Relationship of Carbon Isotope Discrimination to Water Use Efficiency and Productivity of Barley Under Field and Greenhouse Conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This study was conducted to evaluate the application of carbon isotope discrimination (CID) as a selection criterion for improving water use efficiency (WUE) and productivity of barley ( Hordeum vulgare L.) under field and drought‐stress conditions in a greenhouse. A total of 54 genotypes were screened for variability in CID under field conditions, while 23 genotypes were evaluated under water‐deficit conditions in the greenhouse. A survey of leaf CID of 54 genotypes at two field locations showed more than 2.14‰ difference between extreme genotypes. Significant (P ≤ 0.05) genotypic variation was found in WUE and CID that had a negative strong correlation. There was a negative correlation between leaf CID and aerial biomass in the greenhouse and among six‐row genotypes in the field. Correlations between leaf CID across field locations and across irrigation regimes in the greenhouse were significant (experiment 1, r = 0.79 and 0.94 for six‐ and two‐row genotypes), suggesting stability of the CID trait across different environments. Overall, these results indicate the potential of leaf CID as a reliable method for selecting for high WUE and productivity in barley breeding programmes in the Canadian prairies. Further work is currently underway to determine heritability/genetics of leaf CID and application of molecular marker‐assisted selection for the traits in barley breeding programmes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it