The ability of 29 barley cultivars to compete and withstand competition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Using competitive crops and cultivars can be an important integrated weed management (IWM) tool, useful in both conventional and low-external-input (LEI) farming systems. Barley is considered a competitive crop, but cultivar competitiveness varies. There are two aspects of cultivar competitive ability; the ability to compete (AC) and the ability to withstand competition (AWC). However, the relationship between these aspects has not been addressed in barley. A study was conducted to explore aspects of barley cultivar competitive ability with oats, and to examine the feasibility of ranking cultivars based on either, or both, AWC and AC. Field trials were undertaken in 2001 and 2002 to determine cultivar competitive ability for 29 barley cultivars commonly grown on the Canadian prairies. Cultivars were selected from semidwarf and full height, hulled and hull-less, 2- and 6-row, and feed and malt classes. Yield loss ranged from 6 to 79% while weed seed return ranged from 10 to 83% of gross yield. As a class, semidwarf and hull-less cultivars were less competitive than full height and hulled cultivars, respectively. However, considerable variation existed within these classes, and an absolute relationship between class membership and competitive ability did not exist. Ability to withstand competition was significantly correlated with ability to compete, but correlation coefficients were not strong enough to attempt reliable co-selection within a breeding program. Ability to compete was a more consistent measure of competitive ability than AWC. Ranking barley cultivar competitive ability would make it a valuable IWM tool for farmers and extension personnel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 it