Influence of Day Length on Stem Growth, Flowering, Morphology of Flower Clusters, and Seed-Set in Buckwheat (<i>Fagopyrum esculentum</i>Moench)
Bibliographic record
Abstract
The effects of day length on main stem growth, flowering, morphology of flower clusters and seed-set were examined in three buckwheat cultivars Shinanonatsusoba (summer eco-type), Miyazakizairai (autumn eco-type) and BLO 1999 (a long cluster line which usually develops DM clusters at Kade Research Ltd., Canada). Long-day treatment prolonged the stem elongation period, elevated the first flowering node, delayed the first flowering day, increased the numbers of nodes, flower clusters and flowers on the main stem, and decreased the increase rate of flowering-cluster number, the number of seeds and the seed-set ratio on the main stem. It also increased the frequency of DM clusters, the length of the flower clusters and the number of sub-flower-clusters per cluster in Shinanonatsusoba and Miyazakizairai as well as in BLO 1999. The effects of day length varied among the growth parameters and there were three types of responses to day length. The difference between the summer and autumn eco-type cultivars in the responses to day length was elucidated in four groups of parameters; (1) main stem elongation; (2) first flowering node and first flowering day; (3) increase rate of flowering-cluster number on the main stem; and (4) the number of seeds and seed-set ratio.
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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".