First versus last born: Flowers, pods, and yield formation in no‐tillage lentil
Bibliographic record
Abstract
Abstract Lentil ( Lens culinaris Medik.) is a grain legume crop grown under no‐tillage (NT) management and rhizobia inoculation in the northern Great Plains. Our goal was to characterize pod growth characteristics to understand yield formation in North American short‐season cultivars. Objectives were to compare pods on nodes during early and late reproductive growth through flower and pod number, pod setting percentage, pod growth rate, effective pod‐filling period, and final pod size, and to test if N fertility could increase pod numbers and pod growth under NT management. Two field experiments, Study 1 and Study 2, were conducted at Saskatoon and Indian Head, SK, in western Canada. For Study 1, cultivar CDC Sedley was treated with 0–60 kg N ha −1 on long‐term NT fields for 3 yr (2006–2008). For Study 2, eight cultivars from three maturity classes were grown under control, inoculant, and N fertilizer regimes under NT at Saskatoon (2006 and 2007). Lentil set more yield in early‐flowering nodes via flower number, with 2.6 flowers node −1 . Late nodes had fewer (2.1) flowers but the same pod setting percentage of 80% for CDC Sedley, and a lower percentage across eight cultivars. Late nodes produced pods with greater growth rates and shorter filling times, resulting in fewer but similar sized pods. The largest pods were found on nodes with fewer flowers and when moisture was adequate during filling. Drought stress in 2007 occurred and lowered pod setting to 60% and shortened the effective pod‐filling period during late reproductive drought. During the two wet years, higher N rates increased late‐season pod growth rate, but not flower numbers. An increase in late node and flower production may further improve yield, particularly in large‐seeded cultivars.
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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 | 0.001 |
| 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 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".