Post-flowering dry matter accumulation and partitioning and timing of crop maturity in chickpea in western Canada
Bibliographic record
Abstract
A field experiment aimed at determining whether timing of crop maturity was related to patterns of dry matter (DM) accumulation and partitioning to reproductive organs in chickpea was conducted at different locations in Saskatchewan over two seasons, 2003 and 2004. Five genotypes 272-2, 298T-9, E100Ym, CDC Anna, and CDC Frontier were grown in a RCB design with four replications. Beginning at 60 d after seeding (DAS) and every 15 d following, plant samples were taken and separated into stem, leaf and pod fractions. Then dry weights of the sample fractions were determined. Total DM production showed an increasing trend over sampling dates, but the increase was at a decreasing rate beginning in mid-season. The early genotype 272-2 had a pattern of total DM accumulation similar to the others, but had significantly smaller vegetative (stem plus leaf) DM accumulation during the latter part of the growth period. This shows a relatively high proportion of DM partitioning to pod for 272-2. Also, the partitioning of resources to reproductive parts (allometric partitioning) and pod harvest index were each negatively associated with days to maturity, implying that assimilate partitioning for maximum pod DM is important for early maturity in chickpea in western Canada. Key words: days to maturity, post-flowering growth, dry matter, dry matter partitioning, pod harvest index
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".