Aspects of interspecific competition in maize (Zea mays L.)
Bibliographic record
Abstract
Interspecific competition is comprised of both resource dependant and resource independent processes. While many studies have focused on the role that resource dependant competition plays in reducing crop yields, few have investigated whether resource independent effects, such as light or hormonal signaling, may contribute to these yield losses. The focus of this thesis was to investigate the role of the shade avoidance response in determining the onset and outcome of crop-weed competition in maize ('Zea mays ' L.). The results of greenhouse and field trials demonstrate that shade avoidance in maize can be induced shortly after seedling emergence and that the effects of this early response can be detected throughout the entire life cycle of the crop. Seedlings exposed to a weedy or low red to far-red light (R/FR) environment at emergence displayed an initial increase in plant height and a reduction in the root-to-shoot ratio. These effects were followed by a reduction in the rate of leaf appearance (RLA) and a linear decline in biomass and leaf area (LA) as the duration of time spent in a weedy environment increased. Conversely, seedlings emerging in a weed-free or ambient R/FR environment were unaffected regardless the duration of time spent in the weedy environment. These effects of early crop-weed competition are distinct from those of plant population density (i.e., intraspecific competition). Results of a field trial demonstrated that intraspecific competition at a conventional density of 8 plants m-2 did not negatively impact RLA or biomass accumulation until well after the defined critical period for weed control. Moreover, intraspecific competition at 16 plants m-2 was not detected until the 12th leaftip stage, suggesting that the effects of crop density are more closely associated with canopy closure than an early shade avoidance response. At maturity, seedlings that expressed shade avoidance at early stages of development set fewer kernels and partitioned less biomass to the developing ear. Shade avoidance also doubled the plant-to-plant variability in yield parameters without affecting the mean or frequency distribution of shoot biomass at maturity. When taken together, the results of these studies indicate that shade avoidance destabilizes stand productivity by increasing plant-to-plant variability in reproductive effort prior to intra- or interspecific competition for resources.
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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".