Hypobaria, hypoxia, and light affect gas exchange and the CO<sub>2</sub>compensation and saturation points of lettuce (<i>Lactuca sativa</i>)This paper is one of a selection published in a Special Issue comprising papers presented at the 50th Annual Meeting of the Canadian Society of Plant Physiologists (CSPP) held at the University of Ottawa, Ontario, in June 2008.
Bibliographic record
Abstract
There are important engineering and crop production advantages in growing plants under hypobaric (reduced atmospheric pressure) conditions for extraterrestrial base or spaceflight environments. The objectives of this research were to determine the influence of hypobaria and reduced partial pressure of oxygen (pO2) (hypoxia) under low and high light irradiance on carbon dioxide (CO2) assimilation (CA), dark-period respiration (DPR), and the CO2compensation and CO2saturation points of lettuce (Lactuca sativa L. ‘Buttercrunch’). Plants were grown under variable total gas pressures [25 and 101 kPa (ambient)] at 6, 12, or 21 kPa pO2(approximately the partial pressure in air at normal pressure). Light irradiance at canopy level of the low-pressure plant growth system (LPPG) was at 240 (low) or 600 (high) µmol·m–2·s–1. While hypobaria (25 kPa) had no effect on CAor the CO2compensation point, it reduced the DPR and the CO2saturation point, and increased the CA / DPR ratio. Hypoxia (6 kPa pO2) and low light reduced CA, DPR, and the CA / DPR ratio. Hypoxia decreased the CO2compensation point regardless of total pressure. Hypoxia also decreased the the CO2saturation point of ambient-pressure plants, but had no effect on hypobaric plants. While low light reduced the CO2saturation point, it increased the CO2compensation point, compared with high-light plants. The results show that hypobaric conditions of 25 kPa do not adversely affect gas exchange compared with ambient-pressure plants, and may be advantageous during hypoxic stress.
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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".