Carbon Gain, Water Use and Nutrient Uptake Dynamics of Beet (<italic>Beta vulgaris</italic>) Grown in Controlled Environments
Bibliographic record
Abstract
Due to its large proportion of edible biomass, beet (Beta vulgaris) has high potential as a candidate crop for bioregenerative life support systems. This paper summarizes data collected for beet under batch and staged stand culture in closed environment chambers. Full stand trials were conducted under the following conditions: 1000 μL L−1 atmospheric carbon dioxide concentration, light intensities ranging from 400–600 μmol m−2 s−1 PAR with a 14 hour photoperiod, 73% ± 5% relative humidity, a 26/20 °C day/night temperature regime and a fixed planting density of 17.6 plants m−2. For batch planted stands, total edible yield was determined to be 28.3 g dry weight basis (dwb) with a 95% Confidence Interval (CI) of [24.7, 31.8] g plant−1 with a harvest index of 94%. Under similar conditions, yield for staged beet stands was 31.4 g dwb with a 95% CI of [24.54, 38.31] g plant−1. Water use efficiency under these same conditions was found to be 0.003 mol C mol−1 H2O. Relative nitrate, ammonium, phosphate and potassium uptake rate averaged 0.11. Data indicate that a square meter of beet in production would supply roughly 2% of the daily air revitalization requirement of a single crew member.
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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".