Summer (Subarctic) versus Winter (Subtropic) Production Affects Spinach (<i>Spinacia oleracea</i> L.) Leaf Bionutrients: Vitamins (C, E, Folate, K<sub>1</sub>, provitamin A), Lutein, Phenolics, and Antioxidants
Bibliographic record
Abstract
Comparison of spinach (Spinacia oleracea L.) cultivars Lazio and Samish grown during the summer solstice in the subarctic versus the winter solstice in the subtropics provided insight into interactions between production environment (light intensity), cultivar, and leaf age/maturity/position affecting bionutrient concentrations of vitamins (C, E, folate, K1, provitamin A), lutein, phenolics, and antioxidants. Growing spinach during the winter solstice in the subtropics resulted in increased leaf dry matter %, oxidized (dehydro) ascorbic acid (AsA), α- and γ-tocopherol, and total phenols but lower reduced (free) AsA, α-carotene, folate, and antioxidant capacity compared to summer solstice-grown spinach in the subarctic. Both cultivars had similar bionutrients, except for higher dehydroAsA, and lower α- and γ-tocopherol in 'Samish' compared to 'Lazio'. For most bionutrients measured, there was a linear, and sometimes quadratic, increase in concentrations from bottom to top canopy leaves. However, total phenolics and antioxidant capacity increased basipetally. The current study has thus demonstrated that dehydroAsA, α-tocopherol, and γ-tocopherol were substantially lower in subarctic compared to subtropical-grown spinach, whereas the opposite relationship was found for antioxidant capacity, α-carotene, and folates (vitamin B9). The observations are consistent with previously reported isolated effects of growth environment on bionutrient status of crops. The current results clearly highlight the effect of production environment (predominantly radiation capture), interacting with genetics and plant phenology to alter the bionutrient status of crops. While reflecting the effects of changing growing conditions, these results also indicate potential alterations in the nutritive value of foods with anticipated shifts in global climatic conditions.
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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".