Models of interference in monocultures and mixtures of wheat (Triticum aestivum L.) and quackgrass (Elytrigia repens (L.) Nevski.).
Bibliographic record
Abstract
Quackgrass is the most serious perennial grassy weed of wheat in Manitoba. Field experiments and surveys investigating the nature and extent of interference in monocultures and mixtures of quackgrass and wheat were conducted over the years 1987 to 1989 at Portage La Prairie, Manitoba, Canada.\nIntraspecific and interspecific interference between spring wheat and quackgrass was investigated in the field using an additive series design consisting of five replacement series proportions at total stand densities of 75, 150, and 300 plants sqM. A revised synthetic no-interaction analysis determined that wheat was superior to quackgrass in both intraspecific and interpecific interference and that niche dedifferentiation was large. Quackgrass reproductive variable were less sensitive to interspecific interference than were vegetative variables. \nSurveys of commercial fields of spring wheat infested with quackgrass were conducted using a dynamic stratified random sampling design in which systematic samples were taken at approximately 30, 60 and 93 days after planting. Wheat yield loss, as a percentage of weed-free yield, (Yw%) was related to spring quackgrass shoot counts/m-2 (Qs) by a rectangular hyperbolic model of the form\nYw% = 98.7(1-0.433(Qs)/100(1+(0.433(Qs)/193.7))).\nWheat kernel weight was the wheat yield component most influenced by quackgrass infestation. In quackgrass populations the majority of new rhizome production occurred during wheat senescence and biomass partitioning to heads increased as quackgrass infestation increased. Allometric models of the relationship between quackgrass parts were site specific and generally became more accurate the later the sampling date. \nA set of models relating spring quackgrass infestation to yield losses in hard red spring wheat, flax, and polish canola were combined with allometric models in a multi-year spreadsheet (Lotus 1-2-3, v 3.1) model. Simulations run using the multi-year model demonstrated the potential of a spreadsheet model of assisting in weed control decisions.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".