Bibliographic record
Abstract
Early physiological mechanisms that occur in crop plants in response to neighboring weeds are not well understood. In this experiment, it was hypothesized that, in the absence of direct competition for resources, low red to far red ratio (R:FR) reflected from neighboring weeds will modulate the phenylpropanoid pathway, increase hydrogen peroxide (H2O2), and up-regulate the expression of ethylene biosynthesis and auxin transport genes. Laboratory experiments were conducted under conditions of nonlimiting resources using perennial ryegrass as a model weed species. We discovered that the detection by phytochrome (Phy) of low R:FR signals reflected from both biological and nonbiological sources triggered an up-regulation of ethylene biosynthesis genes and stimulated an auxin transport gene. The low R:FR also modulated the phenylpropanoid pathway resulting in a reduction in anthocyanin content and an enhancement of lignin synthesis. The presence of neighboring weeds also caused an accumulation of H2O2in the first leaf and crown root tissues of the maize seedling. Stomata were observed to be closed as H2O2accumulated in leaf tissue. This is the first study to report the modulation of phenylpropanoid pathway and the accumulation of H2O2attributed to low R:FR. We further suggest that these physiological changes that occur in response to early weed competition result in a physiological cost to the crop plant, which contributes to the rapid loss in yield observed in weed competition studies conducted under field conditions.
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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) | 0.001 | 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".