Relationship of physiological characters to yield parameters in oilseed rape (<i>Brassica napus</i> L.)
Bibliographic record
Abstract
The physiological basis of seed yield in oilseed rape (Brassica napus L.) still remains unclear, and conclusions on the contribution of such traits to seed yield are difficult to make. Nine cultivars, classified into three yield groups (high, medium and low) based on significant differences in seed yield from previous trials, were tested over two locations and years. Leaf chlorophyll content, net photosynthetic rate per unit leaf area (PA), per unit leaf dry matter (PDM) and per unit leaf chlorophyll (PC), transpiration rate (TR) and water use efficiency (WUE) were investigated on fully expanded leaf numbers 4 (vegetative), 6 (early flowering) and 8 (early podding stage) on the main stem and related to seed yield, total dry matter (TDM) and harvest index (HI) of each yield group. Differences among yield groups for seed yield, TDM and HI were significant. Chlorophyll content was lowest on leaf 4, but increased with leaf age. Correlations between net photosynthetic rate and seed yield were not found. However, cultivars in the high yield group maximized their net photosynthetic rates (PA, PDM, and PC) on leaf 6 during early flowering at the time when TR was lowest and WUE at its highest. In the medium and low groups, photosynthetic rates were highest on leaf 4, but decreased to lowest values on leaf 8, together with the high yield group. In general, the results indicate that the largest contribution to net photosynthesis by oilseed rape leaves occurred during the vegetative and early flowering stages compared with the early pod-filling stage. Key words: Total dry matter, harvest index, photosynthesis, chlorophyll
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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) | 0.000 | 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 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".