different light spectra: fluorescent light (FL), monochromatic red LED light (R), monochromatic blue LED light (B), and mixed red and blue LED light with a red to blue light ratio at 4 (R/B=4), 8 (R/B=8), and 12 (R/B=12), respectively. The effects of light spectra and Se forms on plant growth, photosynthetic performance, Se accumulation and nitrate reduction were investigated. The results showed that the light spectra and Se forms had significant interactions for plant growth, foliar Se accumulation and nitrate reduction. The Se concentration and nitrate content in the leaves were negatively correlated with the percentage of red light from the light sources. Compared to Se applied as selenite, exogenous Se applied as selenate was more effective in reducing nitrate via promoting nitrate reductase and glutamate synthase activities. The lowest nitrate content and highest plant biomass were observed under R/B=8 for both the selenate and selenite treatments. The significant effect of the light spectra on the root concentration factor and translocation factor of Se resulted in marked variations in the Se concentrations in the roots and leaves. Compared with FL, red and blue LED light led to significant decreases in the foliar Se concentration. The results from this study suggest that the light spectra can contribute to Se distribution and accumulation to produce vegetables with better food quality.
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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".