Relationship between matric suction and leaf indices of <i>Schefflera arboricola</i> in biochar amended soil
Bibliographic record
Abstract
Stomatal conductance (SC) and chlorophyll concentration (CC) are sensitive to soil matric suction (ψ). The relationship between these two plant parameters and ψ in the root zone can help understand the water uptake efficiency and photosynthetic capacity of a plant. This paper aims to quantify the relationships between SC and CC with ψ, for Schefflera arboricola grown in compacted bare silty sand and biochar amended soil (BAS). Plant parameters (SC, CC, leaf area (LA), root length (RL)) and ψ were regularly monitored in an atmospheric controlled room. The maximum recorded SC was greater in BAS than that in bare soil due to the higher water demand of LA. Based on measured data upon evapotranspiration, two equations are proposed to interpret the effects of ψ on plant water uptake and photosynthesis. A fitting equation is established to relate normalized SC with ψ to identify a threshold suction ([Formula: see text]; indicator of drought stress resistance). The magnitude of [Formula: see text] is found to be mainly dependent on LA/RL ratio and root ends. Furthermore, a new relationship between CC and ψ is observed and developed. A decrease in CC at higher ψ is attributed to leaf senescence and stomatal closure, restricting plant to produce more chlorophyll.
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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".