Early physiological and biochemical responses of soyabean to neighbouring weeds under resource‐independent 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
Summary The mechanisms by which weeds compete with crop plants are poorly understood. To gain insight into these mechanisms, we characterised early physiological responses of soyabean to neighbouring weeds using a biological weedy system that generated a consistent far‐red‐enriched light environment and excluded direct resource competition. Neighbouring weeds decreased superoxide dismutase activity in unifoliate leaves. This coincided with increased hydrogen peroxide (H 2 O 2 ) and oxidized ascorbate levels, while the steady‐state level of superoxide, catalase activity and lipid peroxidation remained unchanged. These responses suggested increased leaf production of singlet oxygen ( 1 O 2 ), which was demonstrated by detection of increased Singlet Oxygen Sensor Green ( SOSG ) fluorescence within 3 h after staining of unifoliate leaves. This finding was further supported by increased ratios of the photosensitiser protochlorophyllide to both chlorophyllide a , and total chlorophyll in the dark as well as enhanced sensitivity to cell death by a 1 O 2 ‐generating compound in the light. These responses coincided with dramatic changes in photosynthesis, carbon partitioning and biomass allocation with a persistent decline in leaf sucrose level and biomass production at later growth stages. This study provides direct experimental evidence that under resource‐independent competition, far‐red‐enriched light reflected by neighbouring weeds can alter the balance between ROS production and detoxification and thereby generate an oxidative stress signal in soyabean leaves.
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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 | 0.000 | 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 it