Short‐Season Soybean Genetic Improvement Evaluated in Weed‐Free and Weedy Conditions
Bibliographic record
Abstract
ABSTRACT Previously we found that the genetic improvement rate of soybean [ Glycine max (L.) Merr.] increased as plant population increased, indicating that new cultivars were more tolerant to higher population stress. The objectives of the current work were to determine genetic improvement rates under weed interference and to examine agronomic and seed composition responses to weed interference. Twenty maturity group 0 to 00 cultivars released from 1934 to 2007 were grown at Ottawa, ON, from 2006 to 2008 under weed‐free and naturally weedy conditions in a split strip trial. Over all cultivars, yield loss due to weeds ranged from 11 to 80% over years. Genetic improvement under weed‐free conditions ranged from 12.1 to 16.6 kg ha −1 yr −1 , similar to previous estimates. Under weedy conditions, estimates of genetic improvement decreased as weed pressure increased, ranging from 14.2 kg ha −1 yr −1 with 11% yield loss to 1.2 kg ha −1 yr −1 with 80% yield loss. Weed interference resulted in inconsistent changes in maturity, plant height, lodging, seed size, and seed protein and oil concentration across the 3 yr of this study. Canopy development was estimated using a measurement of green area from digital images. In weed‐free soybean canopies, newer soybean cultivars had a slower rate of development compared to older cultivars. New cultivars were not more tolerant to weed interference but also were not inferior to old cultivars under weedy conditions.
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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 | 0.001 |
| 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".