Interspecific competition in a pecan–cotton alleycropping system in the southern United States: Production physiology
Bibliographic record
Abstract
A study was conducted on a Red Bay sandy loam soil (Rhodic Paleudult) in Jay, Florida, USA, to investigate how interspecific interactions between pecan ( Carya illinoensis K. Koch) and cotton ( Gossypium hirsutum L.) would affect cotton leaf morphology and gas exchange and thereby biomass and lint yield. We quantified specific leaf area (SLA), specific leaf nitrogen (SLN), net photosynthesis (A), transpiration, stomatal conductance, and net canopy photosynthetic index (CNPI) from cotton with and without aboveground and belowground interactions. To separate roots of cotton and pecan, polyethylene-lined trenches were installed (barrier treatment) parallel to tree rows in half the number of plots. Results showed that SLA for barrier and nonbarrier plants was 61% and 47% higher, respectively, compared with the monoculture cotton. Monoculture plants exhibited higher CNPI (70.7 μmol·m–2·s–1) compared with the barrier (52.7 μmol·m–2·s–1) and nonbarrier plants (18.3 μmol·m–2·s–1). SLN was similar for both the barrier and nonbarrier plants; however, it was lower than the monoculture. A positive curvilinear relationship between A and SLN was observed, with peak A (28 μmol·m–2·s–1) observed between 2.2 and 2.4 mg N·m–2. Significant curvilinear relationships between CNPI and aboveground biomass and lint yield were also observed for all treatments. These findings indicate that competitive interactions in alleycropping regulate leaf level traits such as SLA and SLN by altering water and light availability, which in turn exert a profound influence on aboveground biomass and lint yield for cotton plants.
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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 | 0.001 | 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".