Pot size matters revisited: does container size affect the response to elevated CO2 and our ability to detect genotypic variability in this response in wheat?
Bibliographic record
Abstract
Many studies have investigated the effect of elevated CO2 (eCO2) in wheat, although few have evaluated the potential of genotypic variability in the response. Such studies are the next logical step in wheat climate change adaptation research, and they will require the evaluation of large numbers of genotypes. For practical reasons the preliminary studies are most likely to be conducted in controlled environments. There have been concerns that the root restriction related to container-grown plants can influence (1) the response to eCO2, (2) the detection of genotypic variability for various traits of interest, and (3) the ability to find the genotypes most responsive to eCO2. In the present study we evaluated two sizes of container - 1.4L pots and 7.5L columns - side-by side in a glasshouse environment and found that for 14 of 23 traits observed environment effects (ambient CO2, eCO2 or eCO2 and high temperature) were not consistent between plants grown in pots and in columns. More importantly, of the 21 traits showing genotypic variability, only 8 showed consistent genotype differences and rankings across both container types. Statistical analyses conducted separately for plants grown in pots or in columns showed different cultivars as being the most responsive to elevated CO2 and would thus, have led to different conclusions. This study is intended as a message of caution to controlled environment experimenters: using small containers can artificially create conditions that could either hide or overly express genotypic variability in some traits in response to eCO2 compared with what might be expected in larger containers.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".